IJSRET Volume 7 Issue 2, Mar-Apr-2021


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.

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