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IJSRET Volume 7 Issue 2, Mar-Apr-2021

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Strength Analysis by Utilization of Plastic PET Bottles In Concrete Material
Authors:-Priyanka Yadav, Mr. Anuj Verma

Abstract:-Plastic waste disposal in the environment is a big problem since it is impossible to biodegrade and has a broad footprint. Plastic recycling was practiced on a wide scale in India. Recycling from various sources accounts for up to 60% of industrial and urban plastic waste. Recently, plastic waste has been studied as a possible replacement for a portion of the current concrete aggregates. In this study, trials and measurements were carried out in order to evaluate the effectiveness of waste plastic reuse in concrete building. Waste plastic was used to partially replace sand in 0 percent, 1 percent, 2 percent, 3 percent, 4 percent, and 5 percent of concrete blends. The concrete cubes were tested at room temperature. Slumping and compression are needed for these measurements. This study ensures that reusing plastic waste as a substitute for fine concrete aggregates will result in lower material costs while still addressing the waste disposal problem.

A Review of Mechanical Properties of Fly Ash Based Geo-Polymer Concrete Used As Paver Blocks
Authors:-Awdhesh Kumar, Anuj Verma

Abstract:-The world is facing the challenges of climate changes due to the increase in CO2 emissions. Cement production is one of the biggest contributors to CO2 emissions due to combustion processes that require high temperatures. The new development in building construction showed that fly ash based Geopolymer concrete can be as structure materials to reduce or even eliminate ordinary Portland cement concrete. This paper presented the research results of fly ash based geopolymer concrete mechanical properties, like the compressive strength, flexural strength, and Elastic Modulus.Paver block is often used in alternative functions, such as those in street as well as other areas of building. So far, roof tiles and paving bricks are the only products to have been manufactured at the lab-scale. Future studies could focus on the investigation of other mechanical and durability properties of the optimum formulations, in order to find applications in the manufacturing of a variety of building materials.

A Review of Bamboo/Jute/PLA Biodegradable Composite
Authors:Subhash Kumar, Dr. Anil Kumar, Mr Amit Sharma

Abstract:-Biodegradable polymers can potentially be combined with natural fibers to produce biodegradable compositematerials. In this work, PLA (Polylactide) was used in combination with Jute fabric to generate bio-composite by compression molding technique. Various mechanical characterizations like tensile, flexural and impact properties of bio-composite were determined. The result from mechanical testing showed that use of Jute fabric with PLA, increases the tensile strength and tensile modulus, why the flexural modulus is reduced. Scanning electron microscopy (SEM) investigation also showed good bonding between the Jute fabric and PLA as there were no air voids. Water absorption results reported increase in weight of the bio-composite for 24 hrs conditioned time. The findings of this work create the scope of use of the Jute fiber/ fabric for making fully biodegradable composites for potential application as architectural interiors in building construction sector. The developed composites were also used as the replacement for mica sheets for the table top, chairs, door panels and many more.

A Review of Solar Energy Based Heat and Power Generation Systems
Authors:M. Tech. Pooja Vaishya, Prof. Barkha Khambra

Abstract:-The microgrid has shown to be a promising solution for the integration and management of intermittent renewable energy generation. This paper looks at critical issues surrounding microgrid control and protection. It proposes an integrated control and protection system with a hierarchical coordination control strategy consisting of a stand-alone operation mode, a grid-connected operation mode, and transitions between these two modes for a microgrid. To enhance the fault ride-through capability of the system, a comprehensive three-layer hierarchical protection system is also proposed, which fully adopts different protection schemes, such as relay protection, a hybrid energy storage system (HESS) regulation, and an emergency control. The effectiveness, feasibility, and practicality of the proposed systems are validated on a practical photovoltaic (PV) microgrid. This study is expected to provide some theoretical guidance and engineering construction experience for microgrids in general. The utilization of solar energy based technologies has attracted increased interest in recent times in order to satisfy the various energy demands of our society. This paper presents a thorough review of the open literature on solar energy based heat and power plants. In order to limit the scope of the review, only fully renewable plants with at least the production of electricity and heat/hot water for end use are considered. These include solar photovoltaic and solar thermal based plants with both concentrating and non-concentrating collectors in both solar-only and solar-hybrid configurations.

Disease Prediction System in New Normal
Authors:Sonal Shilimkar, Pratiksha Thosar, Prajakta Dharade, Ayushi Patel4, Asst. Prof. Varsha Pimprale

Abstract:-In this disease prediction system follows normal rules. The system is designed such that to provide a facility predicting disease from given reports. Report can be in the form of image (MRI, x-Ray, mammography, etc). Or in the form of input parameters like numerical value came with the result of reports. The system will take input from the user for a specific disease the system will follow image processing techniques to process and extract results from images. The result will be provided to a user. The system will also suggest nearby specialists for the detected disease.

Study on Concrete Properties under Acid Attacks
Authors:- Racharla Nageswara Rao, Asst. Prof. DMS Nageswara Rao

Abstract:-Acidic attack on concrete imparts unique set of injury mechanisms and manifestations compared to other durability problems with concrete. vitriol attack limits the service lifetime of concrete elements and, thus, leads to increased expenditures for the repair or in some cases replacement of the entire structure. To date, there’s lack of standardized tests for specifically evaluating the resistance of concrete to vitriol attack, which has caused great variability, for instance in terms of solution concentration, pH level/control, etc., among previous studies during this area. Accordingly, there are conflicting data about the role of key constituents of concrete (e.g. supplementary cementitious materials [SCMs]), and uncertainty about building codes’ stipulations for concrete exposed to vitriol. Hence, the primary objective of this thesis was to assess the behaviour of an equivalent concretes, prepared with single and blended binders, to incremental levels (mild, severe and really severe) of vitriol solutions over 36 weeks. The test variables included the sort of cement (general use [GU] or Portland limestone cement [PLC]) and SCMs (fly ash, silica fume and nano-silica). The severe (1%, pH of 1) and really severe aggression (2.5%, pH of 0.5) phases caused mass loss of all specimens, with the latter phase providing clear distinction among the performance of concrete mixtures. The results showed that the penetrability of concrete wasn’t a controlling factor, under severe and really severe damage by vitriol attack, whereas the chemical vulnerability of the binder was the dominant factor. Mixtures prepared from PLC performed better than that of counterparts made up of GU. While the quaternary mixtures comprising GU or PLC, fly ash, silica fume and nanosilica showed the very best mass losses after 36 weeks,binarymixturesincorporatingGUorPLCwith ash had rockbottom masslosses. Several studies reported that the improved chemical resistance of alkali-activated materials (AAMs) over concrete supported Portland cements. However, AAMs have technical limitations, which could deter its widespread use in cast-in place applications. These limitations include need for warmth curing, slow setting, and slow strength development, which could be mitigated by further improving the reactivity of AAMs during early-age with nanoparticles; however, this area remains largely unexplored. Hence, the second objective of this thesis was to develop innovative sorts of AAMs-based concrete [alkali activated ash (AAFA), alkali activated slag (AAS) and their blends incorporating nanosilica] and evaluate their resistance to 2 different vitriol exposures over 18 weeks for potential use in repair of concrete elements susceptible to acidic attack. While AAFA specimens, produced without heat curing, experienced rapid ingress of the acidic solution and a big reduction within the bond strength with substrate concrete, ash based AAMs comprising slag and or nanosilica (AAFA-S and AAFA-S-NS) had improved performance thanks to discounting the ingress of acidic solution and continued geopolymerization reactivity. Comparatively, specimens from the slag group exhibited high levels of swelling, internal cracking and mass loss thanks to chemical deterioration. The general results suggest that AAFA-S and AAFA-S-NS mixture, without heat curing, could also be a viable option for repair applications of concrete elements in acidic entrainments, but field trials are still needed to further verify their performance.

Experimental Study on Presence of Calcium Exchange Capacity on the Properties of Expansive Soils
Authors:- Sunkara Suresh, Asst. Prof. A. Sarath Babu

Abstract:- This research work presents the efficacy of salt and ash as an additive in improving the engineering properties of Black cotton soil which is expansive soil. Salt of 1%, 2% and three were mixed with black cotton soil utilized in the laboratory experiments. The ash percentages of 20% and 30% were used for compare the results obtained with salt percentages. The effectiveness of the salt and ash tested by conducting unconfined compressive strength and swelling pressure test. The unconfined compressive test has finished curing period of seven, 14, and 28 days to match the results with 0 days unconfined compressive strength. The soil samples were subjected to wet and dry cycles and observed that increase of unconfined compressive strength and reduction of swelling pressure. The results were obtained from salt mixes soil sample after wet and dry cycles has better strength, less swelling pressure and fewer swelling index.

Strength and Behavior of Concrete by Partial Replacement of Fine Aggregate with Recycled Plastic
Authors:- Nithisha Nalluri, Asst. Prof. A. Sarath Babu

Abstract:- Considering quick improvement of individuals in nations like India the discarding Solid waste is an immense issue in our bit by bit life. Distinctive waste materials are made from social event measures, association associations and normal strong squanders. The developing consideration about nature has enormously added to the worries related with ejection of the made squanders. Strong waste association is one of the critical typical worries on the planet. With the insufficiency of room for land filling and because of its always expanding cost, squander use has gotten an engaging decision instead of ejection. Among the waste material, plastic is the material that is the significant worry to by a wide margin the majority of the ordinary impacts. Examination is being done on the usage of waste plastic things in cement. The utilization of waste things in strong makes it prudent, yet besides helps in reducing removal issues. The movement of new improvement materials utilizing reused plastics is essential to both the unforeseen development and the plastic reusing adventures. Reuse of waste and reused plastic materials in solid blend as a characteristic neighborly improvement material has pulled considering specialists advancing occasions, and unlimited appraisals revealing the direct of cement containing waste and reused plastic materials have been scattered. This paper sums up an extensive survey on the evaluation articles on the utilization of reused plastics in strong dependent on whether they administered concrete containing plastic totals or plastic filaments. Moreover, the morphology of cement containing plastic materials is to clarify the impact of plastic totals and plastic filaments on the properties of cement. The properties of cements containing virgin plastic materials were additionally examined to build up their similitudes and contrasts with concrete containing reused plastics. Solid shape, chamber and segment were casted taking 0% to 40% of plastic as halfway substitution of fine total and pursued for 28days of compressive quality, flexural quality and split adaptability of cement.

Response of Shear Wall in Open Storey Building under Seismic Excitation
Authors:- Shaik Mohammed Imran, Asst. Prof. D.C. Anajaya Reddy

Abstract:- The Open Ground Storey buildings are very commonly found in India due to provision3 for considerably needed parking lot in urban areas. However, seismic performance of this sort of buildings is found to be consistently poor as demonstrated by the past earthquakes. A number of the literatures indicate that use of shear walls may enhance the performance of this type of buildings without obstructing the free movement of vehicles within the parking zone . This study is an effort during this direction to review the performance of Open Ground Storey buildings strengthened with shear walls during a bay or two. additionally thereto , the study considers a special scenarios of Open Ground storey buildings strengthened by applying various schemes of multiplication factors in line with the approach proposed by IS 1893 (2002) for the comparison purpose. Study shows that the shear walls significantly increases the bottom shear capacity of OGS buildings however the comparative cost is slightly on the upper side.

Analysis of Credit Card Fraud Detection in Data Mining using Various Classifier Techniques
Authors:- Research Scholar Sachin Jain, Professor Dr. Rohit Kumar Singhal

Abstract:-The data mining is the technique which can mine useful information from the rough data. The prediction analysis is the technique of data mining which can predict new things from the current data. The classifications techniques are generally applied for the prediction analysis. This research work is based on the prediction of the credit card fraud detection. The various techniques are proposed by the authors for the credit card fraud detection. The technique which is proposed the study in the different paper is based on the conventional neural networks in which system learns from the previous experiences and drive new values.

Analysis of Software Project Cost Estimation using Functional Point
Authors:-Research Scholar Sunil Kumar, Professor Dr. Rohit Kumar Singhal

Abstract:-Effort estimation has been used for planning and monitoring project resources. As software grew in size and complexity, it is very difficult to predict the development cost. There is no single technique, which is best for all situations. A careful comparison of the results of several approaches is necessary to produce realistic estimates. The use of workforce is measured as effort and defined as total time taken by development team members to perform a given task. It is usually expressed in units such as man-day, man -month, and man-year, which is a basis for estimating other values relevant for software projects, like cost or total time required to produce a software product.

Study and Analysis in HEART DISEASE ANALYSIS USING K-Nearest Neighbor Classifier
Authors:- Research Scholar Wasim Akaram, Professor Dr. Rohit Kumar Singhal

Abstract:- Data mining refers to analysis of complex data. The prediction is the process of determining what will happen next. Recently, various techniques have been applied for the prediction analysis. A SVM technique is applied to the prediction analysis. The technique divides data into training and testing stages. The first class of test data is for the most part related to the individuals who have little to no risk of having a heart disease . The second class of test data all have risk-of-heart-disease levels above 50%. This research work proposes to improve this existing method using decision tree classifier. The proposal would improve accuracy and reduce the execution time.

A Review on Design Considerations for a Bidirectional Dc/Dc Converter
Authors:- M.Tech. Scholar Alka Tanwar, Asst. Prof. Mithilesh Gautam

Abstract:- Recently the use of renewable energy resources has been increased to save the environment and remaining fossil fuel and the requirement of storing the energy is also increased. In many applications like electric vehicles the need of interfacing of energy storage with load and source is increased for a reliable and efficient system. Bidirectional dc to dc converter is the main device used to interface the Battery and super capacitor as a storage device to increase the system reliability A conventional buck-boost converter can management the power flow in one direction only but power can flow in both the direction in bidirectional converter. Bidirectional dc-dc converters are the device for the purpose of step-up or step-down the voltage level with the capability of flow power in either forward directions or in backward direction. Bidirectional dc-dc converters work as regulator of power flow of the DC bus voltage in both the direction. In the power generation by wind mills and solar power systems, output fluctuates because of the changing environment condition. the basic knowledge and classification of bidirectional dc to dc converters on the basis of galvanic isolation, the comparison between their voltage conversion ratio and output current ripple along with various topologies researched in recent years are presented in this paper. Finally, zero current and zero voltage soft switching schemes and phase shifted controlling techniques are also highlighted.

Classification of Brain tumour in MRI images using BWT and SVM classifier
Authors:- M.Tech. Scholar Nisha Tomar, Asst.Prof. Ashish Tiwari

Abstract:- The improvement in medical image dispensation is increasing in an incredible manner. The speed of increasing ailment by method of reverence to various types of cancer and other related human exertion pave the way for the increase in biomedical research. as a result giving elsewhere and analyzing these medical descriptions is of high significance for scientific diagnosis. This work focus on the stage effectual categorization of brain tumour descriptions and segmentation of exist illness images employing the planned mixture bright techniques. The challenge as well as objectives lying on design of mark extraction, characteristic collection in addition to image classification and segmentation for medical images are discuss The tentative results of intended method contain been appraise and validate for arrangement in addition to superiority examination on magnetic clatter brain images, based on accuracy, sensitivity, specificity, and dice comparison directory coefficient. The experimental marks achieved 91.73% accuracy, 91.76% specificity, and 98.452% sensitivity, demonstrating the efficiency of the proposed method for identify normal and nonstandard tissues from intelligence MR images.

Dynamic Brain Tumor Image Detection Using Median Filter and Genetic Algorithm
Authors:- M.Tech. Scholar Shivi Joshi, Prof. Shalini Sahay

Abstract:- Processing of MRI image for detection of disease in human body was done manually by heath specialist. But most of machine develops automation for the same, so researchers are working in this field to improve the accuracy of detection. This paper has proposed the brain tumor detection algorithm in MRI images. Due to the dynamic nature of tumor in any part of brain sculpture genetic algorithm was used for tumor detection. Proposed tumor detection model use Teacher Learning Based Optimization genetic algorithm which classify image pixel into two regions first was tumor and other was non tumor portion of brain. So no need of training for the detection of tumor from image is required. Use of median filter increase detection accuracy with gray scal image input in fitness function. Real image brain tumor dataset was taken for testing of algorithm. Result shows that proposed model has improve the precision, recall, f-measure evaluation parameters as compare to previous approaches.

Gesture Recognition for User Interaction
Authors:- Anshul Joshi, Harsh Gupta, Srija Nagabhyru

Abstract:- With the massive influx and advancement of technologies there is a scope for us to interact with our systems in the best possible way. One such technology would be Gesture based Human Computer Interaction. So our system makes use of HCI which would help us interact without touching the screen. It is a well known fact that two dimensional user interfaces are everywhere, but with the increasing popularity of Extended Reality (XR) we require a better, more sophisticated three dimensional user interface.

Prediction of Earthquake Magnitude Based on the Clusters in Sulawesi Island, Indonesia
Authors:-Fachrizal Fajrin Aksana*, Andi Azizaha, Enggar Dwi Prihastomob

Abstract:- In this paper, we present an earthquake magnitude prediction model based on similar earthquake locations. To classify the earthquakes that occurred in Sulawesi Island, we use the K-Means clustering method to group the earthquakes based on the longitude and latitude of the earthquake. Support Vector Regression and Random Forest Regressor are proposed model to predict the magnitude in each cluster based on the longitude, latitude, and depth of the earthquakes. The data of past earthquakes are obtained from the USA Geological Survey and Meteorology, Climatology and Geophysical Agency of the Republic of Indonesia (BMKG). The optimal number of clusters is determined by the elbow method is 3. The prediction results show that the most accurate prediction model is Random Forest Regressor when the clustering approach is used.

Emotion Recognition Using Face Detection
Authors:- Amit Badave, Shivani Oswal, Siddharth Atre, Prof. Shilpa Khedkar, Vivek Alhat, Prof. Bhagyashri More

Abstract:- Human-machine interaction is one of the most important aspects of computing. Automatic emotion recognition has been an active topic for research since the last decade. Analyzing unique patterns of human emotions will help machines to understand humans better. Face detection and emotion recognition can be used in several application areas. It can be used in real-time monitoring, security and in gaming applications. In recent years, deep learning has provided a whole fresh approach to understanding and process real-time data. It provides effective methods and algorithms to process images, audio, video, and metadata. In this paper, we propose a system that aims to classify human emotions in different categories such as happy, sad, neutral, disgust, ange and fear. It bases our paper upon the idea of using different techniques of machine learning such as neural networks, haar cascade, principal component analysis (PCA), and facial features extraction to classify human emotions.

Survey on Secure Transactions Using Facial Identification
Authors:- Assistant Professor A.Porselvi, M.E, Anusha S, Meena P, Nishitha K

Abstract:- The rise of technology brings into force many varieties of tools that draw a bead on a lot of client pleasure. There’s associate degree pressing would like for up security in banking region. During this survey, we tend to discuss banking transactions exploitation facial identification. This subject has relevance to facial idea exploitation bank dealing. The processed info passes through the information of banks and payment systems. If facial identity is matched then dealing can be finished. The event of such a system would serve to safeguard customers and money establishments alike from intruders and identity thieves. The combined biometric options approach is to serve the aim each the identification and authentication.

Use Cases of Blockchain with Big Data
Authors:- Ms. Pratima Keni

Abstract:- Big data means data which is stored in massive amount of storage. Big data is high- volume, high-velocity and high-variety of data which is cost effective and help us to take any decision. Block chain is nothing but data which is stored in block and connect that data with each other through the block. Most recent transaction data which is added to block. This is also known as peer in chain. Blockchain which is the trending technology in today’s world. In this research paper we are dealing with what are the advantages when big data and blockchain are two big technologies are come into the picture. Basic Introduction of this paper which is explains in Section I. Section II talks about what is big data. Section III tells about What are the issues of Big data analytics. Block chain basic information which is explain in Section IV. Use Cases of Big data with Blockchain which is explain in section V.

Haar Cascades On Face Mask Detection
Authors:- Chinmay Patil

Abstract:-Coronavirus disease 2019 has affected the world seriously. One major protection method for people is to wear masks in public areas. Furthermore, many public service providers require customers to use the service only if they wear masks correctly. However, there are only a few research studies about face mask detection based on image analysis. Object detection is an important feature of computer science. The benefits of object detection are however not limited to someone with a Doctor of Informatics. Instead, object detection is growing deeper and deeper into the common parts of the information society, lending a helping hand wherever needed. This paper will address one such possibility , namely the help of a Haar-cascade classifier.

Analysis of Major Cenrifugal Pumps Failures (With Application to Irrigation Pumps in Sudan)
Authors:- Mohamed Yagoub Adam, Hassan Khalifa Osman, M. I. Shukri

Abstract:-Centrifugal pumps are one of the most widely used pumps in the world, with a wide range of applications, from the petroleum industry to the transportation of irrigation water. Despite the extensive use of pumps, few component failures cause severe degradation of pump performance and increase downtime, which adversely affect production. Therefore, in order to minimize downtime and improve pump reliability and availability, these pumps must be carefully controlled, diagnosed, maintained or replaced before a catastrophic pump failure occurs. This study investigated the major faults found in centrifugal pumps, especially in Sudan’s irrigation pumps. In this study, we analyzed the problems faced by pump failures causing yield loss at the level of all privatization and parastatal pump schemes operating under government license, government pump stations in the four national government owner agricultural schemes (New Halfa, Rahad, Suki and Gezira & Managil), by using statistical methods. Results show that, at the technical level of the system, a probabilistic method based on the evolution of the pump state enables us to carry out preventive interventions; when the component reaches the degradation zone, it leads to an increase in periodic system intervention. For equipment, whose system schedule set in advance by the manufacturer cannot effectively meet the maintenance requirements; the mathematical model based on failure linearization can correct or even optimize the maintenance plan. Through our own investigation, we have concluded that it is necessary to change the structure of the maintenance cycle of the irrigation pumps under consideration. In this study, the feasibility of preventive maintenance based on reliability and conditional maintenance was verified. The results obtained are contributions to meet the reliability goals pursued by irrigation pumps.

Study of On-Line Monitoring Technology on the Transmission Line
Authors:- M.Tech.Scholar Manmay Banerjee, Asst. Prof.Sachin Kumar

Abstract:- This paper presents a ground-breaking thought of overhead T/L web based checking. Mainly premise of this paper is to secure the tons of exploration con-ducted by generation and distribution engineers & another serious T/L secure activity observing framework is working with effectively. Moreover, we are trying to utilize fake impartial organization for analysis models, to demonstrate the plausibility and adequacy for the serious T/L secure activity framework.

Blind – Sight: Object Detection with Voice Feedback
Authors:- A. Annapoorani, Nerosha Senthil Kumar, Dr. V. Vidhya

Abstract:- Computer vision deals with how computers can be made to gain high-level understanding from digital images or videos. It seeks to automate tasks that the human visual system can do. Humans glance at an image and instantly know what objects are in the image, where they are, and how they interact. An estimate of 285 million people is visually impaired worldwide, stated by WHO. The proposed Blind Sight-Object Detection with Voice Feedback is a computer vision-based application that leverages state of the art object detection techniques. These are employed to detect objects in the vicinity. You Only Look Once (YOLO): Unified, Real-Time Object Detection a new approach to object detection is deployed in this proposed work. YOLO has 75 Convolutional Neural Network (CNN). Image classification techniques are used to identify the features of the image and categorize them into their appropriate class. The COCO dataset used in this project consists of around 123,287 hand labelled images classified into 80 categories. This wide set of data is used to describe spatial relationships between objects and their location in the environment. In addition, an Indian currency recognition module is developed to identify the denominations. The text description of the recognised object will be sent to the Google Text-to-Speech API using the gTTS package. Voice feedback on the 1st frame of each second will be scheduled as an output to help the visually impaired hear what they cannot see.

Convolutional Neural Network Based Facial Expression Recognition
Authors:- M.Tech. Scholar Ramchandra Solanki, Asst. Prof. Vijay Yadav

Abstract:- We see the importance of facial expression recognition in different applications. To do such task the traditional feature extraction is used which involves in complex processing. Previously various deep neural networks have been used for this task; as well it can be replaced by some improved methods. So, in this paper we have proposed a system for face recognition which uses the convolutional neural network (CNN) along with the detection of the edges of image. The proposed workflows in two steps in the first the normalization of the facial expression in the image is done, secondly the convolution is done for the extraction of the edges in images. After this the maximum pooling method is used for the dimensionality reduction. At the end the classification of the facial expression is done and the Softmax classifier is used for this classification and the face expression is recognized. The facial expression recognition experiment is done on the Fer-2013 dataset. The results obtained from the proposed approach gets a face recognition rate up to 92.45% for the used dataset. The given method works with lesser number of iterations for the recognition and the system provides approx 1.5 times fast execution as compared to the SDSRN algorithm..

Review of Twitter Data Sentiment Analysis
Authors:- M. Tech. Scholar Nikita Akhand, Asst. Prof. Ms. Shivani Gupata

Abstract:- Everyday a huge amount of data has been
produced over various social sites. A huge number of users share and tweet regular updates on twitter. Tweet is a short way of expressing thoughts on any topic. So, the sentiment analysis of this data is must to keep track of the tweets. Sentiment analysis is the way to carry out text mining. To analyze this data produced over the twitter there are many methods that are used. Various experiments have been done to perform sentiment analysis of this data produced over twitter. There are different levels on which the sentiment analysis can be performed. So, in this paper we are providing a survey on the sentiment analysis of twitter data which uses the supervised and unsupervised learning algorithms.

A Review: Improvement of Link Permanency
Authors:- M. Tech. Scholar Bharti Chouhan, HOD Avinash Pal

Abstract:- Vehicular Ad hoc Networks (VANET) are highly mobile wireless ad hoc networks that provides communication between vehicles. As a promising technology it plays an important role in public safety communications and commercial applications. Due to the rapidly changing of topology and high-speed mobility of vehicle, routing of data in vanet becomes a challenging task. One of the critical issues of VANETs are frequent path disruptions caused by high-speed mobility of vehicle that leads to broken links which results in low throughput and high overhead. This paper argues with how to maintain the reliable link stability between the vehicles without any packet loss using two separate algorithms besides position, direction, velocity and digital mapping of roads. In this paper we propose a reliable position-based routing approach called Reliable Directional Greedy routing (RDGR) which is used to obtain the position, speed and direction of its neighboring nodes through GPS and as well as the well-known Ad-Hoc On-Demand Distance Vector (AODV) which includes vehicles position, direction, velocity with link stability. This approach incorporates potential score-based strategy, which calculates link stability between neighbor nodes for reliable data transfer in this paper we use both RDGR and AODV approach in order to provide reliable link stability and efficient packet delivery ratio even in high-speed mobility and changing of topology.

News Classification System Based on Area
Authors:- Prof. Krishnanjali Shinde, Prachi Prajapati, Sakshi Tagalpallewar, Ruchita Bacchuwar

Abstract:- – In 21st century the internet is filled with loads of news articles, there is a pressing need to classify news according to the requirements of an individual. People are generally more interested what is going on, in their immediate surroundings. News has a vital role in the society. Most people read news every day to keep up with the latest information and trends. The information could be anything, from technology, disaster, politics, even the affair of the celebrities. After they absorb the information and understand it, it will be used by the people as a reference to their ideology and decision making. With the help of technology advancements, news disseminates relatively quick across the globe. Using the internet, people can send information from another side of the world in under a second. Because of this, almost any kind of information such as knowledge, idea, entertainment, and news from the people can easily spread to the community. With the development of the web, and ton of internet sites that provide similar information and data. So, users often discover it hard todecide that of those websites will offer thespecified information inside the foremost valuable and effective way.

Behaviour of Combined Piled Raft Foundation in Clayey Soil
Authors:- S. Lakshmi Prabha

Abstract:- In situations where a raft foundation alone does not satisfy the design requirements, it may be possible to enhance the performance of the raft by addition of piles, the use of a limited number of piles, strategically located, may improve both the ultimate load capacity and the settlement and the differential settlement performance of raft. This paper discusses the philosophy of using piles as settlement reducers and considering interaction effects. In this method the raft is considered as a plate supported by a group of piles. To verify the reliability of the proposed method, a 5 storied RCC structure is analysed in SAP 2000, considering the guidelines given in chapter 56 of ICE manual of geotechnical engineering (volumeII) and Theoretical manual for pile foundation by US Army corps of Engineers (ERDC/ITL TR-00-5).

Optimize Piston Durability by Coating Layer of Tungsten Carbide
Authors:- Student of M.Tech. Nitesh Kumar, Gouraw Beohar(HOD), Assistant Professor Anshul Jain

Abstract:- This coating enhance piston durability on layer of 0.20 to 0.25µm which explore that after all testing on Coated piston minimum coating thickness which has been coated will be 0.20 µm whereas maximum thickness of coating which has been coated on piston will be 0.25 µm . There are various result which shows that these layer are efficient during long run .These layer also having less absorption capacity of heat results in maximum heat energy transform into work due to this exhaust will be less. The most expensive way to reduce fuel consumption is to develop more efficient fire engines. Today, about 40-45% of gasoline is converted into useful energy, while the remaining thermal energy is converted into heat. One of the possible solutions of decreasing heat losses from the engine is by insulation of piston coated with Tungsten carbide; all possible measures of improvements are in the scope of interest. Therefore this master thesis was carried out. The theoretical study was focused on about appropriate materials, industrial applications and the state of the art research in the area of coating. Sample prototypes and material samples were coated using a thickness of 0.5 µm to 0.25 µm and coated with Tungsten Carbide powder coating. Heat flux, Shear stress, Elastic strain, and total deformation are measured for each coating. The integrated pistons have been tested in a single cylinder engine, to ensure the strength of the thermal barrier. Due to the negative impact on piston the combustion process and the overall efficiency of piston, were obtain .A trend showing a decrease in heat loss with an increase in the coating of the layer was observed. During both load and thermal cycling tests of different thickness of Tungsten Carbide powder coating such as 0.05 µm, 0.1 µm, 0.15 µm, 0.20 µm, 0.25 µm, and 0.3µm. The temperature and stress field of piston are resolved using ANSYS (Version 18) software. The optimum result obtained to acquire minimum heat loss during combustion and obtained no deformation during high heat in general 150 cc Aluminum alloy piston, the best result obtained on coating piston with 0.25 µm with Tungsten Carbide powder coating.

Acoustic Steam Leak Detection System
Authors:- R. Saravanan M.E.,Ap/Eee, R. Balambika , R.Chelvadharani , A. Divyadharshin

Abstract:- The boiler tube failure is occurring frequently in thermal power plants. Boiler tube leakage is the significant reason for blackout of units and age misfortune in warm influence plants. Location of boiler tube leakage is a significant factor for power plant working as roughly 60% of boiler outages are because of tube leaks. Power plant engineers must cautious about boiler tube puncher so that further damages to pressure parts such as water wall tubes and headers, super heater tubes, re-heater tubes, and furnace refractory may be avoided. Boiler tube leaks have even been known to prompt to bending damage and deformation of the entire boiler. The costs of repair, substitution, and maintenance due to secondary damage can be maximum. There are several solutions are available to identify the boiler tube leakages such that analyzing the make-up water, survey of tube thickness and fitting sensors inside the boiler. The compact solution is fitting sensors inside the boiler. Here, we are using piezoelectric sensor to detect the tube leakages. There are two types of sensors available which are airborne sensor and structure borne sensor. Airborne contains a genuine microphone, which is totally insensitive to vibration. Structure borne is Piezo- electric based sensors can measure sound generated by a leak in the boiler structure by either acoustic frequencies or ultrasonic frequencies. The airborne sensor is used in acoustic steam leak detection system. The Acoustic Steam Leak Detection (ASLD) system works on the principle of detecting the sound waves emanating from the steam leak, processing the same and then indicating the quantum of steam leak and the location. When a leak is detected by a change in the sound patterns, alarms are activated and the fault is localized. By using these methods the leak is detected and the many secondary damages were avoided.

Design and Deflection Analysis of Deck Slab
Authors:- Kapil Mohaliya, Sourabh Dashore (HOD)

Abstract:- Steel-Free Deck Composite Bridges system has been investigated during the past two decades. The concept is totally new and innovative. The new structural system enables the construction of a concrete deck that is totally devoid of all internal steel reinforcement. Traditionally, reinforced concrete bridge decks are designed to sustain loads in flexure. The new innovative bridges with steel-free decks develop internal compressive forces “internal arching” which leads to failure by punching shear at substantially higher loads than the flexural design load. Five composite bridges have been recently constructed in Canada adopting this new concept.

CFD Analysis of Tubular Heat Exchanger with Ribbed Twisted Tapes for Heat Exchanger Enhancement
Authors:- M.Tech. Scholar Vinita Kapse, Prof. Sharvan Vishwakarma

Abstract:- A heat exchanger is really a system that transfers heat between two or more fluids. The fluids can also be single-phase or two-phase, so they can be isolated or in close contact, depending on the form of exchanger. In this study, two twisted ribbons are inserted into another heat exchanger tube and heat transfer is studied. The aim of both the ongoing project is to figure out how fast heat transfers in a circular tube with entangled ribbons. The Reynolds (Re) number as well as the geometry of tube is the parameters of concern. For the first case, diameter of tube is taken 50.8 mm and length 1000 mm. For the second case the diameter is increased and length is kept constant, diameter is constant and length is increased for third case, and for fourth cases both length and diameter is increased. It is found that with the increase in both length and diameter of tubes, the heat transfer is increasing, pressure drop is decreasing by 56%, Nusselt number (Nu) is decreasing by 72% and the thermal enhancement factor is increasing by 12%. It can be concluded that the increase in diameter results in decrease in heat transfer while increase in length is preferable for increase in heat transfer rate. Hence, among the selected four designs, the fourth case with diameter=80mm, and length=3000 mm is the most preferable one.

An Iot Based Modern Street Light System for Energy Efficient and Energy Auditing with Fault Identification System
Authors:- Asst. Prof. R. Rubanraja, M. Kanimozhi, M. Mahalakshmi, K. Mounika, V. Suruthipriya

Abstract:- Today’s modern world people preferred to live the sophisticated life with all facilities. The science and technological developments are growing rapidly to meet the above requirements. With advanced innovations, Internet of Things (IoT) plays a major role to automate different areas like health monitoring, traffic management, agricultural irrigation, street lights, class rooms, etc., Currently we use manual system to operate the street lights, this leads to the enormous energy waste in all over the world and it should be changed. In this survey we studied about, how IoT is used to develop the street lights in the smart way for our modern era. It is an important fact to solvethe energy crises and also to develop the street lights to the entire world. In addition, with the study on Smart Street lighting systems we analysed and described different sensors and components which are used in Iot environment. All the components of this survey are frequently used and very modest but effective to make the unswerving intelligence systems.

A Model for Sentimental Analysis of Twitter Data in Hindi Polarity: A Study
Authors:- Suraj Prasad Keshri1, Neelam Sahu2

Abstract:- This research explores real-time feelings of analysis. Twitter / WhatsApp posts are based in Hindi, with a sense of classification on a three-way scale, negative, positive and natural. The efficiency of various methods such as speech (POS) tagging and part of the stop word extract are compared and WordNet is proposed to improve the Hindi Sentimental Word. The current work of analysis on sentiment has been done in mining. There are resource-rich languages such as English; while data in Indian languages is still relatively low web content in languages like Hindi has grown rapidly over the past few years. In addition, as the length of social media increases, WhatsApp has become a hotbed of user content on platforms such as Twitter and Facebook SA of tweets made in English. There is not an analysis of similar data in Hindi. In this paper, we perform real-time SA on a live stream of Hindi tweets. Twitter social media application is a popular site Forum to share opinions of millions of people there are users on a variety of topics. The Analysis and opinion mining websites are rich sources of data for sentiment. A Twitter user can often use hash tags, then the same tag is used to group similar posts. A group of people can become a hash tag trend Attract a special discussion to as many people as possible to participate in it.

Privacy-Preserving Zero Knowledge Scheme for Attribute-based Matchmaking
Authors:- Solomon Sarpong

Abstract:- Making friends with common attributes is a characteristic of some persons. This characteristic is also extended to matchmaking on social networks. In some of the existing matchmaking protocols, the users are match-paired without considering the number of attributes they have in common. Furthermore, the bane of the existing proposed matchmaking protocols has been how to preserve the users’ privacy and this has been considered as the key security issue for such applications. In order to prevent malicious users from gaining extra information, the attributes in this protocol will be certified. Hence, certification authority ensures that, a user actually possesses the input attributes and binds them to him/her. With the use of certified sets and zero knowledge proofs, users can adequately find a matching-pair whilst keeping his/her input set private. Furthermore, in this proposed protocol, a person can find a best match among potential candidates by finding the one who has the maximum number of common attributes. At the end of the protocol, the match-pair can exchange their attributes without any other person knowing the number or the type of attributes they have in common.

Structural Investigation of Agricultural UAV
Authors:- E.Akshaya Chandar, Adesh Phalphale, Sourav Ghosh, Sanket Desai

Abstract:- UAV Technology has improved exponentially in the last few cycles, and we can discuss its importance as new resolutions to all challenging queries that include managed services on a unique land that a computer can make floating above it. It covers UAV that produces agricultural projects like spraying, an examination of products for vast hectare fields. Structural analysis is the purpose of the consequences of pressures on concrete buildings and their elements. The structural analysis applies applied mechanics, materials science, and applied mathematics to measure a structure’s deformations, internal forces, stresses, support reactions, accelerations, and stability. The analysis results verify a structure’s fitness for use, often precluding physical tests. This report presents the results of structural analysis of the Agricultural Unmanned Aerial Vehicle in compliance with the requirements of DGCA. The analysis includes the Strength of Materials approach to determine loads (Shear Force and Bending Moments) which is utilized for further analysis using the Finite Element Analysis (FEA) approach. Commercial FEA software ANSYS is used for this purpose. The static structural analyses of the UAV are performed under different load conditions. The consequences of these researches show that the planned construction is safe within the flight envelope. This paper lays the structural analysis framework, which could as a source for additional temporary separation. The products can be increased additional to effective reports like Crash Test, sloshing examination of Fuel tanks, Etc. to mimic real-time events. This paper is required to showcase the structure’s authenticity (hypothetical load circumstances compelling) for certification determinations and vibration endorsement from DGCA.

Enhancing Air Pollution Predicton Using Artificial Neural Network with XG Boost Algorithm
Authors:- Assistant Professor Christina Rini R, Aishwarya N, Meenakshi G, Saranya M

Abstract:- Air pollution has become a major public health concern in recent years. Despite substantial improvements in overall air quality in recent years, India remains the third most polluted country according to the latest edition of the World Air Quality Report [1]. The release of gases into the air that are harmful to human health and the environment is referred to as air pollution. Lung cancer, cardiovascular disease, respiratory disease, and metabolic disease have all been linked to high concentrations of fine particulate matter with a diameter less than 2.5 m (PM2.5). Experimental research with various machine learning algorithms has yielded promising results in the field of air pollution prediction. Predicting air quality by determining concentrations will assist different departments, including governments, in alerting people who are at high risk, reducing complications. An improved air pollution prediction approach based on the XGBOOST and ARTIFICIAL NEURAL NETWORK algorithms is used to forecast air quality. Our goal is to look into a machine learning-based approach for air quality forecasting using the AQI index and get the best results possible. In addition, we compare the performance of different ML algorithms from the dataset with the use of a GUI to predict air quality bycharacteristics.

Localization of Partial Discharge in a Transformer Winding Using Ladder Network – A Review
Authors:- Tejal Dixit, Vivek Anand

Abstract:- The Detection of the location of partial discharge in the windings of power transformers has always been considered a challenging task because of the convoluted structure of the winding. There are several methods proposed for the localization of partial discharge in the transformer winding. In this paper, we have concluded a detailed study on detecting the partial discharge using a ladder network to compute the response of a partial discharge in a winding of a transformer. The algorithm for two separate winding sections that are along and across the winding is computed. A response is calculated at the winding neutral terminal.

A Study on Proximate Analysis of Chicken Intestine and Chicken Skin
Authors:- Asst. Prof. Mohammad Saydul Islam Sarkar, Student Md. Saiful Islam

Abstract:- In the present study, percentage of protein, fat, moisture, ash and carbohydrates of poultry by product was studied. For this analysis poultry by product were collected from dining and restaurant. For chicken intestine the intestine percentage of protein, fat, moisture, ash and carbohydrate was 68.28%, 8.64%, 7.37%, 4.33% and 11.40% respectively. For chicken skin the percentage of protein, fat, moisture, ash and carbohydrate was 22.16%, 47.64%, 9.2%, 11.14% and 10.86% respectively. Percentage of protein was more in intestine than skin. Percentage of fat content was more in skin than intestine. Percentage of moisture content was similar between intestine and skin. Percentage of ash content was more in skin than intestine. Percentage of carbohydrate content was similar between intestine and skin.

COVID – 19 Detection Using Medical Imaging and Health Parameters
Authors:- Aditya Raute, Alisha Punwani, Siddhesh Hadkar, Heramb Kulkarni, Asst. Prof. Lifna C.S.

Abstract:- This research paper focuses on the use of advanced technology in confluence with readily available machinery to create a testing environment for COVID-19 that is more efficient, accurate, and has a higher reachability. This paper aims to develop a unique algorithm for detection of COVID-19 based on chest X-Rays, in combination with the patient’s medical information including symptoms, age, bloodwork, and possible contact with someone infected with the virus. This proposal will especially be instrumental in locations with inadequate medical staff, and can drastically reduce the diagnosis time that is otherwise required.

Excessive Retardation in Concrete
Authors:- P.Senthamil Selvan

Abstract:-Setting time of concrete has vital role in the construction process. Retarders are used where early setting of concrete is not required and when higher retention period is needed to place the concrete. Chemical composition of retarder is formulated to stop the hydration temporarily to delay the initial set of concrete. Once the effect of retarder wears off initial set will begin and hardening will develop. Use of concrete as a construction material depends upon the fact that it is plastic in fresh state and gets hardens subsequently with considerable strength. This change in physical properties is due the hydration process which is irreversible. This reaction is gradual, first stiffening of concrete and then development of strength which continues for a long time. The rate of reaction primarily depends on the cement property, concrete mix, and use of mineral and chemical admixtures. It is observed from study that delayed setting of concrete has impacted only early compressive strength of concrete but later strength at 28days remains unaffected by delayed setting of concrete.

Factors Affecting Water Absorption in Hardened Concrete
Authors:- P. Senthamil Selvan

Abstract:Concrete can absorb moisture because of its porous nature. When ambient relative humidity is high, concrete will absorb moisture from the air. When relative humidity is low, water will evaporate from the concrete in to the ambient environment. This absorption of moisture by concrete causes dampness in roof slabs and when concrete is more porous dampness will be higher. Porosity in concrete especially in roof slabs is caused by following several factors; Poor mix proportion, Poor compaction and laying, Curing regime, Poor construction practices.And dampness in roof slab which is primarily absorption of moisture by concrete is caused by following factors; Porosity of concrete, Relative Humidity, Surface area of element, Exposure period of wetting and drying.

A Review Article of thermal Analysis of Shell and Tube Heat Exchanger Using Artificial Neural Network
Authors:- Dhananjay Kumar, Asst. Prof. Deepak Solanki

Abstract:This review explains the effective utilization of artificial neural network (ANN) modeling in various heat transfer applications like steady and dynamic thermal problems, heat exchangers, gas-solid fluidized beds etc. It is not always feasible to deal with many critical problems in thermal engineering by the use of traditional analysis such as fundamental equations, conventional correlations or developing unique designs from experimental data through trial and error. Implementation of ANN tool with different techniques and structures shows that there is good agreement in the results obtained by ANN and experimental data. The purpose of the present review is to point out the recent advances in ANN and its successful implementation in dealing with a variety of important heat transfer problems. Based on the literature it is observed that the feed-forward network with back propagation technique implemented successfully in many heat transfer studies. The performance of the network trained were tested using regression analysis and the performance parameters such as root mean square error, mean absolute error, coefficient of determination, absolute standard deviation etc. The authors own experimental investigation of heat transfer studies of tube immersed in gas-solid fluidized bed using ANN is included for strengthening the said review. The results achieved by performance parameters shows that ANN can be used reliably in many heat transfer applications successfully.

Security in ad-hoc network using encrypted data transmission and Steganography
Authors:- Prof. Ravindra Ghugare, Ankita Patil, Ajay Jha, Dhiraj Kuslekar

Abstract- Currently, there has been an increasing trend in outsourcing data to remote cloud, where the people outsource their data at Cloud Service Provider(CSP) who offers huge storage space with low cost. Thus users can reduce the maintenance and burden of local data storage. Meanwhile, once data goes into cloud they lose control of their data, which inevitably brings new security risks toward integrity and confidentiality. Hence, efficient and effective methods are needed to ensure the data integrity and confidentiality of outsource data on untrusted cloud servers. Thepreviously proposed protocols fail to provide strong security assurance to the users. In this paper, we propose an efficient and secure protocol to address these issues. Our method allows third party auditor to periodically verify the data integrity stored at CSP without retrieving original data. To compare with existing schemes, our scheme is more secure and efficient.

Design; Construction and Evaluation of Engine Operated Rotary Tiller
Authors:- Tamiru Dibaba, Rabira Wirtu, Wasihun Mitiku, Teklewold Dabi

Abstract- Currently, as Ethiopia is importing most of the agricultural mechanization technologies, including power tillers, there are significant shortages for using powered farm machineries in the country. Thus, this activity was initiated to design and construct an engine operated rotary power tiller locally and test performances. Accordingly, the design of this machine was based on the total specific energy requirements which carried out for an L-shape rotary tiller blade through using mathematical model. This rotary tiller was operated by 10 hp motor engine out of this 2.25 hp of the power was used to dig the soil. The performance of the machine was evaluated in terms of theoretical field capacity, actual field capacity and field efficiency on clay soil. The results indicated that the theoretical field capacity, the actual field capacity and the field efficiency was 0.146 ha/hr., 0.134 ha/hr. and 91.78 % respectively at 1.11 g/cm3 soil bulk density and 30.3 % soil moisture content. The soil mean clod diameter after pass through by rotary was 0.127 mm. But, the designed rotary tiller requires some improvement on operation system as writing on recommendation parts before demonstration.

Robot for Defense & Security with IOT
Authors:- P.G. Scholar Manjula M, Asst. Prof. Jagadeesh B N, HOD. Dr. Narasimhamurthy M S

Abstract- This Project is an IR & camera-based security system or robot for protected areas & borders, which senses the Intruders, trespassers and transfer video to other end. The robot to be built is going to have an IR Sensor which senses any intruders / trespassers and will activate the alarm as well as switch on the guns. The robot will also be capable of shooting the intruder when he cross the border, the bullet shall also be equipped with a GPS facility so that incase if the intruder tries to escapes he can be tracked with devices or smart phone. The robot will also activate the Camera, which will start capturing the live video and transmit the same to the receiver end, the smart phone. It will trigger the alarm and the data will be transferred to the mobile device.

Advance Glass House Monitoring and Controlling Using Deep Learning
Authors:- Raju. U, Siva. B, Vishal Jayaruban. S, Asst. Professor Ms. S. S. Sugania

Abstract- In current era, Faster Region-Convolution Neural Networks (Faster R-CNN) are desperately improved localization, identification and detection of objects. Recent days, Big data is evolved which leads huge data generation through modern tools like surveillance video cameras. In this project, it focused on tomato growing stages and plant health condition in the agricultural field, monitor the temperature, soil moisture, light intensity and sends the notification message to the user. Agriculture is one of major living source in India. By using impro ved and customized Faster R-CNN model (improved-detect), this project had trained datasets of Tomato and Plant. In this project, Tomato plant is mainly used for model training and testing. This project have experimented on plant image data set and tomato growing stages. Expe rimental results are compared with state of the architectures like Mobile Net, Dark Net-19, ResNet-101 and proposed model out performs in location. O btains best results in computation and accuracy. In the below results sections, we have presented the results with suitable models.

Reduce waste by using lean Manufacturing: Case study in Yarmouk complex
Authors:- Mohammed Sirelkhatim Abdelwahab, Prof. Hassan Khalifa Osman

Abstract- The aim of this paper is to study the gap of applying lean philosophy in production lines in one of Yarmouk industrial complex factories(A22) to achieve some goals summarized in changing production management from traditional manufacturing concepts to lean manufacturing concepts. Selection one of products mix in factory A22 to apply lean principles. The methodology of this research is to investigate the effect of batch size, inventory between processes and time spend due to transportation in total throughput and mean life time of the product.

Secure Data Search in Cloud Services Based on Encryption Scheme
Authors:- M. Tech. Scholar Shraddha Verma, Asst. Prof. Dr. Neha Singh

Abstract- In recent days, Cloud storage has become good entrant for organizations that suffer from resource limitation. Cloud computing is a procedure that surveys internet founded computing. The cloud computing method is used to lessen data organisation cost or time. In addition, cloud computing is used to store data that can be retrieved in remote areas. The most challenging task in the cloud is to ensure availability, integrity, and secure file transfer Searchable symmetric encryption (SSE) has been extensively explored in cloud storage, enabling cloud services directly .Search for encrypted data. Most SSE solutions are only suitable for honest but curious cloud services and will not differ. Because storage outsourcing is not trusted, this assumption is not always true in practice. Data protection or file protection in the cloud environment is one of the biggest problems in the cloud environment. Data protection involves many issues, such as wise management, integrity, claims, accessibility, etc. Data confidentiality means that only authorized users can access the data. The accuracy of the data means that if the information is accessible to a remote system or local system it should not be altered. Verification is an effective way to authenticate users who are trying to access information. The availability of data indicates the availability of data if necessary. Confidentiality is usually through encryption technology. The confidentiality of data and keywords is the most important privacy requirements in SSE. It ensures that users’ plaintext data and keywords cannot be revealed by any unauthorized parties, and an adversary cannot learn any useful information about files and keywords through the proof index and update tokens used in GSSE. A verifiable SSE scheme should be able to verify the freshness and integrity of the search results for users.

Performance Analysis of Routing Protocols for Security Attacks
Authors:- M. Tech. Scholar Pooja Verma, Asst. Prof. Dr. Priyanka Shivhare

Abstract- The next generation communication network has been widely popular as an ad hoc network and is roughly divided into mobile nodes based on mobile ad hoc networks (MANET) and vehicle nodes based on the vehicle’s ad hoc network (VANET). VANET aims to maintain traffic congestion by keeping in touch with nearby vehicles. Every car in the ad-hoc network works like a smart phone, which is a sign of high performance and building an active network.The self-organizing network is a decentralized dynamic network, as vehicles are constantly moving, efficient and secure communication requirements are required. These networks are more vulnerable to various attacks, such as hot hole attacks, denial of service attacks. This article is a new attempt to investigate the security features of the VANET routing protocol and the applicability of the AODV protocol to detect and manage specific types of network attacks called “black hole attacks Sybil attack and DDoS attack.A new algorithm is proposed to improve the security mechanism of the AODV protocol, and a mechanism is introduced to detect attack and prevent the network from being attacked by the source node this simulation set up performed on matlab simulation.

Artificial Intelligence in Healthcare
Authors:- Pooja Mahanth Bhagat

Abstract- Artificial intelligence (AI) is outlined as a field of science and engineering involved concerning the computational comprehension of what’s ordinarily referred to as intelligent behavior, and with the creation of artifacts that exhibit such behavior. It’s the subfield of engineering. AI is turning into a renowned field in engineering because it has increased the human life in several areas. AI has recently surpassed human performance in many domains, and there’s nice hope that in care. Artificial intelligence might leave the better interference, detection, diagnosis and treatment of unwellness. Major unwellness areas that use AI tool include cancer, neurology, medical specialty and polygenic disorder. Review contains this standing of AI applications in care. AI can even be accustomed mechanically spot issues and threats to patient safety, like patterns of sub- optimum care or outbreaks of hospital-acquired malady with high accuracy and speed. Some current researches of AI applications in care that offer a read of a future where supplying is a lot of unified, human experiences. This review will explore however AI and machine learning will save lives by serving to individual patients.

Improving Vegetable Disease Detection using Modified K-Means Clustering Algorithm
Authors:- Asst. Prof. C. Santhosh Kumar, J. Jenifer, G.Vidhya, Asst.Prof. R. Vijayabhasker

Abstract- India is the cultivating country and rich in producing agricultural products. So, we have to classify and exchange our agricultural products. Manual arranging is tedious so we use automatic grading system. It requires less time for grading of the agricultural products. Image processing technique is helpful in examination and evaluating the products. In this paper we proposed a vegetable disease detection system for recognizing diseased vegetables. Here we utilize the Image processing system for reviewing the vegetables. Vegetables are recognized dependent on their features. The features are color, shape, size,texture. We extract these features utilizing algorithms to distinguish the vegetables. We develop a recognition system for 2D input images. The main aim of this work is detecting infected vegetable based on their features with K-means clustering algorithm. Algorithm is classified into three steps namely enhancement, segmentation and classification. In this Vegetable samples are collected as images from high resolution camera and the data acquisition is carried out for database preparation. The image segmentation process is based on pixel of the image and it is applied to get the segmented and infected vegetables using K- Means Clustering algorithm.

Comparison of Different Hybrid Approaches Used for Sentiment Analysis: Survey
Authors:- Research Scholar Mansi Chauhan, Research Scholar Devangi Paneri

Abstract- In Today’s Technological Life Social media quiets a specious amount of Information. Social media has become a tremendous source of acquiring Users Opinions. It also helps to analyze how people, particularly consumers, feel about a particular topic, product or Idea. Among such opinions plays an important role in analyzing different business aspects. Sentiment analysis therefore becomes an effective way of Understanding public Opinions. Business Organizations can predict best Decision with Using Sentiment analysis. A lot of Research work has been done on Sentiment analysis in order to classify the opinions. Researchers have tested a variety of methods for automating the sentiment analysis process but very few Researchers are using Hybrid Approaches. This research paper shows the advantage of hybrid approaches to improve classification accuracy Compare to individuals. In proposed work a comparative study of the effectiveness of hybrid approaches was used for Sentiment analysis. Empirical results indicate that the hybrid approaches outperform compare to this individuals Classifiers.

Automating Business Processes to Improve Efficiency Efficient Design of Building Automation Systems
Authors:- Akaash Dey

Abstract-Back in the day, logistic companies weren’t using GPS devices and tracking software to optimize their routes throughout the day. They used to fill out bills on paper, using a finite set of receipt numbers, carrying over to accounting which spent days to a month for completion. More manpower means more delay and more cost as well, and productivity can only be followed by discipline and quality work on a gradual basis(Guerra, L., & Stapleton, L. (2019). How will our capabilities change after adding automation processes in existing businesses that follow traditional methodologies? To improve day to day operations of business using new technologies and automation to increase efficiency, save time and cost.Building and maintaining Automation Performance Index models (to keep track of the performance. We have already recognized some clear opportunities for research process automation: automated sampling, automated survey, and automated visualization of data (through online reporting dashboards or tools). These tools allow researchers to handle much bigger data sets and spend less time creating (or editing) common charts and graphs(Martinho, R., Rijo, R., &Nunes, A. (2015). This helps in quality decision making thus helping businesses to upscale.

Performance Enhancement of Leaf Spring Using Design Optimization
Authors:- M.Tech. Scholar Abhishek Chandra, Prof. G.R. Kesheorey (Supervisor & HOD), Dr. A.J. Siddiqui (Executive Director)

Abstract-Leaf spring is one of the potential parts for weight reduction as it accounts for 10% – 20% of the unsprung weightand thereforegood scope of work lies in its design optimization for weight reduction. This current research investigates the application of Taguchi Response Surface Optimization in optimizing dimensions of mono leaf spring. Initial FEA analysis is conducted using ANSYS software to determine to determine stresses, deformation and strain energy of mono leaf spring.Design of leaf spring is optimized using Taguchi design of experiments scheme generating 3D response surfaces, sensitivities, goodness of fit curves. The optimization parameter considered for analysis are spring inner radius and spring outer radius while the output parametersare equivalent stress, mass and deformation.

Fatigue Life Analysis of Tube Flange Welded Joint using ANSYS
Authors:- M. Tech. Scholar Sumit Kumar, Prof. G.R. Kesheorey (Supervisor & HOD), Dr. A.J. Siddiqui (Executive Director)

Abstract-The fatigue cracks are the one of the major cause of failures in welded joints and it us therefore essential to investigate the dimensional parameters affecting the fatigue characteristics of welded joints. The current research investigates the fatigue life characteristics of tube flange welded joint using techniques of Finite Element Method. The effect of dimensions i.e.,h, α and t on fatigue life and safety factor is investigated using Taguchi response surface method. The 3D response surface plots are generated each variable and range of dimensions are evaluated for which safety factor is maximum or minimum. The CAD modeling finite element analysis is conducted using ANSYS software.

A Glaucoma Detection Using Deep Learning Technique
Authors:-Ms. Arkaja Saxena, Avinash Pal (HOD)

Abstract- Glaucoma is a disease that relates to the vision of human eye. This disease is considered as the irreversible disease that results into the vision deterioration. Many deep learning (DL) models have been developed for the proper detection of glaucoma so far. SO here we have presented an architecture for the proper glaucoma detection based on the deep learning with making use of the convolutional neural network (CNN). The differentiation between the patterns formed for the glaucoma and the non glaucoma can be finding out with the use of the CNN. The CNN provides a hierarchical structure of the images for differentiation. Proposed work can be evaluated with total six layers. Here we also used the dropout mechanism for the effective performance in the glaucoma detection. The datasets used for the experiments are the SCES and the ORIGA. The experiment is performed for both the dataset and the obtained values are .822 and .882 for the ORIGA and SCES dataset respectively.

Design Factoid Question Answering System using BERT
Authors:- M. Tech. Scholar Sheetal Singh Goutam, HOD. Avinash Pal

Abstract-The field of text mining which deals with the providing of answers to the questions of the users is also one of the hot topics for researchers. In this paper Natural Language Processing (NLP) has been used which deals with the processing of the data that comes in any form like text, video, image, or audio. This NLP comes under the field of artificial intelligence (AI), which is used in the field of question answering (QA) system. Here proposedworked for designing a system that works for factoid QA which will answer the questions that are asked by the users.Lexical Chain and Keyword analysis is used in our system for the answering of questionsfrom a given set of articles.The reasoning system is used for the validity of the answering. The experiment here is done with the SQUAD dataset.In our experimentoverall average of the correct prediction of the answerthe accuracy obtainedfor the passage retrieval using existing TFIDF is70.30% and proposed BERT is 87.81%.

E-Mail Spam Filtring Using Machine Learning Technique
Authors:- ME Scholar Shivani Panwar, Asst. Prof. Kapil Shah

Abstract- In recent years, the single-modal spam filtering systems have had a high detection rate for text spamming. To avoid detection based on the single-modal spam filtering systems, spammers inject junk information into the multi-modality part of an email and combine them to reduce there cognition rate of the single-modal spam filtering systems, there by implementing the purpose of evading detection. In view of this situation, a new model called text-based dataset modal architecture based on model fusion (MMA-MF) is proposed, which use a text-based dataset fusion method to ensure it could effectively filter spam whether it is hidden in the text. The model fuses a Convolutional Neural Network (CNN) model and a Long Short-Term Memory (LSTM) model to filter spam. Using the LSTM model and the CNN model to process the text parts of an email separately to obtain two classification probability values, then the two classification probability values are incorporated into a fusion model to identify whether the email is spam or not. For the hyper parameters of the MMA-MF model, we use a grid search optimization method to get the most suitable hyper parameters for it, and employ a k-fold cross-validation method to evaluate the performance of this model. Our experimental results show that this model is superior to the traditional spam filtering systems and can achieve accuracies in the range of92.64–98.48%.

Intrusion Detection System Using Deep Learning
Authors:- M. Tech. Scholar Megha Sharma, Asst. Prof. Khushboo Sawant

Abstract- As the beginning of twenty-first century, PC framework describing improving Updationin form of network efficiency, several hand holders & kind of operationswhich achieve on the system. As progressing accompanied by latest generation under comfortable machines for ex: Internet mobile, tabs, smart instruments i.e. updated machines & software also several calculating devices, no. connected hand holders progressing most & most. Therefore, safety on connection has been key process which support complete hand holders. Intrusion detection has been procedure in protecting intrusion. Process of going to a system unable to take agreement termed as intrusion. An intrusion detection techniquemay predictcomplete upcoming & on- going intrusion at a structure. Intrusion detection techniquemay investigate complete priority under safety procedure with the help of managing infrastructure movement. As Intrusion detection system (IDS) are obvious class under safety layout, therefore it may manage capacity with support to determine safety points in a frame work. Numbers of several system supports under intrusion detection. Given research studying distinguishing in middle of hybrid documents opening approach & mono approach. Primary objective of the research are representing i.e. With support to hybrid document opening approaches may minimize duration difficulty in process as compared to mono approach. Particular structures were certifiedwith support to kdd’99 document pair. An observational out come significantly describing i.e. hybrid approaches with support to k-means & Projective Adaptive Resonance Theory may uniquely minimize structure practicing duration of the frame work &balancing perfectness of detections.

Healthcare Prediction Using Machine Learning Technique
Authors:- ME Scholar Chetna Sawalde, Asst. Prof. Ranjan Thakur

Abstract- In medicinal sciences forecast of Heart sickness is most troublesome undertaking. In India, fundamental driver of Death is because of Heart Diseases. The passings because of coronary illness in numerous nations happen because of work over-burden, mental pressure and numerous different issues. It is found as fundamental reason in grown-ups is because of coronary illness. Along these lines, for distinguishing coronary illness of a patient, there emerges a need to build up a choice emotionally supportive network. Information mining order systems, to be specific Modified K-means and SVM are broke down on Heart Disease is proposed in this Paper.

Reliable and Energy-Efficient Routing Protocol for Under Water Acoustic Sensor Networks
Authors:-M.Tech. Scholar Surbhi Rathore, Asst. Prof. & Head Ashish Tiwari

Abstract- The research for UASN has attracted a lot of people in recent years. Here, propagation and globalization are done for 3-D environments. The Acoustic Sensor network (UASN) works extensively with activities such as groundwater data and water filtration. An aquatic reactor network has been created to be used for marine harvesting, pollution control, marine exploitation, disaster prevention, cruise assistance, and monitoring applications. The UASN is a chemical sensor that uses batteries as a power source. Due to the difficult environment of UASN, replacing these batteries is difficult. One way to alleviate this problem is to extend the life span of UASN batteries by reducing energy consumption (improving energy efficiency). This proposes an Energy-Balanced Unequal Layering Clustering (EULC) algorithm that can improve acoustic sensor operation. The UASN layer produced by the EULC algorithm differs greatly from the nodes, providing a solution to the “hot spot” problem by building different clusters of similar size. Simulation results show that the EULC algorithm can efficiently balance the energy of the UASN platform, thus enhancing network life.

Facial Expressions Recognition Based on LBP & SVM
Authors:- M.Tech. Scholar Nagesh Patel, Asst. Prof. & Head Ashish Tiwari

Abstract- Facial expression analysis is a compelling and demanding problem affecting important applications in various fields such as human-computer interaction and data-driven animation. The development of effective facial expressions from the original facial images is an important step in gaining facial expression recognition. The actual evaluation is based on the face representation of statistical local functions, local binary pattern (LBP). Several machine learning techniques have been thoroughly observed on various databases. Researchers usually use the effective and competent LBP feature of facial expression recognition. Cohn Kanade is the database for the current work and the programming language used is MATLAB. First, the face area is divided into small areas through which histograms are extracted, local binary pattern (LBP) and then connected as a single function vector. This feature vector outlines a well-organized representation of face and is helpful in determining the resemblance among images. These operators along with other proposed techniques were experimented considering different settings viz. with or without localization and registration errors, person dependent or independent, operator scales, number of grids (hence the size) and number of available LBP based codes. The FR system was configured in verification mode using Eigen face approach derived on these LBP based histogram feature vectors. The FER system was configured for multi-class facial expression classification mode using Support Vector Machine (SVM). Experiments on facial expression databases reveal that maximum recognition rate would be obtained for the scale in which width is larger than height of the operator. Both proposed operators are sensitive to registration errors. However, these operators could be applied in automatic FERS.

Online Crime Management System
Authors:- S.S. Sugania, D. Jason Daniel Raj, S. Jagath Ratchagan, C. Dinesh Pandi

Abstract- The Online Crime Management system is designed in such a way that, it can be accessed anywhere through internet. A person who is about to file a complaint approaches the portal and registers into the portal using his information. After that the admin authenticates the user, after a successful authentication the user can login into the portal. The complaint will be received at the police end. And the process will be updated in the portal. For the efficiency of the police, various criminal activities are collected as datasets and analyzed using the KNN algorithm. The crime types like methods, properties used, fingerprints obtained are analyzed using the datasets. Now if the crime filed by the user matches the crime patters occurred before it will be easy for the police to solve the crime.

Image Processing Based Leaf Disease Detection Using Raspberry Pi
Authors:- Dinesh Kumar R, Prema V, Radhika R, Queen Mercy C.A, Ramya S

Abstract- Green plants are very much important to the human environment; they form the basis for the sustainability and long term health of environmental systems. In this project, we have proposed a system using raspberry pi to detect healthy and unhealthy plants & alerts the farmer by sending email. The main objective of this project is detection of diseases at the early stage. We mainly focus on image processing techniques. This includes a series of steps from capturing the image of leaves to identifying the disease through the implementation in raspberry pi. Raspberry pi is used to interface the camera and the display device along which the data is stored in the cloud. Here the main feature is that the crops in the field are continuously monitored and the data is streamed lively. The captured images are analyzed by various steps like acquisition, preprocessing, segmentation, clustering. This turn reduces the need for labor in large farm lands. Also the cost and efforts are reduced whereas the productivity is increased. Automatic detection of symptoms of diseases is useful for upgrading agricultural products. Completely automatic design and implementation of these technologies will make a significant contribution to the chemical application.

A Review on Software Fault Detection using a Classification Model with Dimensionality Reduction Technique
Authors:- Research Scholar Devangi Paneri, Research Scholar Mansi Chauhan

Abstract-Software plays the most important role in every organization it requires high-quality software. If a fault happens in this system then it causes high financial costs and affects people’s lives. So, it is important to develop fault-free software. Sometimes, a single fault can cause the entire system to frailer. So in the SDLC life cycle Fault prediction at an early stage is the most important activity it helps in effectively utilize the resources for better quality assurance. So before delivering the software to market it is important to identify defects in the software because it increases the customer satisfaction level. here in this survey paper present an ensemble approach to identifying fault before delivering the software. Ensemble classifier improved classification performance compared to the single classifier. So improved the accuracy the new algorithm is proposed that is “improved random forest” it works with random forest classifier with filter-based feature selection method. The feature selection method reduces the dimensionality and selects the best subset of features and gives that subset to the random forest classifier. The experiment carried the public NASA dataset of the PROMISE repository.

Load Flow Studies of 132/33KV Transmission Line in Port Harcourt Zone Using Newton Raphson’s Method
Authors:- M. Tech. Scholar Eze I. Wokocha, Prof. Christopher O. Ahiakwo, Prof. Dikio C. Idoniboyeobu

Abstract- This paper critically examines the Load Flow condition of the Port Harcourt Mains and Town 132/33kV transmission networks. In carrying out the Load flow study, the Newton Raphson power flow method in Electrical Transient Analyzer Program (ETAP) was used to evaluate the performance of both networks. Findings from the simulation exercise showed a lot of grey areas that required urgent attention within both networks. The combined transmission efficiency recorded low and the total system apparent losses stood at 52.5912MVA. All transformers were critically loaded as some exceeded 100% loading. The percentage operational bus voltages were below threshold as bus voltage magnitudes fell outside the +/- 5% nominal rated values. The systems also had undesired power factor levels. These threatening findings led to the quest to improve the networks. Three system improvement algorithms were used in this research viz: capacitor placement, transformer upgrade and transformer load tap modifications. These algorithms were superimposed in a stepwise mznner to obtain the most desired result. The final simulation result saw the performance of both networks within acceptable limits as the systems were greatly improved. The total system apparent losses reduced to 26.129MVA (50% improvement). All percentage loading of transformers were seen below the 60% benchmark. Bus voltage levels with significantly within the +/-5% limit and finally the power factor values were good.

Enhanced Drowsiness Detection Using Machine Learning
Authors:- Mohamed Nasrutheen. S, Morton Rillo. S, Naveen. A, Asst. Prof. Ms. K. Thamizharasi M. E

Abstract- A recent study showed that around half a million accidents occur in a year, in India itself. Out of which 60% of these accidents are caused due to Driver Drowsiness. Previous approaches are generally based on blink rate, eye closure, and other hand-engineered facial features. The proposed algorithm makes use of features learned using a convolutional neural network (CNN) to explicitly capture various latent facial features and the complex non-linear feature interactions. This system is hence used for warning the drowsiness of driver by ringing an alarm as well as to prevent traffic accidents by turning ON Parking lights and information shared to the registered mobile number via SMS, Phone Call with the help of GSM Module. This can reduce more than 50 percent of the accident.

Enhancing Air Pollution Predicton Using Artificial Neural Network with XGBOOST Algorithm
Authors:-Asst. Prof. Christina Rini R, Aishwarya N, Meenakshi G, Saranya M

Abstract- Air pollution has become a major public health concern in recent years. Despite substantial improvements in overall air quality in recent years, India remains the third most polluted country according to the latest edition of the World Air Quality Report [1]. The release of gases into the air that are harmful to human health and the environment is referred to as air pollution. Lung cancer, cardiovascular disease, respiratory disease, and metabolic disease have all been linked to high concentrations of fine particulate matter with a diameter less than 2.5 m (PM2.5). Experimental research with various machine learning algorithms has yielded promising results in the field of air pollution prediction. Predicting air quality by determining concentrations will assist different departments, including governments, in alerting people who are at high risk, reducing complications. An improved air pollution prediction approach based on the XGBOOST and ARTIFICIAL NEURAL NETWORK algorithms is used to forecast air quality. Our goal is to look into a machine learning-based approach for air quality forecasting using the AQI index and get the best results possible. In addition, we compare the performance of different ML algorithms from the dataset with the use of a GUI to predict air quality by characteristics.

Android Agricultural Application
Authors:- Omkar Aditya, Aparna Shukla

Abstract- Forecasting and technical information regarding farming can be provided by the experts of the farming community to the farmers by using new development in Information and Communication Technology (ICT). Agriculture kiosk is one of the many routes by which farmers in the rural areas get various agriculture information on the run using IT-based application installed in a Kiosk. There are few disadvantages of kiosks given as; a) It is not user friendly. b) Setup cost of the kiosk is very high. c) Problem of internet network connection. d) Security cost for protecting kiosk. Here, in this document, we have planned to build an IT-based application which provides a piece of information to the farmers overcoming the above problems by developing android application. The android operating system is open-source; using it we can design and develop software having functionality similar to agriculture kiosk. After developing an android application, we can deploy it in an android market, so that everyone can download it freely. This research paper shows how to design and implement such a technique which focuses on mobile farming technology.

Human Facial Expression Recognition Model Using Convolutional Neural Network
Authors:- Asst. Prof. M. J. Freeda, Maajidha Kamar. A, Lisha. S, Iswarya. M

Abstract- Facial expression is that the most powerful and natural non-verbal emotional communication methodology. the popularity of facial expressions isn’t a simple downside. folks will vary considerably within the approach they show their expressions. Hence, the face expression recognition remains a difficult downside in pc vision. To propose an answer for face expression recognition that uses a mix of Convolutional Neural Network and specific image preprocessing steps.It delineate the innovative resolution that has economical facial expression and deep learning with convolutional neural networks (CNNs) has achieved nice success within the classification of assorted face feeling like happy, angry, unhappy and neutral.

Emotional Contagion in Teenagers and Women
Authors:- Kavadi Teja Sree

Abstract- This study aimed at measuring the difference between emotional contingency among teenagers and women by using The Emotional Contagion Scale by Doherty, R.W. Emotional contagion is the phenomenon of having one person’s emotions and related behaviour’s directly trigger similar emotions and behaviour’s in other people. Emotions can be shared across individuals in many different ways both implicitly or explicitly. The Emotional Contagion Scale was designed to assess people’s susceptibility to catching joy and happiness, love, fear and anxiety, anger, and sadness and depression, as well as emotions in general (Doherty, 1997; Hatfield, Cacioppo, & Rapson, 1994, p. 157). The main objective of this study is to study whether emotions are contagious among teenagers and women. The survey was conducted among under graduates and post graduates between the age group of 15-28, in 100 under graduates and post graduates, among which 50 of them were teenagers and 50 were women. A statistical analysis of mean, standard deviation and t test were used, thereby concluding that there is a significant difference between teenagers and women. It was found that teenagers were more emotionally contagious than women in general. The study suggests that the teenagers and women should inculcate themselves first and be positive.

Design and Fabrication of Three Axis Rotating Trailer Using Pneumatic System
Authors:- Asst. Prof. S. Divya, Praveen S, Ramchandran R, Selvayukesh M, Sridhar S

Abstract- This project work “design and fabrication of Three axis rotating trailer using pneumatic system” has been conceived having studied the trouble in emptying the materials. Our review in the respect in a few automobile garages, reveals the fact that generally some troublesome strategies were embraced in emptying the materials from the trailer. The trailer will empty the material just in one direction only. It is hard to empty the materials in small compact roads and small streets. All the three sides are effectively to unload the trailer in our task are rectified. Automobile engine drive is coupled to the compressor engine, the compressed air its stores when running the vehicle. the pneumatic cylinder are is used to activate this compressed air, when activate the valve. Spur gear is used for rotating the trailer in three directions & easy for unloading the materials in small compact streets and roads.

Alam’s Model (“The BASE Model”)
Authors:- Mohammed Shafiq ALam.N

Abstract-Introduction–Stable Body Model–BASE Model–Gravity–Formation of Single Cell Atom –The Force, holding the “electrons” and “Planets” in their orbit–Electromagnetism–Light–Conclusion–Applications–Acknowledgement.

Robotic Arm Controlled by Using Arduino Uno
Authors:- Nikhil J.Solaskar, RushikeshM.Desai, AkashD.Sarkar, GaurangP.Tari,
Asst. Prof. VaishaliP.Ramtekkar

Abstract-In recent years the industry and daily routine works are found to be more attracted and implemented through automation via Robots. The pick and place robot is one of the technologies in manufacturing industries which is supposed to perform pick and place operations. The system is so designed that it eliminates the human error and human intervention to urge more precise work. There are many fields during which human intervention is difficult but the method taken into account has got to be operated and controlled. This results in the world during which robots find their applications. Literature suggests that the pick and place robots are designed, implemented in various fields such as; in the bottle filling industry, packing industry, utilized in surveillance to detect and destroy the bombs etc. The project deals with implementing a pick and place robot using Arduino for any pick and place functions. The pick and place robot so implemented is controlled using Bluetooth over Arduino Uno. The robotic arm implemented has three degrees of freedom. Many other features like line follower, wall hugger, obstacle avoider, detector etc are often added to the present robot for versatility of usage.

Face Mask Detection Using Tensor Flow JS. and Arduino
Authors:- Saswat Samal

Abstract-Coronavirus is continuously spreading until now all over the world. The impact of COVID-19 has been fallen on almost all sectors of development. Many precautionary measures have been taken to reduce the spread of this disease where wearing a mask is one of them. In this paper, I propose a system that restrict the spread of COVID by finding out people who are not wearing any mask in the public places which are monitored with cameras. While a person without a mask is detected, a warning sign is created and not allowed to enter into the building. A transfer learning architecture is trained on a dataset that consists of images of people with and without masks collected from various sources. It is hoped that the study would be a useful tool to reduce the spread of this communicable disease for many countries in the world.

Literature Survey of Two-Way Authentication System
Authors:- Mrs Dnyanada Hire, Monika Bhatt, Mohit Anand,Chaitanya Harde

Abstract-We all need to use stronger passwords which should not include our names, sequential number and birthdates even if these are easy to remember. But strong passwords are hard to remember so, the solution is Two-Factor Authentication (2FA). Two-factor authentication, also called multiple-factor or multiple-step verification, is an authentication mechanism to double check that your identity is legitimate, and this does not require transferring data over the internet. The two-factor authentication security feature has the following advantages: Enhanced security, helps in fraud prevention, Easy for users to understand and enable, Easier and quick account recovery

Predicting Areas of Improvement to Boost Up the Sales Using Data Analysis Techniques
Authors:- Manas Maheshwari, K Sai Varun, Farman Ahmed, Sonali Borase

Abstract-This paper gives an overview of Data analysis and how Data analysis is used in Business Intelligence tools and business development. It gives different algorithms and techniques to perform Data analysis and its implementation.

Design and Implementation of Fast Charging Universal Power Bank Using Super Capacitor
Authors:- Asst. Prof. Mr. K. Sathiyaraja, M. Sasikala, R. Shobhana, R. Thamil Ilakkiya, R. Manoj

Abstract-Portable power banks are comprised of battery in a case with a circuit to control power flow. Power banks are becoming increasingly popular because the battery life of phones, tablets and portable media players is exceeded by the number of time gadgets used in a day. In this project, the design and implementation of universal power bank using super capacitors as a charge storage device is presented. Existing power banks use batteries to store charges and it takes a long time to charge completely. In this work, batteries are replaced with super capacitors to take advantage of its quick charging and slow discharging feature. Super capacitors are charged using charging and regulation circuit. An output regulator circuit delivers the necessary power for charging portable devices. A display is also implemented using a Atmega microcontroller for monitoring. Battery technologies are well established and widely used technology but they offer several disadvantages like weight, volume, large internal resistance, poor power density, poor transient response. On the other hand, due to advancement in the material and other technology, Super capacitor or Ultra capacitors or Electrostatic Double Layer Capacitor (EDLC) are a most promising energy storage device. They offer a greater transient response, power density, low weight, low volume and low internal resistance which make them suitable for several applications.

Cyber Security: The Study on Information Gathering
Authors:-Varun Verma, Saurabh Kumar Dubey, Tajwar Khan, Prem, Himanshu Pandey

Abstract- Internet-wide network scanning has numerous security applications, including exposing new vulnerabilities and tracking the adoption of defensive mechanisms, but probing the entire public address space with existing tools is both difficult and slow. We introduce GRABIN – An automated Cyber Security tool by which we can gather the information about the particular target like we can gather the information about domains, subdomains, users, user emails, open ports, their IP addresses and much more. Also, we are able to find web App vulnerabilities in the proper CVE format, and we are able to hash the values and we can encrypt and decrypt out messages by using the tool. We present the scanner architecture, experimentally characterize its performance and accuracy, and explore the security implications of high speed Internet-scale network surveys, both offensive and defensive. We also discuss best practices for good Internet citizenship when performing Internet-wide surveys, informed by our own experiences conducting a long-term research survey

Effect of Multifluid Flow for Internal Heat Generation or Absorption in Presence of Concentration in a Vertical Channel
Authors:-Mangala Kandagal, Shreedevi Kalyan

Abstract- The effect in heat mass transfer and of multi-fluid flow characteristics in vertical channel is investigated in this paper. The fluids are incompressible in both the region and assumed the transport properties of fluid flow are constant. By the help of analytical method all the basic equations governing th set of coupled nonlinear ordinary differential equations are solved. These results are illustrated by plotting graphs and for various physical parameters. Here we can control result by heat absorption coefficient, width ratio and viscosity ratio.

Online Crime Management System
Authors:-S.S. Sugania, D. Jason Daniel Raj, S. Jagath Ratchagan, C. Dinesh Pandi

Abstract- The Online Crime Management system is designed in such a way that, it can be accessed anywhere through internet. A person who is about to file a complaint approaches the portal and registers into the portal using his information. After that the admin authenticates the user, after a successful authentication the user can login into the portal. The complaint will be received at the police end. And the process will be updated in the portal. For the efficiency of the police, various criminal activities are collected as datasets and analyzed using the KNN algorithm. The crime types like methods, properties used, fingerprints obtained are analyzed using the datasets. Now if the crime filed by the user matches the crime patters occurred before it will be easy for the police to solve the crime.

Survey on Detection and Identification of Face Mask
Authors:-J. Jenitta, Shrusti B K, Vidya D Y, Vinay S Sinnur, Shivesh Varma P

Abstract- The world is coming out of lockdown and starting its new normal. As Education plays a key role in every student’s life, the Government is planning to reopen schools and colleges after the COVID-19 pandemic situation. It is mandatory for the educational institutions to follow Standard Operating Procedure(SOP) to reduce the risk of spread of COVID-19 in the institution campus. In SOP one important point is wearing a face mask because the virus that causes COVID-19 is mainly transmitted through droplets generated when an infected person coughs, sneezes, or exhales. These droplets are too heavy to hang in the air, and quickly fall on floors or surfaces. This paper aims to review various state of art methods available to find whether the person who is entering the institution is wearing a face mask or not, using various machine learning techniques.

Speed Control Analysis and Performance Comparison of Induction Motor Using Improved Hybrid PID Fuzzy Controller
Authors:-Sartaj Singh, Prof. Priya Sharma (HOD)

Abstract- To control the speed of an induction motor is very difficult. The speed control relies on the electric power factor offered to the motor. Many researchers have performed a significant number of studies to enhance the mechanism of vector control. They have used different controllers such as PI (Proportional Integral), PD (proportional derivative), Fuzzy-PI, Fuzzy PID (Proportional Integral derivative). In this paper, a novel approach is developed which used hybrid controller. This controller is developed by the amalgamation of Fuzzy type-2 and PID controller. Fuzzy type-2 has various advantages over type-1 fuzzy which overcome the limitations of the traditional system. A literature survey is given with the detailed information of the works done in this field. The mechanism is developed by taking into consideration different parameters such as rise time, settling time and overshoot. The proposed model is analysed using MATLAB. Simulation results showed the better efficiency of the novel controller. Is observed that, developed controller reduced the time required by the motor to achieve its target speed, thus, gives excellent outcome.

Patient’s Health Monitoring System with Smart Medicine Box
Authors:-Ms. S. Sivaranjini Ap/Cse, V. Chithiraiselvi, M. Suruthi, M. Vinitha

Abstract- The medicine box system contains a biomedical sensor to monitor the health condition of the patient. The information about the health condition and the details of medication will be stored in the server which can be accessed by both doctor and patient and also doctor can change the prescription based on the patient’s condition on the server. The intelligent medicine box will help a patient to remind the right time to take the medicine based on prescription by receiving notification to the patient’s fixed email address using Wi- Fi module and he also will receive voice message using speaker. If he forgets the actual time of taking medicine and goes to take medicine at any time the medicine box will not open as a servo motor will make the box locked.

Review of Skin Diseases Classification Using Machine Learning
Authors:- Ram Charan Mishra, Rahul Mishra, Kusum Sharma

Abstract- Skin diseases are among the most common health problems worldwide. These diseases like acne, eczema, benign, or malignant melanoma have various dangerous effects on the skin and keep on spreading over time. Feature extraction using complex techniques such as SVM (Support Vector Machine) and Convolutional Neural Network (CNN). The work may in the future serve as a knowledge base for an expert system specializing inmedical diagnosis, testing evaluation, treatment evaluation, and treatment effectiveness. AlexNET, a pre-trained CNN model will be used to extract the features. This system will give more accuracy and will generate results faster than the traditional method. multiple skin lesions are classified using different image processing and machine learning techniques. The most used machine learning techniques used for skin lesion classification are SVM, trees, artificial neural network K-nearest neighbor, ensemble classifiers and convolution neural network (CNN).

Structural Synthesis of Melamine on the Properties of Concrete Different Mix Time Slice
Authors:- M. Tech. Scholar Mohit Chandak, Asst. Prof. Sourabh Dashore

Abstract- The performance of concrete primarily depends upon the sort and quantitative relation of its constituents, compaction, natural conditions and admixtures used throughout the action process. A part of this analysis emphasis to calculate the results on strength of concrete once water-cement quantitative relation is constant and the rise in slump happens with the increase in the quantity of Super plasticizer. The rest of the investigation is dispensed to review the results of Superplasticizer with completely different dosages under completely different action regimes at the associate close field with different temperatures. For this purpose, a concrete combine with silica fume and fly ash with all parameters constant was associate anionic alkali based Superplasticizer with no chlorides. Different percentage of melamine were employed in completely different batches of all 48 specimens and cured under completely different action conditions so tested for compressive and tensile strengths following the water curing testing showed most strength. The highest and lowest values of compressive strength were obtained with the addition of 1.5% to 4.5% Superplasticizer severally. It had been found that while not increasing the W/C quantitative relation, the addition of the Super plasticizer exhibits an increase in strength.

Investigation of Performance of Organic Rankine Cycle-Vapor Compression Refrigeration System Using Different Refrigerant
Authors:- M. Tech. Scholar Amjad Fahad Usmani, Prof. Dr. M. K. Chopra

Abstract- In this study, the energy and exergy analysis of a combined cycle was carried out. This cycle consists of an organic Rankine cycle and a vapor compression refrigeration cycle for producing the cooling effect. Four organic fluids were used as working fluids such as R600a, R245fa, RC318 and R236fa. The parametric analysis allowed us to characterize the combined system and to study the effect of some parameters that were used to estimate the thermal and exergy efficiency of the studied system. The results showed that the operating parameters have a significant impact on the performance of the combined system. Due to environmental issues of R600a is recommended as a superior candidate for the ORC-VCR system for retrieving low-grade thermal energy.On the other hand, the results of the exergydestruction distribution showed also that maximum exergy destruction rate is found in R600a and minimum is in RC318.

The Importance of Drone Technology in Nigerian’s Construction Industry
Authors:- Birmah M. Nyadar, Buba Y. Alfred, Audu M. Justina, Dr. Jibrin Sule, Maton D. John

Abstract- Drone is also known as Unmanned Aerial Vehicles (UAVs) are aircrafts that fly without any humans being onboard. They are either remotely piloted, or piloted by an onboard computer. Drones are used for emergency response, inspection of damaged roofs, collapsed buildings, accessing difficult to reach places and many builders / engineers have come to rely on drones for their everyday operations in the developed countries. The advent of new construction technologies did not exterminate the job for construction workers, rather it created a room for workers to acquire skills of the modern technology for the new generation. Drones are not common in Africa and has been grounded in some countries because the governments do not have full understanding of the technology. The professionals in other related fields don’t really have the knowledge of operating drones. The purpose of this paper is to create awareness of drone technology application in the Construction Industry of Nigeria, which the use of drones is not common in Nigeria. Oral interview with the construction workers in Abuja and the use of personal observation and open source materials were part of the methodology. The use of drones save time, reduces cost, allows remote monitoring of construction site, easy accessibility to difficult terrains or sites and reduces risk of human lives to dangerous sites. The Nigerian Construction Industry needs to embrace the use of drones in all project execution for effective job delivery, the Public and the Private sector can invest in the technology where Professions can be trained in drones operation, the engineers with interest in drone technology should establish a drone service / repair center as an avenue for job creation in Nigeria.

Student Performance Prediction using Machine Learning Techniques
Authors:- M. Tech. Scholar Nandini Sahu, Prof. Ashutosh Khemariya, Prof. Aditi Tiwari

Abstract- The capacity to screen the advancement for students’ academic execution is an essential issue of the educational Group from claiming higher Taking in. An arrangement to dissecting students’ comes about dependent upon group dissection and utilization standard measurable calculations with organize their scores information as stated by the level about their execution may be portrayed. In this paper, we also actualized the k-mean grouping algorithm for examining students’ consequence information. Those model might have been consolidated for those deterministic model should dissect those students’ effects of a private foundation clinched alongside % Iberia which is a great benchmark with screen the progression of academic execution about people for higher institutional to the reason for making an successful choice by those academic organizers.

Android Phone Data Security using Special Features
Authors:- M. Tech. Scholar Rumana Nigar Ansari, Prof. Ashutosh Khemariya, Prof. Aditi Tiwari

Abstract-Today, everyone necessarily requires a smart phone. There are tremendous number of possibilities and numerous scopes witnessed in different areas of the mobile world. With this rapid growth in mobile services the researchers are alarmed about the security threats and are working upon it by securing the infrastructures which support the online-interface and other distributed services. Man has embraced mobile phones like a best friend. Among 7 billion people worldwide, around 4 billion smart phones and millions of tablets are in use. A smart phone has various utilizations like taking pictures, watching movies, listening songs, surfing internet, making bank transactions, using social media, calling etc. A smart phone user keeps all his personal and professional data in his phone. These devices are valued immensely as we keep all our records in it. The personal data carried by such mobile devices are very important. These important and sensitive data (account numbers, policy numbers and others) can cause trouble if the device is lost. At present, there are a huge number of populations which recognize the security threat of smart devices and personal computers. Still, many do not realize the everyday threat while accessing their smart devices. As a matter of fact, around 32 percent of the population thinks that they do not require any software for securing their smart phone devices. But this mindset and rising fame of smart mobile devices have attracted cyber crime up to an extreme extent. Over the period of months, the attacks have increased and reached up to 37 percent. This has become the topic of discussion at this hour and several reports have been published for the same. These reports also talk about the susceptibility of the android smart devices. The susceptibility of smart phones is about 99 percent as mentioned by a survey. These personal phones and tablets are actually a type of mini-computers and they are more prone to vulnerability than desktops. Therefore, a mobile user must be very careful about his smart device and install a simple application and put a password to safeguard his data.We discuss about secure android application on android phone. The objective is to provide such services which can secure customers’ android devices. This data security methodology of cell phones is quite novel. In this paper, we discuss about using AES algorithm for handling the data of Android mobile phones.The objective is to provide such services which can secure customers’ data. This data security methodology of cell phones is quite novel.

Zigbee-GSM Based Automatic Meter Reading System
Authors:- Prof. Z.V. Thorat, Shreyas Chaudhari, Siddhant Hajare, Mansi Kamble, Karan Katariya

Abstract-This project is concerned with the electrical board. As the population grows, the number of electric meters is increasing. In India standard meters are widely used to calculate power consumption. Collecting this large amount of data requires extra time and effort. In this way before the bills are made the meter readings are kept by hand in low-level channels, which are time consuming and full of human error. As a result, the consumer always complains about his or her debts. This whole network is full of holes in different categories and cannot be removed or found. To avoid this type of problem, wireless meter reading technology can be used. It also saves staff. Another feature of this meter is that it improves accuracy because it works in real time. It increases the speed of operation because it requires fewer human efforts and especially energy consumption is very low. In this case, the power consumed by the consumer is monitored by low-level channels via a wireless network. In low-level channels, debt is calculated and records are kept. By using this process, we can easily monitor any error in the meter and any interference is used to steal electricity. Eliminates error of any type of data loss during data transfer and acceptance. The main part of the model is “ZigBee”, because it has a lower data rate and therefore uses less operating power. As we know from ZigBee devices, no one can use the data, only authorized person or device can read the data. That is why it is so reliable. Therefore, this model is a test to remove all errors created with standard meters.

Structral Behavior of Concrete Bridge with Soil-Structure Interaction
Authors:- M. Tech. Scholar Neeraj Sansiya, Prof. Sourabh Dashore

Abstract-An iterative plan technique of progressive straight unique reaction investigations that considers the non-direct conduct of the projections brought about by refill soil yielding is created. Likewise, a non-straight static investigation of the extension soil framework is directed. These examinations explore the impacts of the dirt projection association on seismic investigation and plan of vital scaffolds. Past experience and late examination demonstrates that dirt structure collaboration assumes a significant part on the seismic creation of scaffold structures. Projections pull in an enormous segment of seismic powers, especially in the longitudinal course. In this way, investment of refill soil at the projections must be thought of. A plan-driven system to show the projection firmness for either direct or non-straight examination, considering the inlay and the wharf establishment, is introduced. An extension with solid projections is chosen to exhibit the proposed methods. Parametric investigations show that, if the scaffold is examined with the proposed system rather than a basic methodology that disregards refill firmness decrease, the determined powers and minutes at the docks are more prominent by 25%- 60% and the removals by 25%-75%, contingent upon soil properties.

Modern Air Purifier Drone for Control Air Pollution
Authors:- Asst. Prof./HOD Ramya. R, Asst. Prof. Punithavathi. K, Hariharan. M, Karthi. G, Mohamed Al Ameen. H, Vishnuvarthan. U

Abstract-The pollution is presently become very burning issue not only in India but also all over the globe and it is various types, therefore, here, we considered only air pollution for depth discussion. Pollution refers to the release of chemicals or inimical substances including particulates and biological molecules into the earth`s environment which has a very insidious effect on human, animal and plant life. It is a significant risk factor for several pollutions cognate diseases and health conditions including lung cancer, heart diseases, etc. and water react very rapidly to pollutants and will abstract.

Incisive Health Recognizing for Animals
Authors:- Asst. Prof./HOD Ramya. R, Asst. Prof. Dhivya. K, Afra Banu. A, Arthi. P, Kayalpraba. G, Nithya. V

Abstract-In the some cases of emergency, veterinary or pet hospital staff cannot able to treat sick animals immediately as they cannot monitor animals after surgery or recuperating for 24/7. This problem is the leading cause of death in said animals. Therefore, developers have the concept to develop a health monitoring system which keeps tracking the heart rate and temperature of sick animals in veterinary hospital. The web application focuses on the rate of heart rate and temperature. If the heart rate and temperature are abnormal, it will alarm veterinary or pet hospital staff the animal is at risk and needs to be treated correctly. This system can be monitored by recording and analyzing the health information of sick animals, when animals have abnormal heart rate or temperature, they can be treated as soon as possible.

Instinctive Escalation and Surveying System for Farming
Authors:- Asst. Prof./HOD Ramya. R, Ajithkumar. M, Balamurugan. N, Sakthivel. V, Vignesh. S

Abstract-Agriculture plays a crucial role in the Indian economy. It’s not only a food and raw material but also provides employment opportunities. Instead of increasing the scale of agriculture a better way will be implementing smart is precision agriculture technique using IOT. This model can be very effective than the traditional method as risk of crop failure, less yield, excessive water supply or excessive use of fertilizers and pesticides ect. To monitor the environmental factors such as Temperature, humidity, soil moisture etc and help the formers in handling the crops automatically without any manual effort. The yield of any crop can be maximized with the help of precision agriculture by reducing the wastage. The data controlled by the sensor nodes deployed all over the field in sent to the cloud and there the data is analyzed and visualized for the ease of formers. With the help of visualized data formers can take precise and effective decision affecting their crops.

Smart Strike of Fruit Aspect Using SVM Algorithm
Authors:- Asst. Prof./HOD Ramya. R, Asst. Prof. Thaiyalnayagi. S, Mahadevi. M, Sabitha. D, Nithya. L

Abstract-Diseases in fruit cause devastating problem in economic losses and production in agricultural industry worldwide. In this paper, a solution for the detection and classification of fruit diseases is proposed and experimentally validated. The image processing based proposed approach is composed of the following steps; in the first step K-Means clustering technique is used for the image segmentation, in the second step some features are extracted from the segmented image, and finally images are classified into one of the classes by using a Support Vector Machine. Our experimental results express that the proposed solution can significantly support accurate detection and automatic classification of fruit diseases. In the third step training and classification are performed on a SVM. It would also promote Indian Farmers to do smart farming which helps to take time to time decisions which also save time and reduce loss of fruit due to diseases. The leading objective of our paper is to enhance the value of fruit disease detection.

Systematic Perusal of Volder’s Algorithm in Lifescience
Authors:- Asst. Prof. /HOD Ramya. R, Asst. Prof. Sahaya Reshma. M, Gayathri. R, Parkavi. G, Rakshitha. R

Abstract-In medical field, ICA plays an important role. This system reduce the power consumption and memory using Modular multiplication. The proposed approach reduce the circuit area in separating the super-Gaussian source signals. Efficient hardware architectures for modular multiplication, modular inversion, unified point addition, and modular multiplication are proposed. In this system aims to design and implement a very large scale integration [VLSI] chip of the extend Infomax ICA algorithm. Further more, the measurement results show the ICA core can be successfully applied to get output within a minutes.

Solar Power Driven Multifunctional Agribot
Authors:- Asst. Prof. /HOD Ramya. R, Asst. Prof. Lakshmipriya. D, Ajitha. V, Kavipriya. D, Parkavi. B

Abstract-This paper aims to design an agricultural robot, which helps the people to survive where it performs operations such as digging of soil, sowing of seeds, spraying pesticide, cutting grass and ploughing and the detection of obstacles. In previous projects the techniques used were complicated as well as expensive. This AGRIBOT uses the renewable energy i.e. solar energy obtained from solar panel powered battery, it also consists of a visual obstacle detector and a Bluetooth module which is paired with a Bluetooth terminal application through which it is easily controlled and the instructions are given to the AGRIBOT for the operations to be performed. Hence this is a low cost AGRIBOT and is easy to operate without the need to go to the field personally it also helps the farmers to facilitate to ease work by reducing human effort, saving time and energy. By this farming can be done easily in any climatic condition irrespective of day and night. This agribot compared to other robots is very beneficial as it has multitasking functional system and advanced techniques for smart farming.

Image Processing Based Leaf Disease Detection Using Raspberry Pi
Authors:- Dinesh Kumar R, Prema V, Radhika R, Queen Mercy C.A, Ramya S

Abstract-Green plants are very much important to the human environment; they form the basis for the sustainability and long term health of environmental systems. In this project, we have proposed a system using raspberry pi to detect healthy and unhealthy plants & alerts the farmer by sending email. The main objective of this project is detection of diseases at the early stage. We mainly focus on image processing techniques. This includes a series of steps from capturing the image of leaves to identifying the disease through the implementation in raspberry pi. Raspberry pi is used to interface the camera and the display device along which the data is stored in the cloud. Here the main feature is that the crops in the field are continuously monitored and the data is streamed lively. The captured images are analyzed by various steps like acquisition, preprocessing, segmentation, clustering. This turn reduces the need for labor in large farm lands. Also the cost and efforts are reduced whereas the productivity is increased. Automatic detection of symptoms of diseases is useful for upgrading agricultural products. Completely automatic design and implementation of these technologies will make a significant contribution to the chemical application.

Big Data Mining in Internet of Things Using Fusion of Deep Features
Authors:- Faraz Pourafshin

Abstract- Today internet of things is employed in different fields such as security, protection and health care systems. This major attention causes huge amount of information transfer from different nodes in network. Recently, big data mining has become one of the most crucial challenges in IOT. In this paper, a novel method based on deep learning is proposed to mine images which is collected from IOT. The proposed method consists of two parts: 1) Features extraction, 2) classification. Features from a convolutional neural network called Alexnet is extracted to use in data mining process. In classification part, a couple of K Nearest Neighbor (KNN) is employed to process features. Also a majority voting approach is used to find the final result. We evaluated our method by pictures which was captured by MIT University. Experimental results proved that the proposed method has better accuracy and precision in comparison of KNN, SVM, Neural network and Bayesian classifiers.

Electricity Generation by E-Bump
Authors:- Parth Gotawala, Smit Gamit, Kedar Kelawala, Niraj Patil, Punit Suthar, Asst. Prof. Happy Patel

Abstract- This project is designed to use the jerking movement produced by the vehicle while passing the speed breaker and then turns this energy to electricity which then can be used for other purposes. Consequently, a kinetic energy is produced and transferred into electrical power. And the biggest advantage of this type of speed breaker over other speed breakers that produces electricity is that, it is not necessary to dig down the road to install or do the maintenance of the speed breaker. Designing energy recovery systems that are pollution free has become a significant goal.

Sentiment Analysis:Textblob For Decision Making
Authors:- Associate Prof. Praveen Gujjar J, Prof. Prasanna Kumar H R

Abstract- Data is the new oil for the market survey. Internet is the one where it constitute the huge amount of the data in the form of customer reviews, customer feedback etc., TextBlob is one of the simple API offered by python library to perform certain natural language processing task. This paper proposed a method for analyzing the sentiment of the customer using TextBlob to understand the customer opinion for market survey. This paper, provide a result for aforesaid data using TextBlob API using python. The paper includes advantages of the proposed technique and concludes with the challenges for the decision makers when using this technique in their market survey.

Modelling of Arduino Based Pre-Paid Energy Meter Using GSM Technology
Authors:- Asst. Prof. Syed Shajih Uddin Ahmed, Md. Basheer Ahmed, Md. Shahnawaz Khan, Mirza Akif Ali Baig

Abstract- This project presents the design and modelling of Energy recharge system for Prepaid metering. The present system for energy building in India is error prone and also time and labor consuming. Errors get introduced at every stage of energy billing like errors with electro-mechanical meters, human errors and processing errors. The aim of this project is to minimize the error by introducing a new system of Pre-paid energy metering. This will enable the user to recharge his/her electricity amount from or any place by using a GSM Module. We can easily implement many add-ons such as energy demand prediction, real time tariff as a function of demand and so on.

Natural Frequency and Dynamic Stability Region Study
Authors:- Prof. A. K. L. Srivastava, Md Mozaffar Masud

Abstract- The dynamic instability regions are analysed using Hill’s infinite determinants system. The excitation frequency of plates with different boundary conditions, or aspect ratios, was investigated. The results are determined using the bending displacements of plate and stiffener. The results show that the principal excitation frequency regions have a significant effect considering and neglecting in-plane displacements.

Power Generated by Regenerative Braking Systems
Authors:- Yash Bhavsar, Mahaveer Jat, Mrs. Hiral Sonkar, Dr. D. M. Patel

Abstract- Most brakes commonly use friction between two surfaces pressed together to convert the kinetic energy of the moving object into heat, though other methods of energy conversion may be employed as all the energy here is being distributed in the form of heat. Regenerative braking converts much of the energy to electrical energy, which maybe stored for later use. Driving an automobile involves many braking events, due to which higher energy losses takesplace, with greater potential savings. With buses, taxis, delivery vans and so on there is even more potential for economy. As we know that the regenerative braking, the efficiency is improved as it results in an increase in energyoutput for a given energy input to a vehicle. The amount of work done by the engine of the vehicle is reduced, in turnreducing the amount of energy required to drive the vehicle. The objective of our project is to study this new type of braking system that can recollect much of the car’s kinetic energy and convert it into electrical energy or mechanical energy. We are also going to make a working model of regenerative braking to illustrate the process of conversion ofenergy fromoneformto another. Regenerative braking converts afraction amount of total kinetic energy intomechanical or electrical energy but with further study and research in near future it can play a vital role in saving thenon-renewable sources of energy.

Literature Survey on IOT and Machine Learning Based Disease Predictor
Authors:- Charmi Zala

Abstract- The world is moving with a fast speed and in Order to keep up ourselves with the whole world we tend to ignore the symptoms of disease which can affect our health at a large extent. Healthcare is one of the important parts for each human being in the world. Health care is given extreme importance with conspicuous novel corona virus. Spreading of disease such as Covid19 has become a global pandemic due to fast spreading of virus in all the countries. Knowing the current situation Internet of Things (IoT) with machine learning will help a lot in serving the best to healthcare and saving many lives around us. Predicting disease according to the symptoms can reduce unnecessary rush to the hospital. This could help to treat the patient early and save many lives getting affected by different disease and virus. As it is rightly said “prevention is better than cure” so predicting disease can help to prevent the occurrence of disease. The Internet of Things (IoT) is very helpful as it can work with real time data as well as the past data that was recorded earlier. This IoT sends data through Wireless Sensor Network (WSN) to the computational devices so that the result can be generated. Machine learning with help of different prediction algorithm such as Decision tree, Naive Bayes etc can help to predict the disease fast and accurate. IOT and Machine Learning are on trend in medical field as it helps both patient and the doctor. Early prediction leads to save time, cost and prevent humans getting affected by diseases.

IOT Based Disinfection and Sterilization using Temperature and Humidity
Authors:- Asst. Prof. M. Nalina Sangaviya, S. Lakshmanan, M. Pavithra, G. Sasireka, G.Vahini

Abstract- The Project is developed based on the Guideline for Disinfection and Sterilization in Healthcare Facilities, University of North Carolina Health Care System. extrapolates quantitative data for ozone virucidal activity on the basis of the available scientific literature data for a safe and effective use of ozone in the appropriate cases and to explore the safety measures developed under the stimulus of the current emergency situation. Ozone is a powerful oxidant reacting with organic molecules, and therefore has bactericidal, virucidal, and fungicidal actions. At the same time it is a toxic substance, having abverse effects on health and safety. Instead of Ozone system ,here we are proposed Temperature and Humidity based Disinfection and Sterilization system. Proposed system maintaining 37OC and 85% of Relative humidity at Disinfection and Sterilization area. Its use is being proposed for the disinfection of workplaces, public places with particular reference to the COVID-19 pandemic outbreak. Water mist is generated by Ultrasonic based mist maker and Temperature of the room is increased by heater attached with proposed system. It should be injected into the room that is to be disinfected until the desired Humidity and Temperature concentration is reached. After the time needed for the disinfection, its concentrations must be reduced to the levels required for the public safety. Here we are using Node MCU Esp8266 module to transfer status of the system to remote location. Electromagnetic relay is used to turn on and off the Ultrasonic humidifier and Heater.16*2 LCD display is used to display the notification to user side. The developed system improves the reliability and stability of Disinfection and Sterilization.

Testing of Alternative Material for Production of Excavator Bucket Teeth from Scrap using Traditional Methods
Authors:- Sir Elkhatim Mohammed Jumaa Abou Zeid, Izeldin Ahmed Abdalla Babikir, M. I. Shukri

Abstract- Failure of the excavator bucket teeth is commonly overcome either by replacing with a new one which is too expensive or by welding the failure parts with metal that sometimes may have different properties from the original one, which may lead to imbalance cases. This study was conducted to test the modified welding method by fabricating alternative bucket teeth from available engine block scrap, using a sand casting process in a traditional foundry, operated by engine waste oil. The quality and properties of the two bucket teeth (Failure (F) and the Alternative (fabricated from scrap) (A)) were tested under laboratory and field measurements. Type of tests includes hardness, chemical composition, heat treatment, microstructure and field failure rate which had resulted in improving some of its mechanical properties such as hardness and wear resistance after practical application and comparison of the two samples in the study field which was tested after (2232 hrs for the failure) and (2016 hrs for the alternative) after 13 months each. According to the experimental results obtained from laboratory examinations and field measurements, the new alternative product has better properties than the failed one.

Bus Ticket Automation with T Money Card
Authors:- M. Ananthi, M. Gowsalya, S. Pavithra, B. Vaishnavi, AP/CSE P. S. Velvizhi

Abstract- These days the public transportation framework like the metro are all around cutting edge. Traveler wellbeing, accommodation and the need to improve the exhibition of existing public transportation is driving interest for shrewd transportation framework on the lookout. The venture based ticket framework for gathering the transport discovered to be a wellspring of major monetary misfortune. It is hard to guarantee the acquisition of ticket by every single traveler .A paper ticket gets pointless to the travelers when the objective is reached. Indeed, even the check of numerous unsold tickets each day is exceptionally high. In the period of innovation, India should zero in on instilling a robotized framework for gathering transport toll. Consequently, this undertaking proposes a computerized card driven framework utilizing Smart Card and GPS Tracking for transport ventures with the assistance of various stages like web, android, IOT. Various situations concerning the execution of this framework here.

Analysis of Energy Management by Using IOT
Authors:- Manmay Banerjee, Amandeep Dhiman, Prateek Shrivastava, Asst. Prof. Rehana Perveen

Abstract- In present scenario the energy is used at a wide range by all our appliances as well as in our industries the energy consumption is getting higher day by day. Therefore, the energy management done by “EMS” Energy management system to reduce energy consumption by using of smart technology and metering, control system in industries. By using of industry automation and PLC, MATLAB, SCADA controlling system we can interface the energy efficient system. The various opportunities are to control interconnected devices by a pre designed scenario human machine interfacing system is a big achievement in IOT. To support the digital transformation of enterprises and help in energy management the transparency is increases by using latest devices due to the need of systematic improvement and increasing the efficiency we used an industrial automation device and hence they consume less amount of energy. The operational cost is higher in any manufacturing and developing industry and it is also responsible for energy consumption, industrial sector is more uses of energy other than any sector it consumes 54% of the global delivered electricity and in addition, non-energy-intensive manufacturing such as pharmaceuticals and energy-intensive-manufacturing are posed make up 70% of the estimated 228 trillion gross output by 2040. So basically, regardless of energy cost fluctuations and an oil prices, the industrial sector is and will continue to be one of the largest contributors of electricity use.

Bank Locker System Using IOT Concept
Authors:- Saifali Shaikh, Rani Jawale, Rushikesh Kandalkar, Onkar Shinde,Prof. Ganesh Kakade,
Prof.Shrikant Dhamdhere(HOD)

Abstract- The main aim of this project is to develop a device for the bank locker security purpose for alerting theft and to auto arrest the thief in bank itself from centralized monitoring unit and control system using IOT technologies. Even the latest technology such as fingerprint sensor lock can be unlocked with ease. So to overcome this problem , this project suggest the use of Internet of Things(IoT) to provide secure enter only to authorized person. For this we are using Raspberry Pi for capturing image, processing it and then sending it via mail to the user’s email account. The Raspberry Pi captures the image when a person tries to enter the bank locker and then process it and sends it to the user’s email account as picture message. The user can then provide authorization to the Raspberry Pi from his/her email account whether to open or remain it shut.

Word Analysis of Friction Stir Spot Weldments Characteristics Using Different Tools Materials and Shape for Similar and Dissimilar Metals
Authors:- Asst. Prof. Attalique Rabbani, Mohd. Zeeshan, Mohammed Salahuddin, Shaik Amjad

Abstract- Efforts to reduce vehicle weight and improve safety performance have resulted in increased application of light-weight aluminium alloys and a recent focus on the weldability of these alloys. Friction stir spot welding (FSSW) is a solid state welding technique (derivative from friction stir welding (FSW), which was developed as a novel method for joining aluminium alloys). During FSSW, the frictional heat generated at the tool-workpiece interface softens the surrounding material, and the rotating and moving pin causes material flow. The forging pressure and mixing of the plasticized material result in the formation of a solid bond region. The present work investigated the effect Aluminium, Brass and Copper alloy plates are joined by friction stir Spot welding (FSSW) by using EN31 and EN19 Tool material with Circular, Taper thread, Square and Diamond Profile Tools. Profiles with varying welding parameters like with a Rotational speed of RPM, Feed and depth of cut, inclinational angle of the tool.All welded samples are observed by followed by their tensile tests. Mechanical strength of the base material with comparable elongation is achieved in FSSW sample rotation speed and welding speed. Material flow during FSSW using a step spiral pin was studied by decomposing the welding process and examining dissimilar alloys spot welds which allowed a visualization of material flow based on their differing etching characteristics. The movement of upper and bottom sheet material, and their mixing during FSSW were observed.

Secure Data Storage Design for Biomedical Compliance Environments

Authors: Nadeesha Perera, Tharindu Silva, Ishara Fernando, Chamika Weerasinghe

Abstract: Secure data storage in biomedical environments is a foundational requirement for maintaining regulatory compliance, safeguarding patient privacy, and enabling ethical scientific research. As healthcare and life sciences organizations generate and manage vast amounts of sensitive information ranging from electronic health records to genomic sequences the need for secure, resilient, and policy-driven storage architectures has become increasingly urgent. This review examines the technical, regulatory, and operational considerations involved in designing storage systems that align with frameworks such as HIPAA, GDPR, and FDA 21 CFR Part 11. The paper begins by analyzing the classification of protected health information (PHI) and the importance of data sensitivity in biomedical workflows. It explores regulatory mandates related to auditability, legal retention, and chain-of-custody, followed by a detailed examination of the evolving threat landscape, including ransomware and insider attacks. The review compares traditional SAN/NAS models, object-based architectures, and software-defined storage solutions, highlighting their respective roles in compliance-driven deployments. Further sections address critical security practices such as encryption, key management, access control, and data lifecycle enforcement. The integration of secure storage with biomedical systems like PACS, LIMS, and EHRs is evaluated, with attention to secure APIs and auditability. Emerging technologies including confidential computing, blockchain-based integrity tracking, and AI-driven anomaly detection are also explored for their future impact. Through real-world case studies, the review illustrates successful implementations in hospitals, research institutions, and hybrid infrastructures. It concludes with an analysis of common challenges such as vendor lock-in and the trade-offs between compliance and usability. Looking ahead, the paper advocates for zero trust-aligned architectures and adaptive compliance automation as guiding principles for next-generation biomedical storage design.

DOI: https://doi.org/10.5281/zenodo.15847131

Towards Autonomous Wireless Cloud–IoT Systems: Architecture And Risk Perspectives

Authors: Pranita Lohani

Abstract: The rapid growth of Internet of Things (IoT) devices and the increasing reliance on cloud computing have driven the need for autonomous wireless Cloud–IoT systems capable of supporting large-scale, real-time applications. These systems integrate heterogeneous devices, sensors, and networks with cloud-based platforms to enable seamless data collection, processing, and decision-making without significant human intervention. The architecture of such systems typically involves layered structures, including edge computing, fog nodes, and centralized cloud services, to optimize performance, reduce latency, and enhance scalability. Despite these benefits, the deployment of autonomous Cloud–IoT systems introduces substantial risks, particularly in terms of cybersecurity, data privacy, and system reliability. Vulnerabilities in communication protocols, improper access controls, and potential failures in autonomous decision-making mechanisms pose significant challenges. To address these concerns, robust risk assessment frameworks, adaptive security mechanisms, and fault-tolerant architectural designs are essential. Moreover, ensuring interoperability among diverse devices and standards while maintaining energy efficiency further complicates system design. This study explores the architectural models and operational strategies of autonomous wireless Cloud–IoT systems, emphasizing both their functional advantages and potential threats. It examines current methodologies for risk identification, mitigation, and continuous monitoring to achieve resilient and secure operation. By providing a comprehensive perspective on architecture and risk, this work aims to guide the development of reliable, scalable, and secure autonomous Cloud–IoT systems capable of supporting emerging applications in smart cities, healthcare, industrial automation, and environmental monitoring.

DOI: http://doi.org/10.5281/zenodo.18162732

Continuous Risk Scoring In SAP ERP Through Autonomous Learning Algorithms

Authors: Yuvraj Deshmora

Abstract: Enterprise Resource Planning systems, particularly SAP ERP, have become critical tools for organizations seeking to streamline operations, integrate business processes, and manage risks effectively. Traditional risk management approaches in SAP ERP often rely on periodic assessments, static risk scoring, and manual intervention, which may fail to capture emerging threats or changes in operational environments. Continuous risk scoring powered by autonomous learning algorithms offers a transformative approach, enabling real-time identification, evaluation, and mitigation of risks across various business processes. By leveraging machine learning, deep learning, and adaptive algorithms, organizations can continuously analyze transactional, master, and operational data to detect anomalies, predict potential failures, and proactively respond to emerging threats. This review examines the current state of continuous risk scoring in SAP ERP, highlighting the capabilities of autonomous learning algorithms, data integration challenges, practical applications, and potential limitations. Case studies and literature indicate that organizations adopting autonomous risk scoring benefit from improved decision-making, reduced manual oversight, and enhanced compliance with regulatory standards. Furthermore, continuous risk assessment supports proactive management strategies by providing dynamic insights into operational, financial, and compliance risks. The review also identifies future directions, including the incorporation of explainable AI for interpretability, integration with cloud-based SAP systems, and the use of reinforcement learning to enhance predictive accuracy. The findings suggest that continuous risk scoring is not only a technological advancement but also a strategic necessity for organizations aiming to maintain resilience and agility in a rapidly changing business environment. By synthesizing current research and practical implementations, this review provides a comprehensive understanding of how autonomous learning algorithms can revolutionize risk management in SAP ERP. It concludes with recommendations for future research and practical adoption strategies to maximize the benefits of continuous risk scoring.

DOI: http://doi.org/10.5281/zenodo.18162741

AI-Augmented Software Quality Engineering: Data-Driven Risk, Prediction, And Continuous Assurance In Modern Software Systems

Authors: Ramani Teegala

Abstract: By April 2021, software quality engineering was under increasing pressure from the combined effects of accelerated release cadences, widespread adoption of microservices, and the operational realities of cloud-native deployments. Banking and other regulated industries faced a particularly acute version of this tension: delivery speed had become a competitive requirement, yet failures carried outsized consequences in customer harm, financial loss, and regulatory exposure. In this context, conventional quality practices such as manual test authoring, rule-based static analysis, and human-driven code review remained necessary but frequently insufficient to scale with system complexity. The problem was not that these practices were ineffective in principle, but that they depended heavily on human attention and stable system boundaries, both of which were increasingly scarce in modern delivery pipelines. AI-augmented software quality refers to the application of machine learning and statistical techniques to improve the effectiveness, coverage, and timeliness of quality controls across the software lifecycle. Unlike general automation, which executes predefined checks, AI-augmentation aims to learn from historical artifacts such as defects, test outcomes, telemetry, and code change patterns in order to anticipate risk and prioritize interventions. By 2021, the software engineering community had accumulated substantial research and industry experience in areas such as defect prediction, anomaly detection in operational metrics, automated test prioritization, and mining software repositories. These approaches did not eliminate the need for engineering judgment or rigorous testing, but they offered a way to focus limited quality effort on the changes, components, and execution paths most likely to fail.Within regulated domains, AI-augmentation for quality must be evaluated through constraints that are distinct from those of consumer software. Quality signals and decisions often need to be explainable, auditable, and reproducible, especially when they influence production readiness, control effectiveness, or incident management. Data used for training and inference can include sensitive operational and development artifacts, requiring governance controls comparable to those used for security and compliance data. Moreover, quality failures in financial systems tend to cluster around concurrency, distributed consistency, configuration drift, and integration boundaries, meaning that a quality system must reason not only about code-level correctness but also about system-level behavior under partial failure. AI methods applied without regard to these constraints risk producing brittle signals that cannot be operationalized, trusted, or defended during audit and post-incident review. This paper examines AI-augmented software quality as understood and practiced by April 2021, with particular attention to how such techniques integrate into modern delivery pipelines and operational feedback loops. It synthesizes research in software analytics, defect prediction, test optimization, and anomaly detection, and it situates these methods within the architectural trends that shaped software systems from 2000 through 2021. The paper proposes a conceptual model in which AI-driven signals complement, rather than replace, established quality controls, and it describes a layered architecture that connects development artifacts, CI/CD execution data, and production telemetry into a cohesive quality intelligence capability. Special attention is given to the interactions between AI-generated quality signals and governance requirements common in regulated environments, including traceability, change control, and evidence preservation. The analysis further explores the practical trade-offs associated with AI-augmented quality, including data quality and labeling challenges, feedback delays, model drift under frequent system change, and the risk of embedding organizational biases into automated decision-making. It evaluates these challenges alongside potential benefits such as earlier risk detection, more efficient test allocation, and improved incident prevention. By framing AI-augmentation as an engineering discipline grounded in measurable outcomes and controlled deployment practices, the paper aims to provide a historically accurate and technically rigorous account of how machine learning techniques can strengthen software quality programs as of April 2021, without relying on later generative AI developments or post-2021 tooling assumptions.

DOI: https://doi.org/10.5281/zenodo.19100296

AI-Powered Network Observability Systems

Authors: Dmitry Kuznetsov

Abstract: The escalating complexity of modern network infrastructures, characterized by the convergence of multi-cloud environments, microservices, and massive IoT deployments, has pushed traditional network monitoring beyond its structural limits. Traditional monitoring, which relies on static thresholds and reactive alerting, fails to provide the deep "internal state" visibility required for modern digital resilience. This review examines the paradigm shift toward AI-powered network observability systems. Unlike traditional monitoring, observability leverages high-cardinality telemetry data—including logs, metrics, and traces—to enable the "Unknown-Unknown" discovery of system behaviors. By integrating Artificial Intelligence (AI) and Machine Learning (ML), these systems transition from simple data aggregation to "Cognitive Insight" engines. We categorize the core methodologies of AI-driven observability, including the use of unsupervised learning for real-time anomaly detection, Graph Neural Networks (GNNs) for mapping relational topologies, and Natural Language Processing (NLP) for parsing unstructured log telemetry. This article explores how these systems automate Root Cause Analysis (RCA) and enable "Self-Healing" network architectures. Furthermore, the review addresses critical challenges, such as the "Data Silo" problem, the computational overhead of real-time inference at the network edge, and the necessity for Explainable AI (XAI) to foster operator trust. By synthesizing recent breakthroughs in Deep Learning and AIOps, this paper provides a strategic roadmap for building "Autonomous Observability" frameworks. The findings suggest that AI-powered observability is the foundational technology required to manage the invisible complexity of the 6G and hyper-connected era, ensuring that network operations move from reactive troubleshooting to proactive, foresight-driven optimization.

DOI: https://doi.org/10.5281/zenodo.19492433

Machine Learning For Network Anomaly Detection In High-Speed Networks

Authors: Andi Pratama

Abstract: The unprecedented escalation in global data traffic, driven by 5G expansion, hyperscale cloud computing, and the Internet of Things (IoT), has fundamentally altered the threat landscape for high-speed networks. Traditional Network Intrusion Detection Systems (NIDS) that rely on manual signature matching or basic statistical thresholds are increasingly incapable of processing traffic at terabit-per-second scales, leading to significant visibility gaps. This review examines the paradigm shift toward Machine Learning (ML)-based anomaly detection as a solution to the "data deluge" in high-speed environments. By focusing on flow-level metadata and statistical behavioral patterns rather than computationally expensive deep packet inspection (DPI), ML models can identify malicious intent within microseconds. We categorize current methodologies, ranging from unsupervised clustering for zero-day discovery to deep learning architectures like Convolutional Neural Networks (CNNs) for spatial traffic analysis and Long Short-Term Memory (LSTM) networks for temporal sequence modeling. This article explores how these models mitigate "alert fatigue" by providing high-precision filtering of benign noise while identifying subtle "low and slow" adversarial tactics. Furthermore, the review addresses the critical challenges of real-time inference at the network edge, the necessity for model quantization to fit within limited hardware buffers, and the emerging risk of adversarial machine learning. By synthesizing recent academic breakthroughs and industrial implementations, this paper provides a strategic roadmap for building "Cognitive Defense" systems. The findings suggest that ML-integrated anomaly detection is the only viable mechanism for maintaining network resilience and integrity in an increasingly automated and high-velocity digital ecosystem.

DOI: https://doi.org/10.5281/zenodo.19492447

Next-Generation Modular Java Architecture For Scalable And Reliable Enterprise Systems

Authors: Dr. Alexander Hughes, Olivia Bennett, Dr. Christopher Nolan, Ethan Walker, Dr. Amelia Clarke, Chaitanya Srinivas

Abstract: The increasing complexity of enterprise applications and the demand for scalability, reliability, and maintainability have driven the need for advanced architectural approaches in software development. This research presents a next-generation modular Java architecture designed to support scalable and highly reliable enterprise systems. The proposed approach emphasizes the decomposition of applications into loosely coupled, independently deployable modules, enabling improved flexibility, fault isolation, and ease of maintenance. By leveraging modern Java frameworks and design principles such as dependency injection, microservices alignment, and service-oriented architecture, the framework enhances system resilience and adaptability to changing business requirements. The architecture incorporates robust error-handling mechanisms, efficient resource management, and scalable deployment strategies to ensure consistent performance under varying workloads. Additionally, it supports seamless integration with cloud-native environments, enabling dynamic scaling and high availability. Experimental evaluation demonstrates that the proposed modular architecture significantly improves system reliability, reduces downtime, and enhances development productivity compared to traditional monolithic systems. The findings highlight the effectiveness of modular design principles in building next-generation enterprise applications that are both scalable and resilient in distributed computing environments.

DOI: https://doi.org/10.5281/zenodo.19763460

A Unified Hybrid Persistence Framework For High-Performance Data Systems Using Redis, MongoDB, And PostgreSQL

Authors: Dr. James Anderson, Emily Carter, Dr. Michael Thompson, Daniel Roberts, Dr. Sophia Williams, Chaitanya Srinivas

Abstract: The rapid growth of data-intensive applications has necessitated the adoption of diverse data storage technologies to meet evolving performance, scalability, and reliability requirements. Traditional single-database approaches often fail to address the heterogeneous data needs of modern systems, leading to inefficiencies in data management and processing. This research proposes a unified hybrid persistence framework that integrates in-memory, NoSQL, and relational databases—specifically Redis, MongoDB, and PostgreSQL—to optimize data storage and retrieval strategies in high-performance environments. The framework leverages Redis for low-latency caching and real-time data access, MongoDB for flexible schema design and efficient handling of semi-structured data, and PostgreSQL for strong transactional integrity and advanced querying capabilities. By combining these systems within a cohesive architecture, the proposed approach enables intelligent data tiering, workload distribution, and consistency management. Furthermore, the study introduces adaptive data routing and synchronization mechanisms to ensure seamless interoperability across multiple persistence layers. Experimental evaluation indicates that the proposed framework significantly improves system throughput, reduces query response time, and enhances scalability compared to traditional monolithic database solutions. Additionally, it strengthens fault tolerance and supports dynamic scaling in distributed environments, making it highly suitable for modern cloud-native and enterprise-scale applications.

DOI: https://doi.org/10.5281/zenodo.19763840

Architecture-Led Escalation Engineering For Stabilizing Enterprise Collaboration Platforms: An Evidence-Based Study On Zimbra Backend Ownership

Authors: Dr. Jonathan Clarke, Emily Dawson, Michael Bennett, Sophie Reynolds, Daniel Foster, Jeji Krishnan

Abstract: Enterprise collaboration platforms such as Zimbra operate in highly distributed and mission-critical environments where system stability and rapid incident resolution are essential for uninterrupted communication. Traditional escalation mechanisms often rely on generic operational workflows that lack alignment with underlying system architecture, leading to delays in diagnosis and resolution of critical issues. This paper proposes an architecture-led escalation engineering framework that integrates deep architectural knowledge with incident management processes to improve system reliability and operational efficiency. The approach emphasizes backend ownership, where each core component—such as Mail Transfer Agents (MTA), mailbox servers, LDAP directory services, and proxy layers—is assigned to dedicated experts responsible for performance, troubleshooting, and continuous optimization. Through evidence-based analysis of real-world Zimbra deployments, the study demonstrates how mapping system architecture to escalation paths enables faster root cause identification, reduces mean time to resolution (MTTR), and enhances cross-team collaboration. The framework also incorporates proactive monitoring, architecture-aware diagnostics, and structured escalation workflows to minimize downtime and prevent recurring incidents. Results indicate that organizations adopting this model achieve improved system stability, stronger accountability, and more efficient incident handling. This research contributes a scalable and practical strategy for stabilizing enterprise collaboration platforms by bridging the gap between system design and operational response.

DOI: http://doi.org/10.5281/zenodo.20157620

Light Propagation Through a Turbulent Cloud: Comparison of Measured and Computed Extinction

Authors: Sk Samsul Hoda, Dr. Vipin kumar

Abstract: Remote sensing techniques used for measurement of atmospheric cloud properties operate under the notion that light extinction caused by scattering and absorption is exponential due to Beer-Lambert law. This is expected to be valid for a uni-form medium with no spatial correlations between particle position. The aim of this research was to show that under turbulent conditions, cloud droplets cannot be inter-preted as non-correlated, and in turn will exhibit a lower than exponential light decay from scattering. The research took place at the MTU π-Chamber laboratory. A tem-perature difference between the floor and ceiling of the chamber was applied to create convection- driven turbulence. When turbulent cloud conditions were achieved, it’s optical depth properties was analyzed. This was done by deriving the optical depth by computational means through the acquisition of its droplet size distribution, and processing it through Mie scattering theory, while simultaneously acquiring direct measurement of optical depth using a Laser-Hygrometer. Results showed that there is a trend where larger temperature differences inside the chamber caused the direct extinction of light to deviate more strongly from the computed extinction. This less then exponential extinction parameter allows us to understand the significant effect that a turbulent cloud cover has on radar and satellite signals.

DOI: http://doi.org/10.5281/zenodo.20269814

Smart Vending Machine System Using Iot

Authors: Prof .P.V. Nimbalkar, S. D. Magar, P. S. Nimbalkar, N. D. Chormal

Abstract: This paper presents the design and implementation of a Smart Vending Machine System using Internet of Things (IoT) technology for automated dispensing of ready-made food items. The main objective of the proposed system is to provide a contactless, efficient, and user-friendly vending solution that reduces human intervention and waiting time. The system is built using an Arduino UNO microcontroller integrated with a Wi-Fi module to enable real-time monitoring and control. A QR code–based cashless payment mechanism is incorporated to enhance convenience and security. Once the payment is successfully verified, the controller activates the dispensing mechanism through a motor driver to deliver the selected food item automatically. The developed prototype was tested under different operating conditions and demonstrated reliable performance with accurate item delivery and quick response time. The proposed IoT-based vending machine system is cost-effective, scalable, and suitable for deployment in public places such as colleges, offices, and railway stations. Future enhancements can include mobile application integration and advanced inventory management for improved automation.

DOI: http://doi.org/10.5281/zenodo.20279899

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Google Scholar Journals

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Know the Process of Selecting Compatible Google Scholar Journals

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Finding the right journal from the Google scholar journal list is not an easy task. Only a genuine and appropriate audience can understand the importance of your research. But many researchers get depressed and finally publish a paper in any journal in lieu to get at least their paper to publish but this is a wrong strategy. Due to their particular act, they lose the impact that their research would lose. IJSRET would like to mention some important parameters that every researcher should check in a journal before he wishes to publish their paper there.

Stay Away from Predators and Advertisements 

These days as the researchers are more and more eager to publish their papers many journals are taking advantage of their condition and taking high charges from them for publishing their work. You have to stay away from them as they would try to contact you or advertise their services on the internet. It is very easy to start a journal and it just needs a domain, a registration and a well-built impressive website to attract the researchers. You should stay away from all such journals and find quality Google Scholar Journals.

Never get confused with Impact Factor of any Journal

Many researchers often get impressed by knowing the impact factor of any journal. By this, they measure the prestige of any journal and wish to publish their paper in such journals. You should also know the fact that the impact of any journal is different for different areas of study. For example, a journal having an excellent impact on electronics research but can have an average or poor impact in the medical domain. So you should check that the journal that you have selected has a high impact factor in that particular area in which your research lies. These were some of the common ways to determine good Google Scholar Journals.

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Journal of Advanced Scientific Research

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A Guide to How to Select the best journal of advanced scientific research

It is a difficult task to select a journal of advanced scientific research after a researcher has completed his laborious work. The process is complex because one has to seek such a journal that matches his domain of work. One should also check the expectation level of the journal before submitting also. IJSRET would like to guide such researchers in selecting a suitable journal-

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Tips to Select journal of advanced scientific research

# Make a List of Available journals

It is necessary to develop some knowledge about the journals available as per your requirement or that lies in your research area. You can consult your friends, colleagues, or professor for this or can browse through the internet.

# Know the Journal Impact

The rank of the journal and its readers play an important role in determining the impact of any journal. Submitting your paper in a low-impact journal will degrade the quality of your research and your work will not be visible to the audience that you wished for. Visiting the website of your selected journal will provide you with such information about the journal.

# A Journal Should Match your need

The subject area which the journal covers is also one of the important factors that one should look for. This helps in finding suitable readers who will admire your work. Also, you should check their editorial policies and the practices which the journal follows along with their reviewing process and the time they take for publication. For this, you have to check the instructions that they give to authors and it is present in nearly all the journals on their website.

After you have completely satisfied with any journal of advanced scientific research, you can proceed further with the publication process.

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Journal of Materials Science

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Importance of Journal of Material Science 

Scholars working in the field of material science really work hard, as preparing samples is a tough task. Chemical composition of different materials for specific product requirement is a deep study of science.  We would like to share some of the advantages of choosing this field to make the researchers realize this unique and trending field. As the name suggests it is the study of properties of material and knowing its boundaries in different environmental conditions so that one can profitably use such products in day-to-day application.

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Advantages of Choosing Material Science as a Subject

  • It is an interesting area of study and also contains multiple disciplines within it
  • There is a lot of potential in this area as per job and career is concerned
  • Researching in the material science field will lead to better career growth and chances to settle abroad.

Material science is all about knowing the property of the material or creating new material from the current to help in the advancement of science. Industries these days are falling short of researchers of material science and often look for a capable researcher who helps them by providing them with advanced knowledge. There are many sub-branches of material science in which one can proceed with the research. For example materials in electronics where one can proceed to study the behavior of silicon chips, transistors, etc, and manipulate the materials to make their products better. In short, the subject is best in itself and no one can deny this.

 IJSRET is one of the best journals of materials science in which researchers can easily publish their work without any problems as we provide fast and reliable service to our customers.

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Peer Reviewed Journal List

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IJSRET is one of the leading journals in peer reviewed journals list in India. It accepts work from several engineering scholars, researchers, lecturers, and subject experts. Journal provides both free and paid publication process on several subjects such as civil, mechanical, electronics, machine learning, etc. Through the journal, authors can maximize the chance to get their work read by the new audience in the entire world.

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Advantages of Publishing in peer reviewed journal:

  • It is a good way to get your work checked by experts so that you will get aware of the validity of your work.
  • It also provides you with feedback reports by which you can learn about the improvement that can be done on the research paper before publication.
  • Sometimes there is a multi-level of peer reviews that give their expert reviews in some of the peer reviewed journals list in India, which is further better to improve the quality of the paper.
  • Majority of researchers voluntary likes to publish their work in such peer reviewed journal to authenticate their work.

Apart from the advantages, there are some disadvantages with such peer-review process such as-

  • It causes a delay in collecting the shreds of evidence related to research to authenticate a paper
  • It is a time-consuming process and causes a delay in the publication of any research paper.
  • It is not 100% effective as several journals have a low standard of the peer review process and they can publish a low-quality paper by mistake.

Many journals often charge more money just for the reason they had a peer review committee.

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IJSRET Editorial Board Member Dr. Jeyalakshmi Poornalingam

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Dr. Jeyalakshmi Poornalingam

Affiliation Assistant Professor of English, V.O.C. Agricultural College and Research Institute, Tamil Nadu Agricultural University, Killikulam, Vallanad, India
Email-Id: poornalingamjeyalakshmi@gmail.com
Publication:

Books:

  • Humanism: Amitav Ghosh. Chennai, India: Emerald Publications, 2015.
  • Time and Space: Amitav Ghosh. Chennai, India: Emerald Publications, 2014.
  • A Call for Student Centred Syllabus: A discrepancy Model of Investigation and
    Syllabus Designing Chennai, India: Emerald, 2014.

Papers:

  • Poornalingam, J. (2023). Assessing language acquisition behavioral patterns in adults. The Literary Herald, 9(3).

  • Elenchezhian, T., Senthilnathan, S., Kalirajan, V., Jeyalakshmi, P., Rajendran, T., Prahadeeswaran, M., Kiruthika, N., Parimalarangan, R., & Karthick, V. (2023). A study on income, expenditure and resource use pattern of paddy in Tiruvannamalai district. International Journal of Plant and Soil Science.

  • Elenchezhian, T., Senthilnathan, S., Kalirajan, V., Jeyalakshmi, P., Rajendran, T., Kiruthika, N., Prahadeeswaran, M., Karthick, V., & Parimalarangan, R. (2023). Estimation of income, expenditure and resource use pattern of groundnut in Thandrampattu block of Tiruvannamalai district. Journal of Experimental Agriculture International.

  • Elenchezhian, T., Senthilnathan, S., Rajendran, T., Kalirajan, V., Jeyalakshmi, P., Kiruthika, N., Prahadeeswaran, M., Parimalarangan, R., & Karthick, V. (2023). Analysis of income, expenditure and resource use pattern of sugarcane in Tamil Nadu. Journal of Experimental Agriculture International.

  • Senthilnathan, S., Elenchezhian, T., Mathiyazhini, M., Ravishankar, M., Aliya, S., Aravindrajan, S., Ranjith, P. J., Jeyalakshmi, P., Kiruthika, N., Parimalarangan, R., Karthick, V., & Rajendran, T. (2023). Growth performance of groundnut in India—An instability and decomposition analysis. Asian Journal of Agricultural Extension, Economics & Sociology, 41(12), 350–356.

  • Elenchezhian, T., Senthilnathan, S., Kalirajan, V., Jeyalakshmi, P., Rajendran, T., & Kiruthika, N. (2023). Area, production and productivity of rice in the world, India, and Tamil Nadu. Agrigate.

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where can I publish my research paper

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Research publish journals is a medium to get worldwide access to your paper. Your paper will be reviewed by several experts throughout the world. So if you are thinking of where can I publish my research paper for free here are some of the answers to it. Choosing the right journal is important and gives a huge impact on your work. Choosing a journal that is not relevant to your work will fail all your months and years of hard work. Before publishing your paper it is better to follow these steps

  • Get your paper to cross-check by some colleague, friend, or professor to eliminate the typo, grammatical, spellings, and punctuation errors
  • After this revise your paper again according to the comments made by your reviewers
  • Prepare a manuscript according to the chosen journal’s needs and requirement
  • Now if you feel everything is done submit your paper
  • You have to be patient and never panic after you have submitted your journal and are waiting for approval

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where can I publish my research paper?

IJSRET is one of the leading publications Journal and answers the question of where can I publish my research paper in INDIA, they will meet all your requirements. We offer paper publishing services to researchers, scholars, students, etc at a nominal cost. We also solve the queries of our customers as we have 24*7 chat support. Here some of the domain from which we publish the paper-

  • Electronics
  • Computer Science
  • Civil
  • Machine Learning,
  • Nanotechnology
  • Civil
  • Electrical Topics
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Architectural Foundations For AI-Driven Intelligent Automation In Salesforce Ecosystems

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Authors: Santhosh Reddy BasiReddy

Abstract: Enterprise CRM platforms are rapidly evolving from traditional transactional systems into intelligent decision hubs that orchestrate complex, end-to-end business processes across distributed cloud ecosystems. Salesforce increasingly serves as the central backbone for automation, analytics, and system integration inregulated, data-intensive, and high-scale enterprise environments. As artificial intelligence technologies mature and move from experimental use cases to production-grade deployments, organizations face significant architectural and operational challenges in preparing Salesforce ecosystems for AI-driven intelligent automation. These challenges include ensuring scalability, minimizing system coupling, maintaining governance and auditability, and integrating adaptive intelligence without disrupting core business workflows. This work synthesizes architectural, process, and governance principles into a unified framework for preparing Salesforce ecosystems for AI-driven intelligent automation.

DOI: http://doi.org/10.5281/zenodo.18014554

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The Consumer & Retail Investor in the FinTech Era: Opportunities and Risks of Digital Finance

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Authors: Vittal Jadhav

Abstract: The move to reshape the financial services offering has greatly benefited from the appearance of Financial Technology (FinTech), namely for consumers and retail investors. The latest wave of FinTech innovations, which include digital payment solutions, robo-advisory platforms, peer-to-peer (P2P) lending, and blockchain-based services, has drastically changed how individuals interact with money and investments. This paper considers the manifold opportunities that FinTech affords (financial inclusion, efficiency, personalization, and cost-cutting) in contrast to the corresponding risks (cybersecurity, data privacy, regulatory, and market volatility). An overview of the literature on FinTech prior to 2020 is contextualized, and the methodology, which compares case-based data together with qualitative analysis, is used to assess the services. It is supported by figures, flow charts, and comparative tables. Beyond the democratization of FinTech, the results show the power that FinTech offers by way of economic empowerment and the systemic vulnerabilities it creates when it fails. The paper suggests a balanced regulatory playing field alongside best practices for leaders, FinTech providers, and other stakeholders to responsibly tap FinTech’s potential.

DOI: https://doi.org/10.5281/zenodo.16314798

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IJSRET Volume 7 Issue 1,Jan-Feb-2021

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A Review of Intrusion Detection Systems
Authors:- Subhash Waskle, Associate Prof. Avinash Pal

Abstract:- An intrusion detection system (IDS) is devices or software’s that are used to monitors networks for any unkind activities that bridge the normal functionality of systems hence causing some policy violation. This paper reviews some of the intrusion detection systems and software’s highlighting their main classifications and their performance evaluations and measure.

Tapping into Geothermal Technology to Boost Electricity Supply in Nigeria
Authors:- Alabi A.A., Adeleke B.S. , Adekanmbi, A.O., Fawole T.G.

Abstract:- It is no more news that attention of humanity has shifted to the generation of energy through renewable energy sources. This paper is based on how Nigeria can tap into the use of geothermal technology other than other renewable energy sources to generate electricity using of the two available geothermal resources (hydrothermal and petrothermal) in available locations. Through hydrothermal plants the heat received from geothermal resources are converted to electricity. This is a technology that if efficiently utilized, can go a long way to make Nigeria electricity challenge a thing of the past.

Segregating Spammers from Social Digital Platform by Genetic Algorithm
Authors:- Rahul Kumar, Dr. Avinash Sharma

Abstract:- Presence of online Social digital platform in human life from past few decade influence advertiser to place their product in different style. Some of digital marketing companies plays a giant role for promoting a product, service, thought, etc. to social digital users. Digital platform do not want to lose their control so spammer who work professionally to promote a brand need to identify ad remove from the platform. This paper has work in this field of online social spammer detection by developing a unsupervised algorithm which identify the user class (Spammer or real) as per sequential behavior done. Proposed work utilized a intelligent water drop genetic algorithm for segregating the users into desired class. Some of digital platform inherent features of the user profile were used for finding the fitness class of the user to the corresponding class of user. Experimental work was done on real twitter dataset and comparison of proposed model was done with existing method of spammer detection. Results shows that proposed model has increased the accuracy of spammer detection.

An Evaluation of the Role Played By The Head Of School In The Delivery Of Quality Education In Zimbabwean Day Secondary Schools: A Case Study Of Guruve District
Authors:- Laison Jairus Kavumbura

Abstract:- Quality education is a critical phenomenon for the provision of quality human resources in any country. Quality education focuses on learning which strengthens the capacity of children to act progressively on their own behalf through the acquisition of knowledge in useful skills. Quality in terms of school products implies school graduates who are not just literate or numerate, but graduates who add value to their families, communities as well as nation through the knowledge, skills and morals they acquired from the school system. In Zimbabwe the parents, government and employers place a very high premium on the quality of education that schools provide to their learners. Certain schools are shunned because of their perceived low standards and yet others are sought after by many parents and students due to the quality of learning perceived to obtain in them. Quality therefore is about high standards of achievement by pupils in all spheres. Quality does not come about like manna from heaven. It is brought about in an organisation deliberately through the leadership process. This article draws on a quantitative enquiry on the role played by heads in the delivery of quality education in Zimbabwean Secondary schools. The study adopted the descriptive survey design. The target population included all secondary school teachers in Guruve district which has a teacher population of plus minus 18000 teachers. Random sampling was used to arrive at a sample of 200 respondents who were made up of 120 males and 80 females. All the information was collected through a questionnaire which had both close-ended and open-ended questions. Descriptive statistical analysis was used to interpret the data. The study revealed that heads did not encourage attendance by pupils to all lessons, there was inadequate provision of stationary and learning equipment and that supervision of learning was not adequately done by the heads. The study also reveals that heads were not results focused in their operations. The study recommends that heads of schools should be equipped with skills and knowledge in the field of leadership and management so that they promote quality education in their schools. Heads should also prioritise supervision of instruction and provision of adequate teaching/learning materials.

A Glass Fiber Compressive Strength Prediction Using Artificial Intelligence (ANN)
Authors:- Madhav Shrivastav, Prof. Sourabh Dashore

Abstract:- Concrete, being widely used, is the most important building material in civil engineering. Concrete is a highly complex material, which makes modeling its behavior a very difficult task. Many attempts were taken earlier to develop suitable mathematical models for the prediction of compressive strength and flexural strength of different concretes. Those traditional methods have failed to map non-linear behavior of concrete ingredients. The present study has used artificial neural networks (ANN) to predict the compressive strength and flexural strength of glass powder concrete. The ANN model has been developed and validated in this research using experimental strength data of different mixes. The artificial neural networks (ANN) model is constructed trained and tested (in MATLAB. For study models were developed. Strength was modeled in ANN model as a function of input data collected by the experimental result in laboratory. In this study, an attempt was also made to develop a multiple regression model for predicting strength (in EXCEL) as it is being used largely by researches in prediction. Finally, this model was used to predict the strength of concrete for different different days.

A Review of Glaucoma Detection Techniques
Authors:- Arkaja Saxena, Associate Prof. Avinash Pal

Abstract:- Glaucoma is one of the main causes of blindness today. It is basically a group of eye diseases that leads to the optic nerve damage and arises mostly due to the increases in the Intraocular Pressure (IOP) within the eyes. The early detection as well as diagnosis of this disorder is very important as at the later stages it leads to complete loss of vision.In this paper we reviewed different glaucoma detection procedures by digital image processing of fundus of eye. This paper also proposes a very simple method for the screening of glaucoma.

Concept Maps: Let’s Organize Your Speech
Authors:- Nirumala Rothinam, Hadidah Abdul Rahman

Abstract:- This research was to observe the effectiveness of concept maps in enhancing Matriculation students’ speaking ability in terms of organization and content. The specific objective of this research is to identify if concept maps could be an effective educational tool to improve students’ speaking scores according to the Malaysian University English Test (MUET) speaking scoring guideline. Participants of this research consist of 24 one-year Science program students. Data collections were done through pre-test and post-test. Data were analysed using descriptive analysis. Results of the analysis established that all the 24 participants showed an increase in the speaking scores after the intervention using concept maps. The research indicated that concept mapping is effective in supporting the organization of thoughts and content to produce verbal output thus producing a positive correlation between the use of concept maps and scores for participants’ speaking assessment.

A Review of Recommendation Techniques
Authors:- M. Tech. Scholar Pooja Relan, Asst. Prof. Avinash Pal

Abstract:- On the Internet, the place the number about
Decisions may be overwhelming, there will be necessity will filter, prioritize Also effectively convey important data so as on allay those issue of majority of the data overload, which need made an possibility issue will huge numbers Internet user. Recommenders techniques work out this issue by looking through huge volume for rapidly created majority of the data on furnish user with customize content and services. This paper investigates the separate aspects and potentials for distinctive prediction techniques clinched alongside recommendation techniques in place with serve concerning illustration a compass to Scrutinize and act in the field of recommendation techniques.

Digital Social Platform BOT User Detection Features and Techniques
Authors:- M.Tech. Scholar Kritya Gorowara, Asst. Prof. Jayshree Boaddh, Asst. Prof. Jashwant Samar

Abstract:- Digital platforms in these days has its own place as a tool for getting more social. This attract many publisher to push there content to relevant audience. As time and labor were optimize by computer programs, so this posting of content is done by BOTs which are program. Many of social platform schedule some programs which detect those BOT user and remove from the network. This paper has summarized BOT detection techniques proposed by various researchers as per different social media platforms, users. As per type of social media platform features were also change and various common features were list in the paper for increasing the understanding of BOTs in the network. Some of evaluation parameters were also formulize which help to compare different BOT detection algorithms.

A Survey on Digital Image Retrieval Technique and Visual Features
Authors:- M.Tech. Scholar Astha Singh, Asst. Prof. Jayshree Boaddh, Asst. Prof. Jashwant Samar

Abstract:- Digital platform based services increases content on servers and retrieval of relevant information depends on data matching algorithms. Out of different type of data image plays an crucial role for various document proof, study, analysis, diagnosis. Hence retrieval of relevant image as per requirement is very important. This paper has summarized various image retrieval techniques proposed by authors for reducing the execution time and improving the relevance of the indexed image as per user query. Paper has list image features used by different scholars for finding the visual similarity between images. Content based image retrieval was done by two type of query first was visual and other was text, paper has list all type of retrieval techniques.

Variables Influencing Food Wastage and Rapid Composting Techniques of Food Waste in Malaysia
Authors:- Nurafiqah Izzati Zafriakma, Faeiza Buyong

Abstract:- – Rapid generation of food waste has become a major concern in municipal solid waste management (MSW) in Malaysia that are practically poor and unstructured. Food waste has significant adverse effects on food security, the environment and the economy, making it a significant problem that needs critical response. The current method in disposing of the waste in a landfill negatively impact human being and environmental safety. Food waste is a material produced when food is purchased, prepared and consumed. Based on the previous studies, it was found that there were variables that influence the number of food waste produced from each individual. Meanwhile, the current treatments used to treat food waste is time-consuming and unable to cope with the amount of incoming waste generated daily. Therefore, this study intended to identify the factors that influence the generation of food waste in Malaysia with the aim of analysing methods to reduce the amount of current or future food waste produced by rapid reduction techniques of composting.

Melanoma classification on Dermoscopy images using Transfer learning with CNN architectures
Authors:- Aaron Hill, Robert Collins, Joseph Morgan

Abstract:- Incidence rate of malignant melanoma has increased from the past two decades but the mortality that comes with it has stabilized. Early detection of melanoma was critical in the past as we do not have effective therapies and detection methodologies. State of the art classifiers based on CNNs are proved efficient to classify images of skin cancer more better than dermatologists and has provided more effective lifesavingdiagnosis, as now a days skin cancers can be detected in early stages. In this paper we will talk about classification of skin cancer using convolutional neural networks and transfer learning. We looked out for papers in Google scholar, PubMed, Google Scholar, Research Gate, Web of Science databases for original research papers and review papers. The papers that has sufficient reports with proofs has been taken into consideration.

Speech Recognition
Authors:- Bhuvan Taneja, Jones C J, Rohan Tanwar

Abstract:-Speech is a simple and effort less approach of communication amongst humans, but in this day and age humans are not restricted to connecting to one another but even to the various machines in their lives. The most essential being the computer. So, this communication approach or technique can be used for connecting humans and computers. This inter play is done by interfaces, this area being titled the Human Computer Interaction (HCI). The following paper gives an general outline of the principal meaning of Automatic Speech Recognition (ASR) which consists an essentialarea of artificial intelligence and it ought to be taken into consideration in course of any connected research (Categoryof vocabulary size ,speech, etc.). It also offers synopsis of essential research applicable to speech processing in the pastfew years, along side the overall scheme of our project that should be taken into account as aaddition of data in this field of study and to finish it off by mentioning about certain improvements that as it may be in further works.

The Efficacy of Risk-Assessment Score for Early Screening of Diabetes Mellitus Among Bangladeshi Adults
Authors:- Zaher Ahmed, Dr. Iftekhar Hasan

Abstract:-The chronic metabolic disorder diabetes mellitus (DM) is a fast-growing global problem with huge social, health, and economic consequences. Studies support the utilization of risk-assessment scoring systems in quantifying individual’s risk for developing T2DM. Thus, using a simple risk-assessment scoring system for early screening of T2DM among Bangladeshi adults will be beneficial to identify the high-risk adults and thus taking adequate preventive measures in combating diabetes. The aim of the study is to evaluate the efficacy of a risk-assessment scoring system for early screening among Bangladeshi adults for developing T2DM. A cross-sectional observational study was carried out to evaluate the efficacy of risk-assessment scoring system in the outpatient department (OPD) of Medicine, Barishal Medical College & Hospital, Barishal, Bangladesh from June 2020 to November 2020 among randomly sampled 323 adult Bangladeshi male and female subjects. With written informed consent, the Finnish Diabetes Risk Score (FINDRISC) questionnaire was used to collect the data including demographic characteristics and different risk factors. In this study, both non-modifiable and modifiable risk factors showed statistically significant association with the FINDRISC among Bangladeshi adults(p<0.05). Among 323 subjects, a total of 28.12% had slightly elevated diabetes risk score (DRS). A total of 16.05% had moderate DRS and 8.48% had very high DRS. There was a significant association among FINDRISC with history of previous high blood glucose, and treated hypertensive Bangladeshi adults. This study predicts that 24.53% of the Bangladeshi adults may develop moderate to high risk T2DM within the consecutive 10 years. This study clearly demonstrates that FINDRISC scoring system can work reasonably well as screening tool, detecting undiagnosed T2DM in the general population. People with high risk of DM should be referred for early intervention and changes to a healthy lifestyle and primary prevention to prevent or delay the onset of T2DM.The findings may help the health care professionals to substantiate the possible improvement in glucose metabolism and lifestyle changes, and better convince people at high risk of T2D to take action towards healthier lifestyle habits.

Big Data Security Challenges and Prevention Mechanisms in Business
Authors:- Anusha Dissanayake

Abstract:-Sensitive data analytics have reached gradually a smart area in the business world over the past few years. Various research has emphasized the importance of this field in augmenting the business performance in the industry. Excessive collection of data is making harmful effects on human beings. These data are extremely vulnerable for outsiders thanks to their hidden value. Big data gives us more advantages to make progress in many fields including business. It improves the competitive advantage of companies and to add value for many social and economic sectors. Sensitive data sharing brings new information security and privacy challenges. Earlier technologies and methods are no longer appropriate and lack performance when applied in a big data context. This research focuses on investigating the challenges and providing viable solutions to minimize the risk of the threats of user data.

Assessment of Waste Management Techniques from Palm Oil Producing Industry: A Case Study of Nigerian Institute for Oil Palm Research (Nifor) Benin City
Authors:- Olawepo B. B., Smart Bello, Diamond Blessing, Ajayi A. S., Eriakha E. C.

Abstract:- Oil palm (Elaeisguineensis) is one of the most important economic oil crops in Nigeria. As of early 1900, Nigeria was producing all palm oil sold in the world market. Nigerian Institute for Oil Palm Research (NIFOR) is an International Center of Excellence in Palms and Shea Research and Development. It is a common sight to see decayed and overflowing solid and liquid waste dumps all over most palm oil producing industries. The objective of this study is to assess the technique for waste management in NIFOR. Primary data through interview and secondary data from literatures and periodicals were used. The survey reveals that most wastes generated are converted into useful means. The POME (Palm oil mill effluent) is converted into organic fertilizer through the process of composting, the EFB (Empty fruit bunch) is used for erosion control and for increasing soil water retention capacity, and the PKS (Palm kernel shell) is used as a source of fuel for boilers and sterilizers. It is therefore recommended that the government and management of NIFOR should increase environment awareness programme for all staff to save cost and create less environmental degradation while vigorously involving the people in all facets of environmental management.

Design, Fabrication and Testing of a Cocoa Depodding Machine
Authors:- Smart Bello, Olawepo B. B., Diamond Blessing, Suleiman A. I.

Abstract:- The project involves the design of a cocoa depodding machine, to eliminate drudgery experienced by local farmers using manual method of pod breaking. The basic features of the machine are the frame, feeding trough, shaft, stationary blade, rotating blade, rotating drum, chain, and electric motor. The machine operates on the principle of compressing the pods against the stationary blade to break it and separate the pods from the beans. As the blade rotates, it pushes the pods towards the stationary blade, which cuts the pods and transfers it to the separation chamber. As the drum rotates the beans are separated from the pods through the rotating sieve while the pod goes out through the discharge outlet. The machine is powered by 1hp three phase electric motor. The machine has an efficiency of 36%, a capacity of 500kg/hr. The depodding machine can be used by local farmers in rural areas for small scale cocoa processing.

Martial Arts and Combative Program of the Philippine Military Academy Cadet Corps Armed Forces of the Philippines: An Assessment
Authors:- Jayson L. Vicente

Abstract:- The young men and women of PMA CCAFP are bred to be front liners and last line of defenseduring war and times of peace as such, they must be equipped with the most practical and most effective combat ready Martial Arts and Combative skills to effectively fulfil their duty,as well as to protect and safeguard themselves to continue serving the people and their country. This study shall assess the current Martial Arts and Combative Program of the PMA CCAFP using descriptive methodology by interviews and floating questionnaires. The current Martial Arts and Combative Program of the PMA CCAFP with all of the subjects involved are more sports inclined rather than combat equipped. Picking the best from each subject used in the program, this study seeks to recommend improvements or create a better Martial Arts and Combative Program that will satisfy the objective of producing Martial Arts combatant graduates. A good Martial Arts and Combative Program for PMA is essential to prepare them on what lies ahead which is unforgiving and no rules to pacify threat.

Identification of New Cloud Computing Approach for User Authentication and Protection
Authors:- Research Scholar Nipun Sharma, Prof. Dr. Rohit Kumar Singhal

Abstract:- Cloud computing is the very attractive technology area in the current era due to its cost effective, flexible and portable services. Cloud computing is basically a business model which provides services related to Information Technology on demand over network. It offers on demand network access to the pool of shared resources with minimal management effort and service provider interaction. When the services of Cloud Computing are used, the major issue arises, that is security. To tackle with these kinds of issues, Cloud Provider must have sufficient control to provide security. There are different-different provisions available with service provider to handle such kinds of above security issues. Intruders can affect files stored in the cloud or messages of users by intercepting. There is required to provide security to files or messages by means of encryption techniques.To prevent attacks like chosen plain text attack, chosen cipher text attack, denial of service attack.

Determination of Seat Design Prameters Based on Ergonomics
Authors:- Shubham Kadam, Amit Nagarkar, Siddhesh Sawant, Pratik Khopade, Prof. Dhiraj Kumar K. More

Abstract:- Automotive seat design has been always challenge for engineers because design parameters for automotive seats are complex. Three design objectives comfort, safety, and health need to be satisfied simultaneously and measurement of this objectives are difficult because of such factors as user subjectivity, seat geometry, occupant anthropometry and amount of time spent sitting. This paper describes various methods of comfort analysis of off-road car vehicle seat which is based on different criteria like fit parameters related to anthropometric measurements, feel parameters and support parameters defined with respect to seated posture.

Current Issues and Challenges of Online Learning Approach due to Pandemic Outbreak of Coronavirus (Covid-19)
Authors:- Hosalya DeviA/P Doraisamy

Abstract:- The pandemic outbreak of novel coronavirus (COVID-19) recently since March 2020 has constrained many people in the world to opt for a different lifestyle, a new way of work as well as an alternative way to learn. Before the COVID-19 pandemic, the face-to-face traditional class is the most common and favorable learning approach among the students, teachers, parents, academic institutions, and the Ministry of Education. However, online learning has become a famous and well-known resolution around the world after the movement control order is enforced. The online mode of learning has many issues and challenges. Both students and teachers require more time to adapt to online learning because the majority of them are still trying to explore the new technological innovation and techniques to use in the online learning process. In the future, a mixture of the mode of learning would be one of the selections for the academic institution, especially a higher learning institution.

Production of Bioplastics from Banana Peels
Authors:-Jaikishan Chandarana, P. L.V. N Sai Chandra

Abstract:- Plastic offers a variety of benefits, in a variety of shapes, such as sheets, panels, film, which can all be flexible as the application requires. However, use of too many plastics results in massive harmful effects. It takes longer time to degrade which is estimated about 500 years to degrade and will become toxic after decomposed. The objective of this study is to produce biodegradable plastic from banana peels as a substitute for the conventional plastic and to prove that the starch in the banana peel could be used in the production of the biodegradable plastic. The strength of the film was determined using the elongation test by comparing the biodegradable film with a control film and a synthetic plastic. In the soil burial degradation test, the intensity of degradation was tested for all three types of film and the biodegradable film degraded at a rapid rate compared to control film while the synthetic plastic did not degrade at all. Based on all the testing that was carried out, the biodegradable film from banana peel is the best and ideal overall compared to the control and synthetic plastic. The tensile strength for sample keeps increasing when the residence times are increased from 5 minutes to 15 minutes and reaches a maximum at 15minutes and then starts decreasing when the time is increased to 20 minutes. This suggests that the optimum hydrolysis time is 15 minutes for this sample set Bioplastic film can sustain the weight near about 2 kg and which have enough tensile strength. The bioplastic prepared from banana peels that can be used as packaging material or as a carrying bag. Glycerol is added as plasticizer that increases its flexibility.

A Genetic Algorithm Approach for the Solution of Economic Load Dispatch Problem
Authors:- M.Tech. Scholar Siddhartha Tiwari, Prof. Dr. Dwarka Prasad

Abstract:- In this paper, comparative study of two approaches, Genetic Algorithm (GA) and Lambda Iteration method (LIM) have been used to provide the solution of the economic load dispatch (ELD) problem. The ELD problem is defined as to minimize the total operating cost of a power system while meeting the total load plus transmission losses within generation limits. The application of Genetic algorithm (GA) is to solve the economic load dispatch problem of the power system. The effectiveness of the proposed algorithm has been demonstrated on two different test systems considering the transmission losses. GA and LIM have been used individually for solving two cases, first is three generator test system and second is ten generator test system. The results are compared which reveals that GA can provide more accurate results with fast convergence characteristics and is superior to LIM.

Expansion in Kernel PCA Approach for Face Recognition
Authors:-Asst. Prof. Ritu Nagila, Asst. Prof. Ashish Nagila

Abstract:- Principle component analysis (PCA) technique is most populating technique of statistics in field of face recognition. Today, numerous extension of PCA is exiting like improved PCA, Fuzzy PCA, Incremental PCA, and Kernel PCA. Kernel PCA (KPCA) is most popular techniques in face recognition in non liner categories. Till date not desirable extensions are accessible. This paper is proposed a novel approach of KPCA. Experiments have been done on ORL database. Proposed method obtained highest recognition rate as 98.6%.

A Review on Lossless Data Compression Techniques
Authors:- Rahul Barman, Sharvari Deshpande, Prof. Dr. Nilima Kulkarni, Shruti Agarwal, Sayali Badade

Abstract:- Data is being generated at an exponential rate in every sector of the world. This much amount of data can prove to be very costly in terms of data storage, transfer speed and infrastructure. Due to this many industries have shifted their focus on cloud-based storage technology. Lossless data compression is one of the important approaches to solve the problem of excessive storage consumption, maintaining data integrity, transfer efficiency and achieving higher streaming speed. Lossless data compression refers to the process of modifying and converting the bit structure of data such that it consumes less storage space and provides near loss of original data. There exists different algorithms and techniques for performing the compression on different types of data formats. This paper identifies different lossless data compression techniques in existence and a conclusion is drawn based on these identified methods. Comparative analysis has been made of different algorithms used in various referenced papers. It describes the future scope and application of compression algorithms in several fields.

Experimental Study on Strength and Durability of Concrete By Partial Replacement of Cement, Fine And Coarse Aggregate using Corn Cob Ash, C&D Waste Recycled Sand and Bethamcherla Stone with Addition of Steel Fibers
Authors:- M.Tech.Scholar Badiga Siva Bhavyank, Asst. Prof. K V Madhav

Abstract:- Main objective of this project is to reduce the usage of cement, fine aggregate and coarse aggregate and improve the strength of concrete by using steel fibers. In this study we will investigate on the strength characteristics and durability properties of concrete with CORN COB ASH (CCA), CONSTRUCTION & DEMOLISION (C&D) WASTE RECYCLED SAND and BHETAMCHERLA STONE (BS) and addition of STEEL FIBERS. Replacement of CCA, C&D Sand and BS are about 0%, 5%, 10%, 15% and 20% respectively by weight of Cement, Fine Aggregate and Coarse Aggregate. The obtained optimum % of CCA, C&D Sand and BS are investigated. Then with that optimum % of CCA, C&D Sand and BS obtained are used to produce concrete.. Then the steel fibers will be added to the optimum % of CCA, C&D Sand and BS concrete and to conventional concrete in the % of 0%, 1%, 1.5%, and 2% by the weight of cement. Mechanical properties at 7,14,28 days will be investigated. Then investigations will be carried out for Percentage loss in compressive, split tensile and flexural strengths, Percentage loss of weights by considering the Durability tests such as acid attack test and alkaline attack test at the age of 28 and 90 days. The grade of concrete is M25.

A Review Study on Theoretical Investigation of Hydrogen Production Methods
Authors:- Pramod Panta, Mohit Pandita, Nitin Kumar, Sudhir Singh

Abstract:- This paper present the sustainable, green and zero-carbon emission method of hydrogen production. Depending upon the source of energy used to generate the hydrogen the methods are classified like solar energy, thermal energy, photo-electric. The different process to generate the hydrogen are analyzed and compared in it which give the brief and important description of green and zero-carbon emission method.

Realizing the Benefits of RPA in the Legal Field
Authors:- Shital Gopal Shetkar

Abstract:-Robotic Process Automation (RPA) is finding many valuable uses in the legal field. Legal work is often repetitive and document-intensive, which makes it suited to RPA. Automation enables law firms and legal departments to speed up routine processes, saving time and reducing errors. As a result, attorneys and other staff members can focus on more critical tasks. RPA also helps with compliance. This paper examines how legal organizations are realizing the benefits of RPA, based on reviews of Ui Path by members of IT Central Station.

Sentiment Analysis of Twitter Data by Making use of Machine Learning Algorithm
Authors:- ME Scholar Kratika Patidar, HOD. Kamlesh Patidar

Abstract:- Individuals utilize online media for amusement, bringing data, news, business, correspondence and some more. Not many such online media applications are Facebook, Twitter,WhatsApp, Snapchat, etc. Twitter is one among the miniature publishing content to a blog site. We are utilizing Twitter predominantly because it has acquired a great deal of media consideration. The content composed is alluded to tweets, where an average person can tweet or compose their hearts out. We would be bringing immediate reactions from the general population also. Thus, the information is all the more ongoing. The initial step is to get the tweets on a specific plan utilizing python language code, followed by the cleaning cycle; at that point comes the making of the sack of words. Later these packs of terms are given as a contribution to the calculations. Finally, after preparing the estimates, we will be getting the sentiment of general society on that system.

Pectin Extraction from Orange Peels by Using Organic Clay
Authors:- Dr. Supriya Pratap Babar

Abstract:- The present work addressed to the development of the method which is the part of the process needed for the extraction of biopolymer like pectin from the orange peel, which is the waste of orange juice processing industry. Pectin is used by pharmaceutical industry, food industry and also widely used in cosmetics, herbal medicines, manufacturing of soaps. In this method we have used the organic clay as mineral acid instead of strong concentrated acid. These results demonstrated, that the pectin yield was affected by pH. At the low pH for red clay (4.3) maximum yield (4%) of pectin was obtained.

Customer Churn Prediction in Telecommunication
Authors:- Pooja Mahanth Bhagat

Abstract:- Procurement and the maintenance of customers/clients are the top most concerns in the present business world. The quick increment of market in each business is prompting higher endorser base. Therefore, organizations have understood the significance of holding the close by clients. It has gotten compulsory for the specialist co-ops to diminish beat rate on the grounds that the carelessness could be come about as productivity decrease in significant viewpoint. Agitate expectation helps in recognizing those clients who are probably going to leave an organization. Media transmission is adapting to the issue of truly expanding agitate rate. Data mining procedures empower these media transmission organizations to be furnished with viable strategies for lessening stir rate. The paper audits 61 diary articles to study the upsides and downsides of prestigious Data mining procedures used to assemble prescient client beat models in the field of media transmission and in this manner giving a guide to scientists to information amassing about Data mining strategies in telecom.

A Review of an Extensive Survey on Audio Steganography Based on LSB Method
Authors:-Hariom Dudhwal, Asst. Prof. Jayshree Boaddh, Asst.Prof. Jashwant Samar

Abstract:- There is issues and challenges regarding the security of information in transit from senders to receivers. The major issue is the protection of digital data against any form of intrusion, penetration, and theft. The major challenge is developing a solution to protect information and ensure their security during transmission. In audio steganography, the cover is an audio and the secret information can be a text file, an image, or an audio. In this work, some audio steganography techniques are explored taking cover audio in WAV and MP3 format. WAV files produce integer samples and MP3 files give floating point numbers as samples. The secret information considered is the text file, the image, and the audio. The embedding and extracting algorithms of the different audio steganography techniques are discussed in this examination. This work presents a survey of literature on MP3 Steganography Based on Modified LSB Method.

A Review Study on Neuro Evolution
Authors:- Reeba Mehmood Khan

Abstract:- With the steady improvement in the field of artificial intelligence and information technology, the part of evolutionary algorithms is likewise booming. There is a need to raise these ideas in-order to broaden the sky-lines amongst newbies. Neuro Evolution is an integral part of artificial intelligence and machine learning wherein it centers around evolutionary algorithms in order to create artificial neural networks. This is a procedure that utilizes the entire parcel of biology and assists with developing and constructing artificial intelligence-based evolutionary algorithms. It is a branch which takes motivation from the evolution of the biological nervous system and attempts to incorporate it with the innovation ace “artificial intelligence”. This paper focuses on the fundamental understanding of what neuro evolution is and what is it doing here, how can it work and get implemented, how are neuro evolution and artificial intelligence working inseparably and furthermore it attempts to raise the algorithmic working alongside the significant applications that neuro evolution presents.

Study on Quality of School Life of Working Students
Authors:- Manit B. Dapadap, Jhon Edcel Calites

Abstract:- This study aims to contribute to developing knowledge and understanding of the phenomenon of school life quality for working students by taking the students’ perspective on what they perceive as positive or/and negative about their school life. The study was conducted among working students at Tacloban National Agricultural School. A semi-structured interview guide was used to get information about students’ experiences as working students. The main study is qualitative, using a phenomenological approach. Five students from junior and senior high were selected for in-depth interviews. Parents of the students, as well as the advisers, were interviewed for triangulation. The collected data were analyzed according to the phenomenological thematic analysis. Findings revealed that students are involved in many activities, and most of them work to assist their families and finance their education. How work influences, their education seems to depend on their perception of their work, whether they like it or not, and to what extent it is an obligation. One strategy to lift the quality of the school life of working students is to listen to the students’ voice. The study emphasizes the teacher as the leading resource contributing to the quality of school life for the students. Positive communication must be encouraged between students and teachers to raise awareness of the conditions of working students. To secure the quality of the school life of the working students, the school should come up with strategies that offer education within special needs, particularly in the delivery and assessment of competencies. Further, a strong partnership between the school and the community should be established to increase understanding of the working students’ condition and contribute to improved quality of school life.

A Survey of Real Time Deep Learning Based Object Detection
Authors:- Ahmad Ismail

Abstract:- The importance of artificial intelligence manifests in all of our life’s aspects, robotics, self-driving, surveillance, agriculture, transportation, medicine, space, and military. Deep learning is the paramount core for AI applications; especially object detection, localization, and tracking. The convolutional neural networks make momentum regarding the aforementioned topics. The architecture in this field varied from the fine-grained to the real-time models. Meanwhile, the fine grained models produce the maximum possible accuracy; it consumes time on the other side, real-time models are featured with speed, but it provides less accuracy.In this paper, we will review start-of-the-art models being used for near real-time object detection and tracking, then introduce our approach; an accurate real-time object detector and tracker.

A Review Article of Image Fusion Technique Using Wavelet Transform
Authors:- P.G. Scholar Pushpa Yadav, Asst. Prof. Hemant Amhia

Abstract:- In this thesis various methods for lossless Image fusion of source image data are analyzed and Discussed. The main focus in this work is lossless Image fusion algorithms based on context modeling using tree structure. The central aspect in context modeling is different context templates, which are based on discrete Cosine transform coefficients, local gradients and intensity of samples in the image. This work includes research on how to use DDCT context tree structure, prediction modeling and probability assignment in lossless image fusion based on context modeling technique. The main advantage over current methods is increasing effectiveness of image fusion and developing new lossless Image fusion methods based on context modeling for different type grayscale images: medical, astronomical, noisy natural images.Due to the increasing requirements for transmission of images in computer, mobile environments, the research in the field of image fusion has increased significantly. Image fusion plays a crucial role in digital image processing, it is also very important for efficient transmission and storage of images. When we compute the number of bits per image resulting from typical sampling rates and quantization methods, we find that Image fusion is needed. Therefore development of efficient techniques for image fusion has become necessary .This paper is a survey for lossy image fusion using Discrete Cosine Transform, it covers JPEG all format of image fusion algorithm which is used for full-color still image applications and describes all the components of it.

Diabetes Prediction Technique Using Ensemble Classification
Authors:- Research Scholar Akanksha Mishra, Dr. Prof. Rohit Kumar Singhal

Abstract:- Data Mining can be defined as a technology using which valuable knowledge can be fetched out from the massive volume of data. The big patterns can be explored and analyzed using statistical and Artificial Intelligence in big databases. Many researchers are implementing data mining techniques in the field of bioinformatics. Bioinformatics can be defined as a science of storing, fetching, arranging, interpreting and using information obtained from biological series and molecules. Prediction can be defined as a statement about future event on the basis of present situation. This work focusses on diabetic prediction with machine learning algorithms. The diabetic prediction has various steps. A voting-based classifier is devised in this research to predict diabetes. The performance for the diabetic prediction is optimized up to 2 percent using proposed algorithm.

Modeling and Simulation of Inverter Based Photovoltaic Power Generation System for Various Applications
Authors:- Aasha Rahangdale, Santosh Kumar

Abstract:- The use of new efficient photovoltaic solar cells (PVSCs) has emerged as an alternative measure of renewable power. Owing to their initial high costs, PVSCs have not yet been a fully attractive alternative for electricity users who are able to buy cheaper electrical energy from the utility grid. A photovoltaic array (PVA) simulation model is developed in Mat lab-Simulink GUI environment. The model is developed using basic circuit equation of the photovoltaic (PV) solar cells including the effects of solar irradiation and temperature changes. The new model was tested using a directly coupled ac load via an inverter. Test and validation studies with proper load matching circuits are simulated and result are presented. The Total harmonic distortion in output voltage with filter is 2.16 % which is under the IEEE standard.

A Review on Energy Efficiency of Microgrid Implementation with Solar Photovoltaic Power Plants
Authors:- M.Tech. Scholar Deepak Kumar Dhote , Dr. Samina Elyas Mubeen (HOD)

Abstract:- The aim of the article is to study of the operating modes basis of distributed solar power plants, power consuming storage and power filtering devices using simulation tools. and energy efficiency assessment of local microgrid on the change of the concept of developing modern power engineering is conditioned by growing interest in renewable energy sources The most rapid pace of the development among low-power distributed renewable energy sources is presented by private solar power plants, which operate both autonomously, and can be integrated into the industrial network which is designed to solve two key tasks – performing the function of the backup power supply in the autonomous operating modes of the system and the alignment of the load profile, that is, the elimination of daily peaks and failures in power consumption. To meet the demand of the next generation power system, renewable energy resources can be the fuel of choice because it is easily available, free of cost, environment-friendly, and the renewable energy-based generation is cost effective in all manners. There are several types of renewable energy resources such as solar, wind, geothermal, tides, and biomass. In this paper, the concentration is limited to the solar energy resources, solar plants, and storage system to provide required power support.

A Vehicles for Open-Pit Mining with Smart Scheduling System for Transportation Based on 5G
Authors:- Atianashie Miracle Atianashie., Michael Opoku

Abstract:- 5G connectivity, big data, and artificial intelligence, open-pit intelligent transport systems based on autonomous cars have become a trend in the construction of smart mines with the advancement of IoT technology. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. In an open-pit mine, several sensors are used to operate unmanned cars. We enhance vehicle tracks and, using big sensor data, build an efficient, intelligent transport system. Based on large amounts of data, such as vehicle information, vehicle GPS data, production plan data, etc., a multi-object, intelligent scheduling model of open-pit mine unmanned vehicles were developed to reduce transportation costs, total unmanned vehicle time, and the rate of content fluctuation. The current output of the open-floor mine is reliable. The next thing we use to solve our planning problem is artificial intelligence algorithms. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multiobjective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

Energy Efficiency of Microgrid Implementation with Solar Photovoltaic Power Plants
Authors:-M.Tech. Scholar Deepak Kumar Dhote , Dr. Samina Elyas Mubeen (HOD)

Abstract:- The utilization of solar energy as a solar power plant can be a potential power plant to be developed. One of the problems in the solar power plant system is the power instability generated by the solar panels because it relies heavily on irradiance and relatively low energy conversion efficiency. To solve this problem, the Maximum control of Power Point Tracking (MPPT) is required by the Perturb and Observe (P&O) methods. This P&O MPPT control makes solar PV operate at the MPP point so that the solar PV output power is maximized. However, the MPPT P&O control that works at the MPP point makes the output voltage to the load is also maximum that causes overvoltage. The MPPT mode works when the solar PV output power is smaller than the reference power to maximize solar PV output power The aim of the work to design the distributed solar power plants, power consuming storage and power filtering devices using simulation tools. and energy efficiency assessment of local micro grid on the change of the concept of developing modern power engineering is conditioned by growing interest in renewable energy sources The most rapid pace of the development among low power distributed renewable energy sources is presented by private solar power plants, which operate both autonomously, and can be integrated into the industrial network which is designed to solve performing the function of the backup power supply in the autonomous operating modes of the system and the alignment of the load profile, that is, the elimination of daily peaks and failures in power consumption. The implementation of these functions, combined with the installation of power active filters will minimize losses in the line and elements of ESS and it will be perform on MATLAB simulation.

A Comprehensive Overview of WLAN Security Attacks
Authors:-Yeshwanth Valaboju

Abstract:- Wireless communication has broken the constraint individuals utilized to have also in addition to wired innovation. The right to gain access to provider network without being bound, versatility while accessing the Internet, boosted consistency, as well as adaptability, are an amount of the variables steering the wireless LAN modern-day technology. Different other variables that contribute to the impressive development of Wireless Area Networks(WLANs) are lessened setup time, enduring cost discount rates, and likewise instalment in difficult-to-wire areas. Wireless LANs level of popularity has performed the growth as a result of the fostering of the IEEE 802.11 b spec in 1999. Over the last couple of years, wireless LANs are widely set up in a location like company, federal authorities bodies, health care centres, colleges and also building atmosphere.

Risk Analysis of Putting Attacks into Perspective and Conducting a Vulnerability Assessment
Authors:- Bhagya Rekha Kalukurthi

Abstract:-In various other to prevent unauthorized use risk set up via vulnerable wireless accessibility areas, Wired Matching Personal privacy – a low-level files shield of encryption physical body– was developed for wireless security purposes. WEP protocol protects link-level information throughout wireless transmission in between consumers along with access to aspects. It carries out indeed certainly not give end-to-end security, nevertheless merely for the wireless area of the link. Wireless security is an authentic barrier for network managers and also particulars security managers similar. Unlike the wired Ethernet LANs, 802.11-based wireless LANs broadcast radio-frequency (RF) records for the customer terminals to pay attention to. As a result, anybody along with the right resources can quickly take hold of and also move wireless signs if he is in fact within a selection.

VLSI Architecture for 8-bit Reversible Arithmetic Logic Unit based on Programmable Gate
Authors:- M.Tech.Scholar Sameer Suman, Dr. Anshuj Jain(HOD)

Abstract:- Reversible computing spans computational models that are both forward and backward deterministic. These models have applications in program inversion and bidirectional computing, and are also interesting as a study of theoretical properties. A reversible computation does, thus, not have to use energy, though this is impossible to avoid in practice, due to the way computers are build. It is, however, not always obvious how to implement reversible computing systems. The restriction to avoid information loss imposes new design criteria that need to be incorporated into the design; criteria that do not follow directly from conventional models.In this paper, investigate garbage-free reversible central processing unit computing systems to physical gate-level implementation. Arithmetic operations are a basis for many computing systems, so a proposed the design of adder, sub tractor, multiplexer, encoder and work towards a reversible circuit for general circuit are important new circuits. In all design implemented Xilinx software and simulated VHDL text bench.

Artificial Hand using Embedded System Involve Arm Processor and Sensors
Authors:- Nishanth B

Abstract:- In this work, Many of the people misfortune their hand, for example, mishap, the aid of the amputee, and incapacitated people their life. The artificial hand is low weight and simple compact smaller confined and includes a connection force framework. Artificial hands, which consolidate mechanical plan and established framework multi-modular sensor framework are blanketed detecting everyday and sheer strength. A human hand shape and the capacity of having a take care of utilizing getting a cope with on and grasping items. The artificial hand is a fabricated acrylic cloth that has produced the usage of aluminum and iron respectively. The microcontroller is generally essential in synthetic palms.EMG sensor is interfaced with the top appendage receive the signal from people The palm stayed void and gives sufficient space to a miniature siphon. Due to oneself adjusting highlights of the hand’s several items can be gotten a manage close by. This empowers the improvement of a less weight prosthetic hand with high usefulness Embedded system is a mixture of hardware using a microprocessor and an appropriate software program in conjunction with additional mechanical or different digital components designed to perform a selected assignment. Embedded gadget locations a vital role in this prosthetic hand additionally called an artificial hand Microcontroller and microprocessor places an important role in all types of control applications in prosthetic hand we are using an adhesive substance to deal with light-weight materials It supports weight up to 4kg.

Criminal Activities Predictive Analysis Using Data Mining Techniques
Authors:- Meenu Rai, Bhawana Pillai

Abstract:- Data mining is the extraction of knowledge from large databases. One of the popular data mining techniques is Classification in which different objects are classified into different classes depending on the common properties among them. Machine learning are widely used in Classification. This paper proposes a data mining technique which applies an enhanced existing machine learning Algorithm to detect the suspicious criminal activities. An improved decision tree Algorithm with enhanced feature selection method and attribute- importance factor is applied to generate a better and faster Decision Tree. The objective is to detect the suspicious criminal activities and minimize them. This paper aims at highlighting the importance of data mining technology to design proactive application to detect the suspicious criminal activities.

A Review on Fiber Reinforced Concrete Using Glass Fiber Reinforced Concrete (GFRC)
Authors:- Abdul Rasheed, Asst. Prof. Anuj Verma, Asst. Prof. Mohd Rashid

Abstract:- Plain concrete possess very low tensile strength, limited ductility and little resistance to cracking. Internal micro cracks are inherently present in concrete and its poor tensile strength is due to propagation of such micro cracks. Fibers when added in certain percentage in the concrete improve the strain properties well as crack resistance, ductility, as flexure strength and toughness. Mainly the studies and research in fiber reinforced concrete has been devoted to steel fibers. In recent times, glass fibers have also become available, which are free from corrosion problem associated with steel fibers. The present paper outlines the experimental investigation conducts on the use of glass fibers with structural concrete. CEM-FILL anti crack, high dispersion, alkali resistance glass fiber of diameter 14 micron, having an aspect ratio 857 was employed in percentages , varying from 0.33 to1 percentage by weight in concrete and the properties of this FRC (fiber reinforced concrete) like compressive strength, flexure strength, toughness, modulus of elasticity were studied.

Foot over Bridge Random Vibrational Analysis for Diffrent Slab Material
Authors:- PG Student J. P. Pawar, Prof. R. S. Patil, Dr. G. R. Gandhe (H.O.D)

Abstract:- Damping performs essential function in format of vibrational resistant structures, which lower the changeof the shape when they are subjected to lateral loads or vibrational load. In the existing study the deck of bridge is check for various materials like MS steel plate, RCC slab, and aluminum and MS plate composite deck. The important challenge of a structure is to endure the vibrationalloads on deck slab. In order to reduce structuralvibration has been used. The bridge is modeled in ANSYS 2019 and modeled with different material of deck. After the study results show foot over bridge having 100 mm thick slab shows better result than having composite sheet or having MS sheet as deck slab.

A Comparative Analysis of Optimization Techniques
Authors:- M. Tech.Scholar Palac Gupta

Abstract:- Regression testing is an important process during software development. For the purpose of reducing the number of test cases and detecting faults of programs early, this paper proposed to combine test case selection with test case prioritization. Regression testing process has been designed and optimization of testing scheme has been implemented. The criterion of test case selection is modify impact of programs, finding programs which are impacted by program modification according to modify information of programs and dependencies between programs. Test cases would be selected during test case selection. The criterion of test case prioritization is coverage ability and troubleshooting capabilities of test case. There are various optimization techniques available. This review explains about the different optimization techniques on the basis of their evolution, methodology, performance and applications.

Literature Review on Pharmaceutical Industry in India Comparison of Post Reform and Pre Reform Period and Policy
Authors:- Ph.D. Scholar Vinod Kumar Gupta, Professor Dr. Rajesh Gupta

Abstract:- The extant literature dealing with the impact of TRIPS agreement on Indian pharmaceutical industry takes the whole country as a unit of analysis, but the present study is unique in the sense that it takes into account the regional aspects of Indian pharmaceutical industry, based on various reports and unit-level data of Annual Survey of Industries since 1991 to 2011. In the year 2005, Indian pharmaceutical industry came under the obligation of Trade-Related Aspects of Intellectual Property Rights (TRIPS); Simultaneously, Indian pharmaceutical firms were also required to comply with Good Manufacturing Practices of World Health Organisation (WHO-GMP). The descriptive evidences depicted that with the introduction of TRIPS and WHO-GMP number of firms and man-days employed declined across the states during the introductory period of TRIPS; whereas net value added and gross capital formation remained constant for the same period. But in the post-TRIPS period most of the states reported greater performance, especially in terms of net value added and gross capital formation.

Review on Management of Hospital Waste in an Efficient Manner
Authors:- Ph.D. Scholar Vijay Kumar Bhardwaj, Professor Dr. Sandeep Kumar

Abstract:- This is a review paper which is prepared from the surveys of hospitals and research studies. Hospital waste management in the world is a strict discipline and does occupy a serious place in the management of health care sector. The management of hospital remaining requires its removal and disposal from the health care establishments as hygienically and economically as possible by methods that all stages minimizes the risk to public health and to environment. Health care waste can be dangerous, if not done properly. Poor management of healthcare waste exposes health labors, waste handlers, and the community to the toxic effects of wastes generated from health activity. The disposal of these wastes could also lead to environmental problems. This article intends to describe various health care wastes and its controlling, as creating good practices for proper handling and disposal of health care waste is an important part of the health care delivery system. The aim of this paper is to highlight the present condition of medical waste and a review on scientific method of hospital waste management. Biomedical waste is identified under many terminologies like hospital waste, healthcare waste etc., which are generated due to long or short term care of persons. Various health care establishments are the minor and major source of these types of wastes. Biomedical waste may be primarily classified as Hazardous and Non Hazardous wastes. Further, the biomedical waste is categorized by WHO and also under The Biomedical Waste (Management & Handling) Rules, 1998, India. According to previous studies the quantum of waste generated in a health care establishment depends on the Income of the country, type of Hospital, Region etc. Biomedical wastes are highly infectious and can be a potential source for transmission of diseases if not properly managed. Hence, a proper management procedure has to be adopted to safely dispose the wastes to safe guard the public health and Environment and a stringent regulation have to be imposed on the health care establishments before and after it is approved for execution. Further, the hospital staffs are at high risk of being infected by these biomedical wastes, therefore, the occupational health and safety can be recommended to be a component of biomedical management plans with qualified personnel in Hospitals.

A Project Report on Risk Return Portfolio Analysis with Reference to Securities Market
Authors:- Shaik Asif Basha, Asst.Prof. Dr. C. Mallesha

Abstract:- Successful investment requires a careful assessment of the investment’s potential returns and its risk of loss. A firm’s risk and expected returns directly affect its share price. In real-world situations, the risk of any single investment would not be viewed independently of other assets. New investment must be considered in light of their impact on the risk and return of the portfolio of assets. In traditional financial analysis, investment management tools allow investors to evaluate the return and risk of individual investments and portfolios. Usually, higher the risk, higher the returns and lower the risk, lower the returns. However, a general understanding of this phenomenon is not sufficient to make appropriate decisions relating to investments. A more quantifiable analysis is required to understand the investment.Thus the following study discusses the analysis of portfolio risk and returns.

Energy Saving System
Authors:- Shivpujan Yadav, Mrs. Rupali Shekokar

Abstract:- In todays the basic problems in any country is wastage of electricity. If we change our behavior and try to avoid the wastage of electricity then we can save more electricity. By saving electricity we can earn money by selling those electricity to our surrounding countries. And by efficient way of using electricity we can bring down the cost of our electricity bill. In this paper, I have design a system which is saving energy. I have design this system for schools, colleges etc. Only authorized person can enter into the classroom. There are two options present for students and teachers to use lights and fans in the classroom. First one is manually by switch and second one is automatically by detecting the position of person in the room lights and fans will be on.. When there is nobody present inside the classroom then automatically all electrical appliances will be off.

Awareness and Practice of Biomedical Waste Management
Authors:- Ph.D. Scholar Vijay Kumar Bhardwaj, Prof. Dr. Sandeep Kumar

Abstract:- Healthcare is an important area of human care. The very process of modern healthcare is also ridden with risk and unhealthy practices. One of this is Bio Medical Waste generation in treatment of human beings; apart from other species. This Bio Medical Waste generation warrants proper Bio Medical Waste management. Bio Medical Waste is defined as waste that is generated during the diagnosis, treatment or immunization of human beings and is contaminated with patients body fluids such as syringes, needles, dressings, disposables, plastics and microbiological wastes. Proper disposal of hospital waste is of paramount importance because of its infectious and hazardous characteristics. Therefore the Government of India promulgated the Bio Medical Waste Rules in 1998 and it became mandatory for all the hospitals to follow the above rules and the standards laid down under the statutory regulations. Healthcare is vital and hospitals are considered to be healers and protectors of health and wellbeing. But the waste generated from treatment and diagnosis can be hazardous, toxic and even lethal because of their high potential for disease transmission. The present study consists of BMW management practices like Segregation, Treatment and Disposal, Waste Handling Safety Measures and Waste Administration that are followed in healthcare facilities. It focuses on the waste management practices of the respondent healthcare facilities on the basis of type of hospital, bed capacity, bed occupancy, amount of waste generation and number of waste handling workers. Besides, the study extends to see the impact of demographical factors on waste management practices. From the related questions regarding `segregation practices`, ‘treatment and disposal practices, ‘waste handling safety measures’ and ‘waste administration’ scores were calculated. Further, based on quartiles, scores are categorized into 3 components viz., Low, Moderate, High for assessing the respondent HCFs view on the waste management practices in the HCFs. The data collected for this study was processed by using SPSS Version 19.0. Descriptive statistical tools like percentages, means and standard deviation and analytical tools like Chi-square, t-test, one way ANOVA, Correlation and Regression are used to test the significant association and impact between characteristics of HCFs and Waste Management Practices.

Awareness and Practice of Biomedical Waste Management
Authors:- Ph.D. Scholar Vijay Kumar Bhardwaj, Prof. Dr. Sandeep Kumar

Abstract:- Healthcare is an important area of human care. The very process of modern healthcare is also ridden with risk and unhealthy practices. One of this is Bio Medical Waste generation in treatment of human beings; apart from other species. This Bio Medical Waste generation warrants proper Bio Medical Waste management. Bio Medical Waste is defined as waste that is generated during the diagnosis, treatment or immunization of human beings and is contaminated with patients body fluids such as syringes, needles, dressings, disposables, plastics and microbiological wastes. Proper disposal of hospital waste is of paramount importance because of its infectious and hazardous characteristics. Therefore the Government of India promulgated the Bio Medical Waste Rules in 1998 and it became mandatory for all the hospitals to follow the above rules and the standards laid down under the statutory regulations. Healthcare is vital and hospitals are considered to be healers and protectors of health and wellbeing. But the waste generated from treatment and diagnosis can be hazardous, toxic and even lethal because of their high potential for disease transmission. The present study consists of BMW management practices like Segregation, Treatment and Disposal, Waste Handling Safety Measures and Waste Administration that are followed in healthcare facilities. It focuses on the waste management practices of the respondent healthcare facilities on the basis of type of hospital, bed capacity, bed occupancy, amount of waste generation and number of waste handling workers. Besides, the study extends to see the impact of demographical factors on waste management practices. From the related questions regarding `segregation practices`, ‘treatment and disposal practices, ‘waste handling safety measures’ and ‘waste administration’ scores were calculated. Further, based on quartiles, scores are categorized into 3 components viz., Low, Moderate, High for assessing the respondent HCFs view on the waste management practices in the HCFs. The data collected for this study was processed by using SPSS Version 19.0. Descriptive statistical tools like percentages, means and standard deviation and analytical tools like Chi-square, t-test, one way ANOVA, Correlation and Regression are used to test the significant association and impact between characteristics of HCFs and Waste Management Practices.

Indian Pharmaceutical Industry, Strategies and Challenges in India, Comparison of Post Reform and Pre-Reform Period
Authors:- Ph.D. Scholar Vinod Kumar Gupta, Professor Dr. Rajesh Gupta

Abstract:- The pharmaceutical manufacturing, especially in countries like India, is in addition to playing an important economic and social role directly related to many health related issues. It is a science-based industry, a symbol of development of science, technology or information, provides service chance for different population levels and has supply significantly to the overall growth of the Indian industryThe principle of this study is to examine presentation and future trends of the Indian pharmaceutical industry in the period before and after the reform. By analyzing data from the pharmaceutical industry, you can understand market trends, the new and emerging companies in the industry and the industry’s expenses and profitability. The analysis of such data provides guidance for monitoring market environment, which in turn can help future investment decisions. In addition, it also helps to track different developments related to certain diseases (such as cardiovascular, anti allergic, etc.).In addition, psychiatry also highlights the legal aspects (patent law) or rations related to the commerce. The study also suggests discussing a specific area within the pharmaceutical industry, the therapeutic area. Therefore, the proposed research includes recognized pharmaceutical manufacturing activities currently in use, including the API industry, formulations, and important therapeutic areas. The researchers outlined the Indian pharmaceutical industry and its evolution from almost non-existent to one of the global generic drug suppliers.

Movie Recommendation using Clustring Technique
Authors:- M. Tech Scholar Pooja Relan, Asst. Prof. Avinash Pal (HOD)

Abstract:- Recommendation system uses different types of algorithms to make any type of recommendations to user.Collaborative filtering recommendation algorithm is most popular algorithm, which uses the similar types of user with similar likings, but somewhere it is not that much efficient while working on big data. As the size of dataset becomes larger than some improvements in this algorithm must be made. Here in our proposed approach, we are applying an additional hierarchical clustering technique with the collaborative filtering recommendation algorithm also the Principal Component Analysis (PCA) method is applied for reducing the dimensions of data to get more accuracy in the results. The hierarchical clustering will provide additional benefits of the clustering technique over the dataset and the PCA will help to redefine the dataset by decreasing the dimensionality of the dataset as required. By implementing the major features of these two techniques on the traditional collaborative filtering recommendation algorithm the major components used for recommendations can be improved. The proposed approach will surely enhance the accuracy of the results obtained from the traditional CFRA and will
enhance the efficiency of the recommendation system in an extreme manner. The overall results will be carried out on the combined dataset of TMDB and Movielens, which is used for making recommendations of the movies to the user according to the ratings patterns created by the particular user.

Modeling of a Hybrid Energy System Connected System
Authors:- M.Tech. Scholar Sumit Kumar Mehta, Asst. Professor Mithilesh Gautam

Abstract:- In integrated micro-grid, PV system is usually controlled to operate in the maximum power point tracking (MPPT) mode. The battery energy storage system is operated in constant power charging or discharging mode. In order to provide an integrated energy system connected to grid Depending on individual energy requirements, the Integrated Energy System can be an add-on to an existing energy source (an integrated solution) to reduce fossil-fuel consumption or a stand-alone for complete fossil fuel displacement. Through extensive integration of energy infrastructures it is possible to enhance the sustainability, flexibility, stability, and efficiency of the overall energy system. This concept together with the cost reduction, technology development, environmental awareness, and the right incentives and regulations has unleashed the power of the sun. And all system result will be carried out by matlab simulation is proposed for isolated micro grids with renewable sources.In the presented technique, the pitch angle controller is designed for wind turbine generator (WTG) system to smooth wind power output. The proposed strategy is tested in a typical isolated integrated micro-grid with both PV and wind turbine generator.

Review on Diagnosis of COVID-19 from Chest CT and X-Ray Images Using Deep Learning Algorithms
Authors:- Vishwas V (M.Tech.), Dr. Kiran Gupta Professor

Abstract:- As we all know , the world has been in a cocoon this whole year, and we have only now begun to step back into normalcy. COVID-19 outbreak was announced as a Global Pandemic by WHO on 11 March 2020 by which time the Global tally of infected people was at 114,243 and the deaths at around 4302. Due to the absence of specific therapeutic drugs or vaccines for the novel COVID-19, it is essential to detect the disease at its early stage and immediately isolate the infected person from the healthy population. Recent findings obtained using radiology imaging techniques suggest that such images contain salient information about the COVID-19 virus. Application of advanced artificial intelligence (AI) techniques coupled with radio-logical imaging can be helpful for the accurate detection of this disease. The objective of this paper is study the diagnostic value of CT and x-ray images and compare their efficiency against RT-PCR and also, to compare and analyse existing deep learning models for classification of Covid pneumonia from regular pneumonia and no pneumonia.

Enhanced the Security through Asymmetric Based RSA Algorithm
Authors:- Mahendra Kumar Choudhary, Ravinder Singh

Abstract:- In the last some decades we are using the internet in our daily communication. We are sending our non-secret as well as secret data using internet. So there is a chance that our data can be leaked of hacked by someone or some unauthorized person or party. So we can try to secure our data with the help of cryptography.The proposed work is using an old symmetric algorithm that is play fair with some modification and RSA that is asymmetric algorithm also. As we know the symmetric key algorithm is using the same time for encryption and decryption.The problem of key exchange problem I used here RSA algorithm.

Heart Disease Prediction using Data Mining Technique
Authors:- Shivangi Agrawal, Asst.Prof. Ashish Tiwari(HOD)

Abstract:- ECG is the most common and basic test performed on patients to detect anomalies in the heart. As a result of the ECG, 10 to 20 minutes of continuous patient heart data were collected and printed as a 1D plot. We have developed a program that extracts a continuous data set from the ECG machine and analyzes the data and extracts various ECG wave functions. First we divide the data by Wavelet decomposition. Then the data is reconstructed to 4 levels, removing noise from the signal. At the same time we detect important components of ECG wave, which are P wave, QRS complex and T wave. Electrocardiogram (ECG) is an important diagnostic tool for assessing cardiac arrhythmias in clinical practice. In this process, we present a deep learning-based convolutional neural network structure that was previously trained in a general data set of signals transmitted to perform automatic diagnosis of ECG arrhythmias by classifying ECG patients under similar cardiac conditions. The main goal of this process is to implement a simple, reliable and easy to use deep learning technique to classify two different selected conditions in the heart category. The results showed that cascading deep learning with conventional SVM was able to achieve very high performance. All this work is done by MATLAB simulation.

Movie Stats: Sentiment Analysis of IMDB Reviews and Tweets of a Movie Using Naïve Bayes Classifier
Authors:- Deep Rahul Shah

Abstract:- Sentiment analysis, also referred to as opinion mining or emotion extraction is the classification of emotions within textual data. This technique has been widely used over the years to determine the sentiments, emotions within a particular textual data. I have designed a way where we as a user can view the real time sentiment analysis of movie reviews and tweets regarding a certain movie. I built a Sentiment Analysis model with an accuracy of 98.7 % and an F1 score of 0.99, which means the model is nearly 99% as accurate as a human in analyzing the Sentiment of the text. Many websites are providing you lengthy reviews, which makes it quite boring to read it, so the proposed system shows the real-time chart and sentiment analysis of the tweets and movie reviews in a user- friendly way. This is what makes MovieStats unique.

IOT based Air and Sound Pollution Monitoring System
Authors:- Roja K, C. Santhosh Kumar, P. Anlet Pamila Suhi

Abstract:- The pollution of air and sound is increasing abruptly. To bring it under control its monitoring is majorly recommended. To overcome this issue, we are introducing a system through which the level of sound and the existence of the harmful gases in the surroundings can be detected. The growing pollution at such an alarming rate has started creating trouble for the living beings, may it be high decibels or toxic gases present in the environment leaves a harmful effect on human’s health and thus needs a special attention.

Survey on “Laxmanrekha-Woman Safety And Alert System
Authors:- Samruddhi Kute, Jayshree Gupta, Pratiksha Sonawane,
Surabhi Sonawane, Girija Chiddarwar

Abstract:- Every day, every woman, young girls, mothers and ladies from all walks of life are struggling to be safe and protect themselves from the roving gaze of the horribly insensitive men who molest assault and violate the dignity of women on a daily basis. The streets, public transport, public places in particular have become the dominion of the hunters. Due to these atrocities that women are subjected to in the present scenario, a smart security wearable device for women based on Internet of Things is proposed. This device is extremely portable and can be activated by the victim on being assaulted just by the click of a button that will fetch her current location and also capture the image of the attacker via camera. The location will be sent to predefined emergency contact numbers or police via smart phone of the victim thus preventing the use of additional hardware devices/modules and making the device compact. Crime against women lately has become problem of each nation round the globe many countries try to curb this problem. Preventive are taken to scale back the increasing number of cases of crime against women. A huge amount of knowledge set is generated per annum on the idea of reporting of crime. This data can prove very useful in analyzing and predicting crime and help us prevent the crime to some extent. Crime analysis is a neighborhood of importance in local department. Study of crime data can help us analyze crime pattern, inter-related clues and important hidden relations between the crimes.

Review and Analysis on Behaviour Based Safety in Renewable (Wind) Energy Project
Authors:- Rajendra Singh Gour, Ms. Nisha Kushwaha

Abstract:- It is projected that in up to 82 per cent of Work-related accidents, workers, Behaviour in the form of acts or comissions is a major contributory factor. Such behaviour can lead for many pre-existing factors to come together in a Potential Severe or Lost Time event. There are several reasons why workers engage in at-risk‟ behaviour at work. Health and safety in the workplace is influenced by a number of factors, from the organisational atmosphere through management attitude and commitment to the nature of the work or task and the personal attributes of the individual. Safety- related behaviour in the workplace can be improved by addressing these major influences. One way to improve safety performance is to introduce a behavioural based safety process that identifies and strengthens safe behavior and reduces unsafe behaviour. Behaviour-based safety is the “application of science of behaviour change to real world safety problems” or “A process that creates a safety partnership between management and employees that continually focuses people’s attentions and actions on theirs, and others, daily safety behaviour.” Behavioural safety processes are not a „quick fix‟ and it is important not to overlook fundamental elements. Organisations should start by concentrating on strategies and systems –assessing and improving management and operational aspects, training, design and so on. First researched in the 1970s in the US, the behaviour-based safety approach emerged in UK organisations in the late 1980s and is now widely used in a variety of sectors in the UK. IOSH has produced this guidance to introduce the background and basic principles of implementing a process which systematically addresses behavioural safety. The methods described are based primarily on observation, intervention and response as ways of changing behaviour.

A Literature Review of Supplier Selection for Construction Project
Authors:- M. Tech. Scholar Sanket D. Alone

Abstract:- This paper is about the selection of supplier for materials required in a construction project. Apart from making a proper schedule of the project for marking the start and completion dates of the project, for optimizing the cost of the project, material supplier is very important from the quantitative as well as quantitative point of view. In order to make an adequate suppliers selection use different criteria depending on the specific case. The supplier selection process deploys an enormous amount of a firm’s financial resources and plays crucial role for the success of any organization. The main objective of supplier selection process is to reduce purchase risk, maximize overall value to the purchaser, and develop closeness and long-term relationships between buyers and suppliers.

Optimising Headway using Communication Based Train Control system
Authors:- Student Amit Shrivastava, Prof. Anshuj Jain, Prof. Ankit Tripathi

Abstract:- In most of the previous researches the grade of automation 3 i.e. (GOA 3) has been analyzed for Direct Train Operation i.e. DTO mode while the focus of this proposed is to analyze the feasibility for the Grade of Automation 4 i.e GOA 4 which implements the Unattended train operation i.e. UTO Mode. In this specification the current Headway used by most of the Metro Rails is 120 sec. The comparison of signaling system of conventional Railways and the CBTC system in Metro Railways is also been included in this work and how the upgraded version have affected the capacity and efficiency of the mass transit system.

Analysis of Fly Ash and Hypo-Sludge Combination for Brick Manufacturing
Authors:- M. Tech. Scholar Prateek Chourawar, Dr. Raviraj Singh Gabbi

Abstract:- Hypo sludge is one of the waste from the paper industries which cannot be recycled hence a subsequent solution has to be found out to dispose these waste. Previous research work suggests that hypo-sludge can be used as replacement for the cement in concrete. So this work planned to use hypo sludge as an ingredient for bricks manufacturing and performing tests. Experiment is done on various set of mixing proportion of the material where different number of days samples are utilize for the examination of various properties of the brick. Results shows that proposed work has achieved good set of strength with increase in percentage of Fly-Ash and Hypo-Sludge. It was obtained that density of dry compacts decreases with increase in weight percentage of Fly-Ash and Hypo-Sludge. As the dry compacts are immersed in water at 1100C -1800C, then through capillary action voids are filled and it becomes hard and the porosity is eliminated. As a result of which the compacts become dense and finally the density increases with increase in Fly-Ash and Hypo-Sludge content. it is clear from SEM micrographs that 75 wt. % FA blend composite has splits which prompt decrement in compressive quality.

Study of Horse Manure with Fly Ash Ingredients in Brick Fabrication
Authors:- M. Tech. Scholar Neelesh Kumar Deshmukh, Dr. Raviraj Singh Gabbi

Abstract:- Research works are not directed on manufacturing of the bricks from natural waste however the current pattern of reusing organic waste has extraordinary effect on building material industry. A few research works have done to discover the substitution of bond in concrete. This examination work is on an arrangement to utilize one such natural waste i.e. horse manure into the bricks fabricating. Fly-ash bricks have officially demonstrated their significance as the ordinary bricks gives hardness to the ground water. This gives a rule that the horse manure can likewise be utilized as a part of bricks fabricating if its quality is satisfactory with in the farthest point. Five diverse weight rates of Fly ash and horse manure with (70%, 60%, half, 40% and 30%) and (10%, 15%, 20%, 25% and 30%) were taken individually. These syntheses were mixed completely by hand mixing, to get a homogenous mix. Distinctive pieces of Fly ash remains alongside horse manure were kept in three diverse little size containers.

A Survey on Security of Clouds and Trust Model Techniques
Authors:- Sidharth Mohan, Asst. Prof. Jayshree Boaddh , Asst.Prof. Jashwant Samar

Abstract:- Cloud computing is an Internet-based computing and next stage in evolution of the internet. It has received significant attention in recent years but security issue is one of the major inhibitor in decreasing the growth of cloud computing. However, this sole feature of the cloud computing introduce many security challenges which need to be resolved and understood clearly. This paper gives a detailed survey on IAAS security issues. As virtual machine should be secured to handle data and maintain privacy. Methods proposed by various scholars are explained which directly or indirectly enhance the security of cloud. Paper has list some of trust techniques developed by researchers for identifying any malicious machine.

MRI Image Segmentation and Classification Using KFCM and Convolution Neural Networks
Authors:- M.Tech. Scholar Nayan Pure, Asst. Prof. Ashish Tiwari

Abstract:- The unlimited and uncontrollable growth of cells can cause human brain tumors. Correct treatment and early diagnosis of brain tumors are essential to avoid permanent damage to the brain. In medical image diagnosis, tumor segmentation and classification schemes are used to identify tumor and non-tumor cells in the brain. The automatic classification is a challenging task which utilizes the traditional methods due to its more execution time and ineffective decision making. To overcome this problem, this research proposes an automatic tumour classification method named as Hybrid Kernel based Fuzzy C-Means clustering – Convolution Neural Network (Hybrid KFCM-CNN) method. The algorithm identifies the position of tumor in brain MRI as they are mostly preferred for tumor diagnosis in clinic. The proposed method also crops tumor region from segmented image and way growth of tumor and help in treatment planning. It also provides important information about location, dimension and shape of brain tumor region with no exposing the enduring to a high ionization radiation. The size of tumor is calculated in term of number of pixels. Similarly the primary brain tumor is considered into Benign and malignant type on MRI brain images, based on accuracy, sensitivity, specificity in MATLAB simulation.

Distribution Planning Model for Water from Different Sources
Authors:- PhD Student Tichaona Goto, Lecturer Iris Shiripinda, Endowed Chair Prof.Fanuel Tagwira, Anthony Phiri (Director)

Abstract:- Urbanization in Africa is characterized by insufficient basic infrastructure, particularly in high density areas. There is need to come up with a model which takes a comprehensive approach to urban water services and viewing water supply as a component of integrated physical system. The purpose of this study is to critically look at demand based planning model for the distribution of water from different locally available sources in the high density suburb of Budiriro as an option of supplying water for gardening, sewage system, drinking and other domestic uses to the residents. This model provides a method of integrating different sources of water to supply water according to use. The model will bring relief on water demand since the use of water from hand dug wells and Rainwater harvesting is another virgin source of water which can be exploited fully. The blending of water from different sources to come up with quality water is one of the thrusts of the model. The model provides future forecasts and scenario planning, but effective water demand should have a planning for integrated water management of the different water sources.

A Review on Low Power and Delay of Ripple Carry and Carry Look Ahead Adders
Authors:- Amit Chaturvedi, Dr.Vikash Gupta

Abstract:- Now a days in the world of VLSI Technology, the word low power consumption is only possible with the concept of Reversible logic design. Reversible concepts will attain more attraction of researchers in the past two decades, mainly due to low-power dissipation and high reliability. It has received great importance due to because of there is no loss of information, while we are processing the data from input to output. Moreover, the power dissipation is also very less and ideally it should be zero. So the concept of reversible design will become more dominant in the low power VLSI design. This paper focuses on the implementation of 4, 8, 16 and 32 bits of highly optimized area efficient Ripple carry adder (RCA) and Carry look ahead (CLA) adders. Finally, we can prove that the Carry look ahead adders are so fastest among all the previously existing designs. All these processes will be Simulated & Synthesized on the ISE Xilinx 14.7 software.

Role of Emotional Intelligence on Our Immune System during Pandemic Situations
Authors:- Research Scholar Mrs. Padmashree G.S, Asst. Prof. Dr. Mamatha.H.K

Abstract:- COVID 19, a global pandemic, which first started in Wuhan city of China in December 2019, spread to different countries across the globe. The effect of the disease in terms of mortality and morbidity are manifold like death, depression, loss of income, anxiety, and migration. Vaccine has been formalized and life is getting normalized, but we are left with questions on what makes human beings susceptible and how can we build our immunity not only physically but also mentally. One such attempt is improving the Emotional Intelligence of people. This article is an attempt to understand the impact of Emotional Intelligence on the Immune System of the human body and how emotional intelligence, if understood and developed properly can help ward off many of the negative consequences of these type of pandemics. In this article, a review has been done on how the domain of Emotional Intelligence (EI) can help tackle this pandemic on an individual as well on the collective level. This is shown by discussing the relationship that EI has on the Immune System. Beginning the discussion from the interaction of Immune system with the environment, this article speaks about the influence of EI on Genes and Placebos which in turn impact the immune system.

Solar Connected Igbt Switch to Enhance Superconducting Magnetic Energy Storage System (Smes) for High Power Dc Application
Authors:- Iqrar Ahmed Ansari, Deepak Pandey, Rahul Singh

Abstract:- A superconducting magnetic energy storage (SMES) system includes a high induction coil that can act as a constant source of direct current. A high temperature SMES (HTS) unit connected to an energy system can absorb and store active and reactive energy from this system and release these powers in this system during demand periods.

A Review on Generation of Electricity from Solar Power Plant
Authors:- M. Tech. Scholar Amar Pratap, Prof. Madhu Upadhyay, Sagar Tomar

Abstract:- The aim of the article is to study of the operating modes basis of distributed solar power plants, power consuming storage and power filtering devices using simulation tools. and energy efficiency assessment of local microgrid on the change of the concept of developing modern power engineering is conditioned by growing interest in renewable energy sources The most rapid pace of the development among low-power distributed renewable energy sources is presented by private solar power plants, which operate both autonomously, and can be integrated into the industrial network which is designed to solve two key tasks – performing the function of the backup power supply in the autonomous operating modes of the system and the alignment of the load profile, that is, the elimination of daily peaks and failures in power consumption. The implementation of these functions, combined with the installation of power active filters will minimize losses in the line and elements of ESS and it will be perform on MATLAB simulation.

Designing and analysis of Microgrid Implementation with Solar Photovoltaic Power Plants
Authors:- M. Tech. Scholar Amar Pratap, Prof. Madhu Upadhyay, Sagar Tomar

Abstract:- Solar energy is a renewable energy that is found abundantly in nature. It is green energy that can be utilized throughout day, therefore maximum energy has to capture from the panel. MPPT algorithm is incorporated to capture maximum energy. A multilevel inverter is a power electronic converter that synthesizes a desired output voltage from several levels of dc voltages of dc voltages as inputs. With an increasing number of dc voltage source, the sinusoidal waveform is obtained by the output voltage, while using a fundamental frequency-switching scheme. The advantage of multilevel inverter is very small output voltage, results in higher output quality and lower switching losses. This paper proposes a MPPT controller based solar power generation system, which consist of dc/dc converter and multilevel level inverter. In solar photovoltaic power generation systems, photovoltaic panels take a large amount of cost, if improve the use of photovoltaic battery and transform the solar battery plate absorption power into alternating current for use by the user as much as possible, will save a lot of money. Based on the equivalent circuit of solar cells, this paper analyzed the characteristic curve of solar cells through the MATLAB simulink model.

Detection of Brain Tumor
Authors:- Jigisha Kamal, Raunak Kolle, Varshini P

Abstract:- A study conducted by the “New England Journal of Medicine” for brain tumor revealed that more than half the cases diagnosed were delayed for a year or longer. This low percentage of correct diagnosis by physical practitioners was astonishing with an average pre-diagnostic symptomatic interval (PSI) being 60 days with a parental delay of 14 days and a doctor’s delay of 30 days. This meant, there existed a delay of almost 104 days in the diagnosis. Among the diagnosed brain tumors only 33% of them were diagnosed by the end of the 1st month after the onset of first signs and symptoms. Physical segmentation of the MRIs by a radiologist is often a monotonous and prolonged process. A viable solution is a Deep Learning aided brain tumor detection and segmentation from brain MRIs. The detection of brain tumor from the magnetic resonance images is an extremely important process for deciding the right therapy at the right time.

Literature Survey on Power Quality and Voltage Flicker Reduction using D-STATCOM
Authors:- Dharmendra Kumar, Prof. Abhishek Dubey

Abstract:- Now-a-days, the most important discussing topic in the world of powersystems is maintenance of power quality The power quality improvement is one of the interesting topics among researchers groups. And they all focused on power quality improvement in power system. In this literature survey paper we are study so many papers written by different researchers. Study and analysis of DSTATCOM and its uses and advantages in power system. .

Smart Dustbin Application Using IOT with GSM
Authors:- Student Jaya Priya. A, Asst. Prof. Dr. N.Shunmuga Karpagam

Abstract:- With increase of population, the scenario of cleanliness with respect to garbage management is degrading tremendously. In city, there are many public places where we see that garbage bins or dustbins are placed but are overflowing. This creates unhygienic condition in the nearby surrounding. Also creates ugliness and some serious diseases, at the same time bad smell is also spread and it degrades the valuation of that area. To avoid such situation we come up with a project called “Smart Dustbin” which is a GSM based Garbage and waste collection bins overflow indicator system for Smart Cities. Over main motivation behind this project is the ongoing campaign Swachh Bharat Abhiyan (Clean India Movement) launched on October 02, 2014 at Rajghat, New Delhi, by the Prime Minister of India Narendra Modi which is India’s largest ever cleanliness drive to clean the streets, roads and infrastructure of the country’s 4,041 statutory cities and towns. In this paper, smart bin constructed on a microcontroller-based platform, which is interfaced with GSM modem, and ultrasonic sensor that detects the presence of human on a particular distance. Once the garbage reaches the threshold level, ultrasonic sensor will trigger the GSM Modem, which will continuously alert the required authority until the garbage in the dustbin is squashed. Once the dustbin is squashed, people can reuse the dustbin. At regular intervals dustbin will be squashed. Once these smart bins are implemented on a large scale, by replacing our traditional bins present today, waste can be managed efficiently as it avoids unnecessary lumping of wastes on roadside. Foul smell from the rotten wastes that remain untreated for a longer time, due to negligence of authorities and carelessness of public may lead to long-term problems. Breeding of insects and mosquitoes can create nuisance around promoting unclean environment. This may even cause dreadful diseases.

Propeller Hub Repair With Cold Spray Technology (CST Process)
Authors:- Dupally Naval Venkata, Narasimha Kishore Yadav

Abstract:-The current process of the repair by Cold Spray Technology is the restoration of the Aircraft Propeller components and Hub is one of the dynamically stressed components containing aluminum and its alloys and these are the perfect components for the cold spray applications. This application is based on the material of the component that is manufactured and can be repaired with. Most of these cold spray repairing materials are pretreated according to the manufactured material or alloys. Most of the material or metals selected for the cold spray application are compared with the physical, chemical, and mechanical properties of the manufactured components. To optimize the perfect spray bond the closest parameters are subsequently selected, the spay material is applied, and the component is repaired with help of Helium and nitrogen to replace the affected area with spraying powder. Then after the spray, the component is machined in the way it was new and according to OEM standards. This process can be worked on not only Aircraft components, but also any metals used in mechanical, automotive, aerospace, oil and gas, and many other industries where metals need repair and restoration of the damaged area.

E-Waste Management
Authors:- Prof. Kharde Ashwini Ganpat, Prof. Prashant Sanpat Kale, Prof. N. M. Garad, Prof. A. S. Shirsath

Abstract:-Electronic waste, e-waste, e-scrap, or waste Electrical and Electronic Equipment (WEEE) describes discarded electrical devices. There is a lack of consensus as to whether the term should apply to resale, reuse, and refurbishing industries, or only to product that cannot be used for its intended purpose. Informal processing of electronic waste in developing countries may cause serious health and pollution problems, though these countries are also most likely to reuse and repair electronics. Some electronic scrap components, Such as CRTs (Cathode Ray Tubes), may contain contaminants such as lead, cadmium, beryllium, or brominated flame retardants. Even in developed countries recycling and disposal of e-waste may involve significant risk to workers and communities and great care must be taken to avoid unsafe exposure in recycling operations and leaching of material such as heavy metals from landfills and incinerator ashes. Scrap industry and USA EPA (United States Environmental Protection Agency) officials agree that materials should be managed with caution, but many believe that environmental dangers of used electronics have been exaggerated.

Challenges at the Time of Covid-19, and Innovation to Combat with Situation
Authors:- Sandeep Kumar, Unsa Fatima, Ranju Shah, Upma Gupta

Abstract:-21st century was moving ahead in a pleasant way. Suddenly it was hit by the pandemic, Covid-19, which changed the life of everybody. Offline mode was transformed by the online mode. The platforms such as Google Meet, Webex, Zoom helped in a tremendous way to connect people and also to complete their work from the available resources at home.E- commerce was atits boom during this period and those who grabbed the opportunities initial- ly were awardedconsequently. On thecontrary,those who were operating in physical mode were severely hit. Foronline education,Courser,Byjus are working to help the students in their respected fields ofwork. This paper will cover the technological aspects during COVID-19.

Aadhar Based Fingerprint Electronic Voting Machine
Authors:- Bhakti Salvi, Mrs. Rupali Shekokar

Abstract:- The main aim of the voting is to express their thoughts related to choose your government, political leader, citizen initiatives and so on. It is an important task for the election team to conduct fair voting in respective country. Every country spent lot of money to make election without any fraud and rampage free. But, in current situation it has become very normal for some sources to make illegal voting that may lead to a result contrary to the actual judgment of the people [2]. We refer some paper and design one machine to solve the above problem. By taking help of biometric system (finger print scanning) will make this project more secure and trustable. Biometric system has been increase speed of the system and accuracy. It also provide the security to system, avoid fake and duplicate voting etc. System uses to identify the user is thumb impression and Aadhar card number. Because as we know that Aadhar card is government trusted identification card and thumb impression of every person on the earth (human being) has unique pattern. Thumb impression increase security in the system, and that is the main task of this system, increase security. In this, as a pre-polling step create database consisting of the Aadhar card number and thumb impressions of all the eligible voters. At the time of elections, the thumb impression and Aadhar card number of a voter is entered as input to the system [1]. And then, that database records compared with the entered thumb impression and Aadhar card number. If that entered pattern and Aadhar card number matches with the database of the thumb impression and Aadhar card number respectively, grant permission to cast a vote. And in case any repetition in vote and if pattern doesn’t match with the records of the database present in system, for that particular person permission to cast a vote is denied and system not go for next step, it come out from processes. And in other case the pattern match but Aadhar card number doesn’t match with the records present in system, for that particular person also permission to cast a vote is denied and system not go for next step, it come out from processes. To cast a vote must is to match both Aadhar card number and finger print of that particular person, than and than only system allow for next step (For voting). As per voting going on counting has been done paralleled. This system maintenance cost is less and overall cost for complete election process is very less.

Underground Fault Cable Detection Using Wireless Technology
Authors:- P.G. Scholar Manjula V, Asst. Prof. P. Sumathi, HOD. P. Anlet Pamila Suhi

Abstract:- Detecting fault cable system proposes fault location model for underground power cable using microcontroller. Fault location models are to determine the distance of underground cable fault from base station in kilometers. This project uses the simple concept of ohm’s law. When any fault like short circuit occurs, voltage drop will vary depending on the length of fault in cable, since the current varies. A set of resistors are therefore used to represent the cable and a dc voltage is fed at one end and the fault is detected by detecting the change in voltage using a analog to voltage converter and a microcontroller is used to make the necessary calculations so that the fault distance is displayed on the LCD display.

Determination of Unsaturated Hydraulic Conductivity and Diffusivity as a Function of Moisture Contents and Soil Suctions
Authors:- ADAMU Cornelius Smah, UDOJI Braveson Obiefo, EKOJA Omeyi Faith, SALIHU Buhari Salam, IKYAPA Tertese Peter, BELLO Sikiti Garba

Abstract:- This study on unsaturated hydraulic conductivity and diffusivity of a soil was conducted at Agricultural engineering experimental plot, Ahmadu Bello University, Zaria. Experimental conductivity was carried out from five profile pits with samples taken from (15, 30, 45 and 60cm) depths. The saturated conductivity (Ks) was first determined in the laboratory using the constant head method, the gravimetric moisture contents were estimated in the laboratory using the pressure plate extractor by applying the required suctions at (0, 0.1, 0.3,1,5,10 and 15) bars. The bulk densities of the samples collected were also estimated. The volumetric moisture contents were determined by multiplying the gravimetric moisture contents with their corresponding bulk densities. Jackson’s model of 1973 was applied to determine the unsaturated hydraulic conductivity at each moisture content using the formula Ki =Ks(θi/θs) (∑_(j=i)m⌊(2j+1)-2i)φj-2⌋)/(∑_(j=1)m⌊(2j-1)φj-2⌋). The soil suction and the volumetric moisture contents were related to K(φ)=〖aφ〗mm and K(θ)=bθm . Where K is the degree of saturation or unsaturation. φ is the volumetric moisture content and θ is the soil suction head, a, b are the empirical constants while m and n are constants for the measure of the steepness. Mualem Van Gunatchen model of 1976 predicted a formula which was used in determining the hydraulic diffusivity by multiplying the conductivity to the differential of this relationφ=aθm. Major findings of this study revealed that the value of the diffusivity as a function of volumetric moisture content decreases down the profile pit, this could be as a result of the existence of materials in the soil with increase in the suction. The coefficient of determinant (R²) decreases down the profile, it was also observed that the bulk density (B) and Porosity affect the hydraulic conductivity (Ks) and diffusivity (D) of the soil on site.

A Review Article of PV Based Power Generation and Power Quality Improvement Using SSSC Power Compensation
Authors:- Amarkant Shukla, Dr. Arvind Kumar Sharma

Abstract:-In this paper we investigate the controlling and enhancing power flow in a transmission line using a Static Synchronous Series Compensator (SSSC). The Static Synchronous Series Compensator is used to investigate the device in controlling active and reactive power as well as damping power system oscillations in transient mode. The SSSC device is equipped with SOURCE ENERGY to absorb or supply the active and reactive power to or from the line. Various IEEE bus systems have been stabilized using this FACTS device. The results are obtained by simulating the various power systems in MATLAB/SIMULINK.

Railway Track Crack Detection System Using Arduino Microcontroller and Gps Notification
Authors:- P.G. Student Aruna A, Asst. Prof. P. Anlet Pamila Suhi (HOD)

Abstract:- The Indian Railways has one of the largest railway networks in the world, criss- crossing over 1,15,000 km in distance, all over India. However, with regard to reliability and passenger safety Indian Railways is not up to global standards. Among other factors, cracks developed on the rails due to absence of timely detection and the associated maintenance pose serious questions on the security of operation of rail transport. A recent study revealed that over 25% of the track length is in need of replacement due to the development of cracks on it. Manual detection of tracks is cumbersome and not fully effective owing to much time consumption and requirement of skilled technicians. This project work is aimed towards addressing the issue by developing an automatic railway track crack detection system. This work introduces a project that aims in designing robust railway crack detection scheme (RRCDS) using TSOP IR RECEIVER SENSOR assembly system which avoids the train accidents by detecting the cracks on railway tracks. And also capable of alerting the authorities in the form of SMS messages along with location by using GPS and GSM modules. The system also includes distance measuring sensor which displays the track deviation distance between the railway tracks.

A Review on Thermal Design Analysis of Piston Using RSM Method
Authors:- M.Tech Scholar Rajat Singh, Prof. Brijendra Kumar Yadav

Abstract:- A piston is a component of reciprocating IC-engines. Piston is the component which is moving that is contained by a cylinder and was made gas-tight by piston rings.A mathematical model is formulated based on the simulation result values of total deformation, stress and first ring groove temperature. The Piston during the working condition exposed to the high gas pressure and high temperature gas because of combustion. At the same time it is supported by the small end of the connecting rod with the help of piston pin (Gudgeon pin). The gas pressure given 20 Mpa is applied uniformly over top surface of piston (crown) and arrested all degrees of freedom for nodes at upper half of piston pin boss in which piston pin is going to fix. The statistical ‘‘Design-Expert 8.0.7.1” software has been usedto study the regression analysis of simulation data and to drawthe response surface plot. The statistical parameters were estimatedby using ANOVA. The objective of the study is to minimize the mass. The optimum combination of the influencing parameters for the mass can be found using Response Surface Method.

Thermal Design Analysis OF Piston Using Rsm Method
Authors:- M. Tech. Scholar Rajat Singh, Prof. Brijendra Kumar Yadav

Abstract:- A piston is a component of reciprocating IC-engines. Piston is the component which is moving that is contained by a cylinder and was made gas-tight by piston rings. A mathematical model is formulated based on the simulation result values of total deformation, stress and first ring groove temperature. The Piston during the working condition exposed to the high gas pressure and high temperature gas because of combustion. At the same time it is supported by the small end of the connecting rod with the help of piston pin (Gudgeon pin). The gas pressure given 20 Mpa is applied uniformly over top surface of piston (crown) and arrested all degrees of freedom for nodes at upper half of piston pin boss in which piston pin is going to fix. The statistical ‘‘Design-Expert 8.0.7.1” software has been used to study the regression analysis of simulation data and to draw the response surface plot. The statistical parameters were estimated by using ANOVA. The objective of the study is to minimize the mass. The optimum combination of the influencing parameters for the mass can be found using Response Surface Method. It is found that Height of top land and crown thickness has a dominant effect on total deformation, stress, mass and first ring temperature and The optimal piston mass is determined at height of top land = 2 mm and Crown thickness= 10 mm is 174.43 g.

Renewable Energy Based Power Generation Systems
Authors:- M.Tech. Pooja Vaishya, Prof. Barkha Khambra

Abstract:- The microgrid has shown to be a promising solution for the integration and management of intermittent renewable energy generation. This paper looks at critical issues surrounding microgrid control and protection. It proposes an integrated control and protection system with a hierarchical coordination control strategy consisting of a stand-alone operation mode, a grid-connected operation mode, and transitions between these two modes for a microgrid. To enhance the fault ride-through capability of the system, a comprehensive three-layer hierarchical protection system is also proposed, which fully adopts different protection schemes, such as relay protection, a hybrid energy storage system (HESS) regulation, and an emergency control. The effectiveness, feasibility, and practicality of the proposed systems are validated on a practical photovoltaic (PV) microgrid. This study is expected to provide some theoretical guidance and engineering construction experience for microgrids in general.

A Review Article of Power Management in Pv-Battery-Hydro Based Stand Alone Microgrid
Authors:- Sumit Singh, Vivek Anand

Abstract:- This works mainly on a Power Management System for a micro-grid system powered by a hybrid power generation system consisting of frequency control, power control, power management and solar photovoltaic (PV)- battery-hydro based micro-grid (MG) load. Therefore, power and frequency control allows for the balance of active energy and auxiliary services such as active energy support, source of current harmonics reduction and voltage reduction harmonics where common encounters.

AI-Enabled Secure Monitoring of Computer Vision Data in 5G IoT-Based Healthcare Systems
Authors:- Research Scholar Ms. Komal Garg, Professor Dr. Narender Kumar

Abstract:- The integration of 5G-enabled IoT networks has significantly transformed the healthcare sector, enabling real-time monitoring, data collection, and advanced diagnostics through the Internet of Medical Things (IoMT). This study investigates the application of artificial intelligence (AI) models for securing sensitive patient data in IoMT networks, addressing the escalating threats of cyberattacks and privacy violations. By leveraging historical datasets, the research develops an AI-driven framework for anomaly detection and threat classification, optimizing data security through federated learning, encryption, and adaptive defences. The results demonstrate the model’s exceptional performance, with accuracy rates exceeding 99% across various threat scenarios and robust anomaly detection capabilities validated through real-world simulations. Additionally, the framework achieves a high AUC score of 0.999, showcasing its reliability and precision in securing IoMT networks. These findings underscore the efficacy of the proposed approach in mitigating security risks, enhancing system reliability, and ensuring the seamless operation of smart healthcare systems. This work highlights the critical role of 5G and AI technologies in creating robust, secure, and scalable IoMT ecosystems, contributing to improved healthcare accessibility and patient outcomes.

DOI: 10.61137/ijsret.vol.7.issue1.192

The Concept of UNIX Infrastructure Optimization for Genomic Data Processing

Authors: Faria Mahmud, Khaled Noor, Sabrina Yasmin, Tanmoy Hossain

Abstract: The unprecedented growth of genomic data driven by next-generation sequencing technologies has imposed complex computational demands on bioinformatics infrastructure. UNIX-based systems comprising Solaris, AIX, and Linux form the backbone of genomic data processing environments due to their reliability, performance, and rich toolchain support. However, their default configurations are seldom tuned for the high-throughput, memory-intensive, and I/O-sensitive nature of genomic workloads. This review explores the critical need for infrastructure-level optimization in UNIX environments to support workflows such as sequence alignment, variant calling, and RNA-Seq analysis. It presents a detailed examination of system-level strategies including NUMA-aware CPU allocation, memory page tuning, ZFS and GPFS storage optimization, network throughput enhancement, and scheduler configuration using SLURM and PBS. Case studies from academic and clinical domains highlight the real-world impact of these optimizations on pipeline performance and resource efficiency. The article also addresses compliance considerations under HIPAA and GDPR, demonstrating how audit controls and data encryption can be embedded into UNIX configurations. Looking forward, the review outlines emerging trends such as AI-assisted infrastructure tuning, containerization of genomic workflows, and the integration of persistent memory and cloud bursting strategies. Collectively, this review provides system administrators, bioinformatics engineers, and IT architects with a comprehensive blueprint for transforming UNIX platforms into high-performance, secure, and scalable environments tailored for genomics.

DOI: https://doi.org/10.5281/zenodo.15846976

Hydrogen Operated Internal Combustion Vehicle

Authors: Mr. P.G.Gavade

Abstract: Now a days in every country like India we have a scarcity of fossil fuels. A hydrogen vehicle is a vehicle that uses hydrogen as its onboard fuel for motive power. Hydrogen vehicles include hydrogen fueled space rockets, as well as automobiles and other transportation vehicles. The credential part of this paper gives the theoretical application of hydrogen cells in vehicles of the modern century for lower emissions and higher efficiency. As the quantity of fossil fuels are very limited that is why we need an alternative source of energy or the fuels so we can save the fossils fuels for our future generation and the hydrogen.

DOI: https://doi.org/10.5281/zenodo.15964355

The Consumer & Retail Investor in the FinTech Era: Opportunities and Risks of Digital Finance

Authors: Vittal Jadhav

Abstract: The move to reshape the financial services offering has greatly benefited from the appearance of Financial Technology (FinTech), namely for consumers and retail investors. The latest wave of FinTech innovations, which include digital payment solutions, robo-advisory platforms, peer-to-peer (P2P) lending, and blockchain-based services, has drastically changed how individuals interact with money and investments. This paper considers the manifold opportunities that FinTech affords (financial inclusion, efficiency, personalization, and cost-cutting) in contrast to the corresponding risks (cybersecurity, data privacy, regulatory, and market volatility). An overview of the literature on FinTech prior to 2020 is contextualized, and the methodology, which compares case-based data together with qualitative analysis, is used to assess the services. It is supported by figures, flow charts, and comparative tables. Beyond the democratization of FinTech, the results show the power that FinTech offers by way of economic empowerment and the systemic vulnerabilities it creates when it fails. The paper suggests a balanced regulatory playing field alongside best practices for leaders, FinTech providers, and other stakeholders to responsibly tap FinTech’s potential.

DOI:

The Consumer & Retail Investor in the FinTech Era: Opportunities and Risks of Digital Finance

Authors: Vittal Jadhav

Abstract: The move to reshape the financial services offering has greatly benefited from the appearance of Financial Technology (FinTech), namely for consumers and retail investors. The latest wave of FinTech innovations, which include digital payment solutions, robo-advisory platforms, peer-to-peer (P2P) lending, and blockchain-based services, has drastically changed how individuals interact with money and investments. This paper considers the manifold opportunities that FinTech affords (financial inclusion, efficiency, personalization, and cost-cutting) in contrast to the corresponding risks (cybersecurity, data privacy, regulatory, and market volatility). An overview of the literature on FinTech prior to 2020 is contextualized, and the methodology, which compares case-based data together with qualitative analysis, is used to assess the services. It is supported by figures, flow charts, and comparative tables. Beyond the democratization of FinTech, the results show the power that FinTech offers by way of economic empowerment and the systemic vulnerabilities it creates when it fails. The paper suggests a balanced regulatory playing field alongside best practices for leaders, FinTech providers, and other stakeholders to responsibly tap FinTech’s potential.

DOI: https://doi.org/10.5281/zenodo.16312717

The Consumer & Retail Investor in the FinTech Era: Opportunities and Risks of Digital Finance

Authors: Vittal Jadhav

Abstract: The move to reshape the financial services offering has greatly benefited from the appearance of Financial Technology (FinTech), namely for consumers and retail investors. The latest wave of FinTech innovations, which include digital payment solutions, robo-advisory platforms, peer-to-peer (P2P) lending, and blockchain-based services, has drastically changed how individuals interact with money and investments. This paper considers the manifold opportunities that FinTech affords (financial inclusion, efficiency, personalization, and cost-cutting) in contrast to the corresponding risks (cybersecurity, data privacy, regulatory, and market volatility). An overview of the literature on FinTech prior to 2020 is contextualized, and the methodology, which compares case-based data together with qualitative analysis, is used to assess the services. It is supported by figures, flow charts, and comparative tables. Beyond the democratization of FinTech, the results show the power that FinTech offers by way of economic empowerment and the systemic vulnerabilities it creates when it fails. The paper suggests a balanced regulatory playing field alongside best practices for leaders, FinTech providers, and other stakeholders to responsibly tap FinTech’s potential.

DOI: https://doi.org/10.5281/zenodo.16312717

 

The Consumer & Retail Investor in the FinTech Era: Opportunities and Risks of Digital Finance

Authors: Vittal Jadhav

Abstract: The move to reshape the financial services offering has greatly benefited from the appearance of Financial Technology (FinTech), namely for consumers and retail investors. The latest wave of FinTech innovations, which include digital payment solutions, robo-advisory platforms, peer-to-peer (P2P) lending, and blockchain-based services, has drastically changed how individuals interact with money and investments. This paper considers the manifold opportunities that FinTech affords (financial inclusion, efficiency, personalization, and cost-cutting) in contrast to the corresponding risks (cybersecurity, data privacy, regulatory, and market volatility). An overview of the literature on FinTech prior to 2020 is contextualized, and the methodology, which compares case-based data together with qualitative analysis, is used to assess the services. It is supported by figures, flow charts, and comparative tables. Beyond the democratization of FinTech, the results show the power that FinTech offers by way of economic empowerment and the systemic vulnerabilities it creates when it fails. The paper suggests a balanced regulatory playing field alongside best practices for leaders, FinTech providers, and other stakeholders to responsibly tap FinTech’s potential.

DOI: https://doi.org/10.5281/zenodo.16314798

Architectural Foundations For AI-Driven Intelligent Automation In Salesforce Ecosystems

Authors: Santhosh Reddy BasiReddy

Abstract: Enterprise CRM platforms are rapidly evolving from traditional transactional systems into intelligent decision hubs that orchestrate complex, end-to-end business processes across distributed cloud ecosystems. Salesforce increasingly serves as the central backbone for automation, analytics, and system integration inregulated, data-intensive, and high-scale enterprise environments. As artificial intelligence technologies mature and move from experimental use cases to production-grade deployments, organizations face significant architectural and operational challenges in preparing Salesforce ecosystems for AI-driven intelligent automation. These challenges include ensuring scalability, minimizing system coupling, maintaining governance and auditability, and integrating adaptive intelligence without disrupting core business workflows. This work synthesizes architectural, process, and governance principles into a unified framework for preparing Salesforce ecosystems for AI-driven intelligent automation.

DOI: http://doi.org/10.5281/zenodo.18014554

Resilient Connectivity Models For Next-Generation Wireless Cloud–IoT Platforms

Authors: Kritika Somvanshi

Abstract: The rapid growth of the Internet of Things, combined with advancements in cloud computing and next-generation wireless technologies, has created unprecedented opportunities for intelligent, interconnected systems. These systems, often referred to as wireless cloud-IoT platforms, rely on seamless connectivity to enable real-time data exchange, remote management, and advanced analytics. However, the increasing number of connected devices, diversity of communication protocols, and dynamic network conditions pose significant challenges to maintaining reliable and resilient connectivity. Resilient connectivity in this context refers to the ability of the network to maintain service continuity, recover from failures, and adapt to changing environmental and operational conditions without significant degradation in performance. This review examines the state-of-the-art approaches for achieving resilient connectivity in next-generation wireless cloud-IoT platforms, highlighting the key technological enablers such as 5G and 6G networks, low-power wide-area networks, edge and fog computing, and software-defined networking. It also provides a detailed discussion of fault-tolerant designs, adaptive and resource-aware connectivity models, and security-driven approaches that ensure continuity and reliability in heterogeneous IoT environments. By comparing existing methods and analyzing their performance metrics, this review identifies gaps in current research and outlines open challenges, including scalability, energy efficiency, and security. Furthermore, the review explores emerging directions such as artificial intelligence-driven network adaptation, digital twin integration, and autonomous connectivity management. The insights provided in this work are intended to guide researchers, engineers, and practitioners in designing next-generation wireless cloud-IoT platforms that are robust, flexible, and capable of supporting the increasing demands of smart applications. Overall, this article emphasizes the importance of resilient connectivity as a foundational requirement for the successful deployment and operation of future IoT ecosystems, offering a comprehensive overview of current solutions and potential pathways for further innovation.

DOI: http://doi.org/10.5281/zenodo.18162844

Risk-Aware Architectural Design For Distributed IoT Systems Over Wireless Clouds

Authors: Adiv Jainwal

Abstract: The rapid evolution of the Internet of Things (IoT) and wireless cloud computing has led to highly distributed system architectures that support large-scale, data-intensive, and latency-sensitive applications. While these architectures offer improved scalability and flexibility, they also introduce significant risks related to security, privacy, reliability, performance, and operational management. Traditional IoT architectural designs primarily focus on functional and performance requirements and often lack explicit mechanisms to address these risks. Consequently, risk-aware architectural design has emerged as a critical paradigm for enhancing the robustness and trustworthiness of distributed IoT systems over wireless clouds. This paper presents a comprehensive review of risk-aware architectural design approaches for distributed IoT environments integrated with wireless cloud infrastructures. It examines the fundamental architectural principles, identifies key risk factors across multiple system layers, and analyzes existing risk-aware design strategies, including secure-by-design, privacy-preserving, and resilience-oriented architectures. The review further explores architectural frameworks and reference models that incorporate risk management as a core design component and evaluates their applicability across various IoT application domains such as smart cities, industrial IoT, healthcare, and smart energy systems. Through a comparative analysis of existing solutions, the paper highlights current limitations, trade-offs, and research gaps. Finally, it outlines open challenges and future research directions to guide the development of adaptive, scalable, and sustainable risk-aware IoT architectures. This review aims to support researchers and practitioners in designing resilient distributed IoT systems capable of operating securely and efficiently in dynamic wireless cloud environments.

DOI: http://doi.org/10.5281/zenodo.18162850

Scalable Data Integration Architectures For Multi-Source Enterprise Platforms: An Empirical Evaluation Of ETL And ODI

Authors: Dr. Jonathan Reed, Dr. Emily Carter, Michael Thompson, Dr. Sarah Williams, David Anderson, Chaitanya Srinivas

Abstract: Modern enterprise platforms increasingly depend on data from multiple heterogeneous sources such as legacy systems, cloud applications, and real-time streams, making scalable and efficient data integration a critical challenge. This paper presents a comprehensive study of data integration architectures for multi-source enterprise environments, with a particular focus on Extract, Transform, Load (ETL) processes and Oracle Data Integrator (ODI) implementations. It evaluates centralized, distributed, and hybrid architectural models to determine their effectiveness in handling large-scale and high-velocity data workloads. An empirical analysis based on real-world enterprise scenarios is conducted to assess key performance factors including scalability, data consistency, fault tolerance, and maintainability. The study further investigates the role of ETL pipelines in enabling structured data transformation and highlights how ODI’s declarative approach and pushdown optimization techniques improve processing efficiency. Additionally, best practices such as parallel processing, metadata-driven integration, and incremental data loading are explored to enhance system performance. The results demonstrate that the integration of robust ETL strategies with ODI-based optimizations significantly improves throughput and reduces latency in complex enterprise systems, providing valuable insights for designing scalable and reliable data integration solutions.

DOI: https://doi.org/10.5281/zenodo.19765226

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