Sensor Based Automatic Fertigation System
Authors:- S. MuthuKumar, M.Naveenraja, V. NaveenKumar, Dr. S.RajaRanganathan
Abstract: – In sensor based automatic system, the irrigation and the fertilizer supplying system can be automated. Our project comprises of two modules irrigation system and the fertilizer supplier system. In irrigation system, the moisture of the soil can be found using the moisture sensor which can be fixed at the different parts of the farm land. For the crops planted, the required water content can be varied with types. Based on the sensor values obtained from the land, the controller will regulate the required amount of water quantity to the crops. This will terminate the motor when the required level reached. In the fertilizer supply system, the fertilizer content present in the soil can be found using the PH sensor fixed at the farm lands. This will find the nutrient content found in the soil. This will supply the fertilizer to the soil based on the sensor values which can be fixed at the farm lands. This will reduce the over watering and over fertilizer supplying to the crops. As the required quantity of water and fertilizer will be supplied to the crops, this will increase the productivity of the crops and improve the texture of the soil.
Predicting Diabetes in Medical Datasets Using Machine Learning Techniques
Authors:- M.Tech. Scholar Arvind Aada, Prof. Sakshi Tiwari
Abstract: – Healthcare industry contains expansive and delicate information and should be taken care of all around cautiously. Diabetes Mellitus is one of the developing amazingly lethal maladies everywhere throughout the world. Medicinal experts need a dependable forecast framework to analyze Diabetes. Distinctive AI methods are helpful for analyzing the information from differing points of view and synopsizing it into profitable data. The openness and accessibility of enormous measures of information will almost certainly give us helpful learning if certain information mining systems are connected on it. The principle objective is to decide new examples and after that to decipher these examples to convey huge and valuable data for the clients. Diabetes adds to coronary illness, kidney malady, nerve harm and visual deficiency. So mining the diabetes information in productive way is a urgent concern. The information mining strategies and strategies will be found to locate the suitable methodologies and systems for proficient grouping of Diabetes dataset and in removing important examples. In this investigation a restorative bioinformatics examinations has been cultivated to anticipate the diabetes. The R programming was utilized as digging device for diagnosing diabetes. The Pima Indian diabetes database was obtained from UCI storehouse utilized for investigation. The dataset was considered and broke down to fabricate compelling model that foresee and analyze the diabetes ailment. In this examination we plan to apply the bootstrapping resembling method to upgrade the exactness and after that applying Naïve Bayes, Decision Trees and k Nearest Neighbors’ (kNN) and think about their execution.
Analysis and Research of System Security Based on Android
Authors:- M. Tech. Scholar Ronak Jain, Prof. Sakshi Tiwari
Abstract: – Android is a savvy versatile terminal working stage center on Linux. Be that as it may, because of its open-source programming and programmable structure character, it drives the Android framework helpless against get infection assaults. This paper has profoundly inquired about from the Linux framework security system, Android-explicit security instruments and other assurance components. Also, on this premise, Android gadgets have accomplished firmly watched on ordinary state. With the goal that aggressors cannot utilize the portion module or center library to get most elevated access consent and be assaulted. In the mean time, to additionally reinforce the security of Android gadgets, it empowers them to appropriately deal with the high-hazard danger. This paper likewise fortified interruption identification framework (HIDS) in light of the host so as to identify noxious programming and reinforce the Android framework level access control.
Analysis of the Impact of Clear Air Atmospheric Conditions on Propagation Loss at Microwave Frequencies
Authors:- Ezeh, Ikechukwu H., Onwuzuruike, V. Kelechi
Abstract: – In the paper, the analysis of the impact of clear –air atmospheric conditions on propagation loss at microwave frequencies is presented. Particularly, the study focused on the impact of variation in point refractivity gradient on multipath fade depth based on the International Telecommunication Union (ITU) recommendation P.530-17 quick planning applications method. The point refractivity gradient depends on the vertical profile of the primary radio climatic parameters, namely, atmo spheric temperature, pressure and relative humidity. Accordingly, the Nigerian Meteorological Agency (NIMET) Radiosonde dataset of the atmospheric temperature, pressure and relative humidity for 2014 in Cross River state were used in the study. The twelve months (2014) Radio sonde dataset of the atmospheric temperature, pressure and relative humidity at the ground level and at height of 65 m above ground were used to compute the refractivity (N) and point refractivity gradient (dN1) for each of the 12 months along with the annual average values of N and dN1. The results show that the ITU annual average value of dN1= –400 is over 200 % of the annual average value of -131.86 obtained from the locally measured data. For each of the 12 months multipath fade depth is computed using the point refractivity gradient obtained in the study along with parameters of a 10 km case study microwave link. The results show that at the frequency of 8 GHz and percentage of time Pw (%) of 0.01 % that a given fade depth is exceeded in the average worst month, the maximum fade depth of 18.95865 dB occurred in October whereas the lowest fade depth of 14.10459 dB occurred in April. Also, the multipath fade depth is inversely proportional to the point refractivity gradient. Furthermore, the result for the multipath fade depth at Pw = 0.01 % and frequencies of 8 GHz , 16 GHz and 28 GHz for the 12 months shows that multipath increase with frequency and the ITU dN1 value continues to maintain the highest multipath fade depth in each of the frequencies considered. Also, the result for the multipath fade depth at the frequency of 16 GHz and Pw of 0.001 %, 0.01 % and 0.1 % for the 12 months shows that multipath decrease with Pw and the ITU dN1 value continues to maintain the highest multipath fade depth in each of the Pw values considered. The ideas presented in this paper is relevant to microwave communication link designers as it enables them to determine the appropriate fade margin that can be specified to accommodate the multipath fade depth that can occur in a given link.
Zigbee Based Routing Security on Home Automation
Authors:- M.Tech.Scholar Amol Ramdas Kasar, Prof. Sakshi Tiwari
Abstract: – Mechanization is a huge field and now daily can be actualized anyplace relying on the application. ZigBee convention IEEE 802.15.4 remote standard can be utilized to set up system for some particular application reason. ZigBee based home robotization remote sensor system can be executed with little starting expense and can be valuable to control fans, lights and other home apparatuses which activity can be controlled with the assistance of a microcontroller. The home computerization can be helpful system for physically incapacitated people just as seniority individual and a similar system can be utilized to control mechanical applications too.
Design and Implementation of Internet of Things Based Smart Mirror Using Raspberry Pi
Authors:- Prof.Dhanashree R. Patil, Apurva S. Ghayalkar, Sayali N.Patil, Shweta P. Patil, Pavan P. Patil
Abstract:- In this paper, we describe the design and development of a futuristic mirror that offers simplified and customizable services to the home environment. .It is a small contribution towards smart home. The mirror interface provides users with the versatility needed for better management and integration of daily tasks. On a par with the recent advances in the Internet of Things standards and applications, the mirror is designed to enable residents to control the household smart appliances and access personalized services. The proposed system is set apart from others for its provision of various customized information services for user profile generation.
Fast Image Dehazing Method Based On Homomorphism Filtering and Contrast Enhancement
Authors:- Neeta Joy, Asst. Prof. Jyothi Johnson
Abstract:- Images captured via camera in the bad weather conditions like hazy or foggy ones would result in degradation of images. This is mainly due to the scattering of atmospheric light. This could lead to the deterioration of the image due to the scattering of atmospheric particles and due to the presence of haze. In this paper, a fast algorithm for single image dehazing is proposed using the homomorphism filtering and then using the contrast enhancement technique. Firstly, to accurately measure the atmospheric light an additional channel method is proposed based on quad-tree subdivision. Here the average grays and gradients are used as assessment criteria. Secondly, after finding the atmospheric light portion in the input image filtering is being applied. For this, homomorphism filtering technique is used. This is a generalized technique for both signal and image processing, involving a nonlinear mapping to a different mapping to a different domain in which linear filter techniques are applied, followed by mapping back to the original domain . At last the haze-free image is obtained as the result of atmospheric scattering model. Numbers of both subjective and objective evaluations are being done with the aid of experiments which shows that this algorithm can clearly and naturally recover the image, with at most clarity at the edges where there is sudden changes in the depth of field. Here the algorithmic time complexity is the linear function of the image size. This has advantages in the running time my maintaining balance between the running times and processing.
Commutation Torque Ripple Reduction in BLDC motor Using M-SEPIC Converter
Authors:- K. ThangaPushpam, S. Radhika, I. TamilSelvi, M. VinothKumar, S. Nagaraj
Abstract:- The paper presents new power converter topology to suppress the torque ripple reduction due to the phase current commutation of brushless DC motor. The modified sepic converter is used in a converter circuit it has high static gain for a given duty cycle and step –up-output. Cuk converter has produce the inverted output. The M-SEPIC is a modification of the basic SEPIC. It is superior to the opposite converters each in terms of the input current, purity and potency. It shows very little overshoot or ringing. And also the switching loss is reduced and has low THD value than Cuk converter so it has high static gain and increased efficiency. The theoretical analysis and framework, using MATLAB/ Simulink environment, are given to illustrate the proposed method and the performance is compared with conventional system. And the experimental results are provided for verification of the BLDC drive system.
Design and Implementation of Quad copter
Authors:- Gaurav Gadge, Ankita Ledey, Sourabh Pawer, Gulshan Balpande
Abstract:- The paper presents new power converter topology to suppress the torque ripple reduThis paper presents the design and implementation of an aerial surveillance quad copter for search and rescue application. The aim of this research is to develop a real-time, compact and cost effective drone that will be capable of search and rescue operation and the class is intended to provide the student with both theoretical and practical knowledge in the areas of electronic engineering and design, system integration hardware programming, and control system design and implementation. The frame of the quad copter was made up of very light glass fiber to ensure stability while flying and also to reduce weight of the overall material. The entire design generated a compact and low cost surveillance quad copter with weight of approximately 1.50 kg; which can take photographs from environments with the aid of the onboard mounted camera. Live streaming was done with the help of laptop during fight.
Crop Prediction System
Authors:- Ruchira Nerkar, Bhakti parkhe, Sanjana Bhandure Prof. Bhushan Chaudhary
Abstract:- In recent years, different emerging technologies and applications were introduced for information technology, and now the information technology has become huge part of our day to day life. Especially for agriculture, the yield prediction is very popular among farmers these days. This may contribute to the proper selection of crops for their agricultural development activities based on a farmers experience on a particular field and crop. In earlier stage yield prediction system used data mining techniques in order to predict the crop, analyzed, fertilize and what on. And now-a-days agricultural forecast is becoming more complex and more difficult due to global warming and abnormal weather. To carry on this tasks farmer needs a building of an effective agricultural yield forecasting system on real time. So, crop prediction system is the most fundamental system, which gives soil temperature, soil moisture, humidity, air temperature, of the soil. This helps farmer to analyze which crop should be cultivated, with respect to atmosphere. In this project we use Arduino Uno board to control the entire task which is introduced in programming. And firstly the system is mounted on a particular place in the farm after that the supply is connected to switch board (extension board) and then by switching on the supply it will start and by identifying the parameter’s by the sensors it will displayed on the 16 x 2 LCD screen on system or else by using the router the user can also access the system from anywhere to check the parameters. This system is smart in a technology and will help the future digital world to be more advanced by this system the farmer would get a clear vision about which crop should be cultivated and suitable for the weather.
Analysis of Classification Algorithms using Machine Learning
Authors:- M. Tech. Scholar Soniya Rathore, Asst. Prof. Ankur Taneja, Asst. Prof. Lakhan Singh Sisodiya
Abstract:- In this work our main focus is on regression which is one of the most important methods in machine learning algorithm. Regression is a statistical approach that is used to find the relationship between variables. It is basically used to predict the outcome from the given dataset. In this work we will discuss the regression algorithms which are available in machine learning algorithm and propose one algorithm that will have less train error and test error as compared to other existing algorithm. The accuracy measure will be in the form of train and test error.
Oxcy Business Suite Application Using CRM,ERP and Supply Chaining For Small and Middle Scale Company
Authors:- Asst. Prof. S. Malarvizhi, M. Shivaranjani, M. Vidhya
Abstract:-Business suite application is depends upon two main things called Enterprise resource planning and Customer relationship management. By using this two methods we can improve both customer and enterprise growth. This application is specifically developed for small and middle scale Companies. Here we also used sorting algorithm, supply chaining method.
A Survey on Robust Intrusion Detection System Methodology and Features
Authors:- M. Tech. Scholar Jyotsna Purohit, Asst. Prof. Jayshree Boaddh, Asst.Prof. Akrati Shrivastava
Abstract:- To improve network security different steps has been taken as size and importance of the network has increases day by day. In order to find intrusion in the network IDS (Intrusion detection system) systems were developed which were broadly classified into two category first was anomaly based and other was misuse based. In this paper survey was done on the various techniques of intrusion detection system where some of supervised and unsupervised intrusion detection techniques are discussed. Here methodology of various researchers are explained with their steps of working. Different types of attacks done by the intruders were also discussed.
A Hybrid Digital Water Marking Technique Based on Feature Selection Using Integer Wavelet Transform Function and Decision Tree
Authors:- M. Tech. Scholar Namrata Joshi, Associate Professor Kapil Shah
Abstract:- The quick development of the Internet in the previous years has quickly expanded the accessibility of advanced information, for example, sound, pictures and recordings to general society. As we have seen in the previous couple of months, the issue of ensuring sight and sound data turns out to be increasingly essential and a great deal of copyright proprietors are worried about securing any unlawful duplication of their information or work. Some genuine work should be done so as to keep up the accessibility of mixed media data. Highlight extraction and order based computerized water checking is new territory of research in flow security assurance and copyright strategy. Around there of research different creators utilized element extraction method, for example, wavelet change work and for arrangement reason utilized help vector machine. During the time spent element based water checking strategy include extraction is most critical part and the characterization relies upon chosen highlight. In this paper proposed novel computerized water checking strategy dependent on whole number wavelet change with quality based order procedure. For the choice of highlight quality utilized RBF work. The determination of quality relies upon separated element by whole number wavelet change. The proposed technique recreates in MATLAB programming and tried some rumored assault, for example, commotion assault, share assault and interpretation assault. Our observational assessment result indicates better execution in pressure of DWT water stamping system.
Solar and Wind Hybrid Agricultural Automation Using Iot
Authors:- Asst. Prof.V. M. Dhumal, Payal Sathawane, Mayuri Mahadule, Priyanka Dharmik, Lokesh Moundekar
Abstract:- Agriculture was the augmentation in the rise of sedentary human civilization. Farmers are unaware of technology and lots of efforts are being made by farmers to enhance the productivity. So to overcome this problem we propose a system based on Internet of things to make smart agriculture by modernizing the current traditional methods of agriculture. The main aspect of this project is that system could automatically work according to obtained measurement values and send regular updates and alerts about the farm conditions to owner’s mobile phone and also alternatively controlled via designed website for better understanding of field. In addition to this , demand for electricity is increasing day by day ,which cannot be fulfilled by non- renewable energy sources. So hybrid renewable sources are use to fulfill this energy demand. These sources combines wind turbines and solar system to generate electricity.
Location of Power Burglary in Customers Consumption Utilizing Exception Discovery Calculation
Authors:- Dr. RamaPraba, S.Sangeetha, V. Aishwarya, M. Keerthana
Abstract:- Progressed Metering Infrastructure (AMI) is a centre piece of Smart-lattice, which is in charge of gathering, estimating and breaking down vitality utilization information of clients. The improvement of this system has been conceivable gratitude to the development of new data and correspondence innovations. In any case, with the entry of these advancements, new issues have emerged in the AMI. One of these difficulties is the vitality robbery, which has been a noteworthy worry in conventional power frameworks around the world. To confront these difficulties, datasets of power utilizations are broke down to distinguish interlopers. Conventional systems to identify interlopers incorporate the utilization of AI and information mining approaches. here, we break down the possibility of applying anomalies discovery calculations for upgrading the security of AMI through of the identification of power burglary. We investigate the exhibitions of different existing exception discovery calculations on a genuine dataset (purchaser vitality use). The outcomes demonstrate the achievability of utilization exceptions calculations in the security of AMI and furthermore the adequacy of the utilization of these techniques in the power utilization datasets for robbery identification.
Enhanced Architecture Design for Tri Layer Communication Using Communal Micro blog Information
Authors:- M. Tech. Scholar Anu Joy
Abstract:- Initially and as usual the user can sign up in the social network. While signing up in the social network, the user need provide all the personal and educational information for the user profile. After creating the social network account, the users may search for new friends and they may chat with the friends, the advanced micro blogging information considers only the public data and public chats. A micro data array will be created for the user. The micro array consists of the entire user’s most important information only. Automatically the micro array details will send and search through the E-Commerce application. Here the artificial neural network will works as a third party agent and the agent will retrieves all the recommended products, as micro blogging information. A panel will be design in the social network for displaying the recommended product details. All the displayed products will be more relevant to the user’s profile. The generated micro blogging information contains an alphanumerical characters like (A34#ULKNELRL*!). The micro blogging information has been generated using Artificial Neural Network (ANN) and Advanced text categorization. This micro blogging information will reduce the time of data retrieval from social network to ecommerce application. The same architecture has been enhanced for new channels, here three news channels taken for the consideration. And this is the third tier among the two tiers. As mentioned above the same micro blogging information generated for news channels also. Here the only the relevant news for the user will be displayed, so that they can quickly go through the news updates. In added with search options also provided for other news information like, user can search the news area wise, city wise and state wise. All the information will be shown in a single window.
Pond Maintaining Bot
Authors:- Nagarjun J, Ragavi N, Shunmitha K, P.Vidhyalakshmi
Abstract:- Water is a basic need for all living being. Hence, it is important to maintain the cleanliness and hygiene of water. The work has been carried out by considering the current situation of our national rivers which are dump with crore litres of sewage and loaded with pollutants, toxic materials, debris etc. The Government of India has taken charge to clean rivers and invest huge capital in many river cleaning projects. There is a need to incorporate technology such that cleaning work is done efficiently and effectively. Mechanisms used for design is such a way that it collects the waste which floats on water bodies and the collected waste can be easily disposed. This design cleans wastes found such as plastic wastes, garlands, bottles and other wastes found floating on water. In this project, a bot is used which will float on the water bodies. RF Transmitter and Receiver are used to move the bot and to collect the waste. The collected waste is stored in the storage unit. Design calculations are made to float the bot in water. The bot is made up of Poly Vinyl Chloride in order to have light weight and consists of Direct Current motor, Fish pump and Arduino.
Semantic Analysis for Predicting Movie Reviews
Authors:- Abitha K S
Abstract:- Film audits are evaluations of the tasteful, stimulition, social and social benefits and noteworthiness of a current film or video. Audits have a tendency to be short to medium length articles, frequently composed by a solitary staff essayist for a specific distribution. For film industry, online survey of basic gatherings of people assumes an essential job. On one hand, the great remarks of a motion picture can pull in more groups of onlookers by and large. Then again, the great remarks don’t fundamental mean high box income and bad habit section. Despite the fact that audits are normally genuinely ”speedy takes” on a motion picture, they can, in a few cases, be extensive, substantive, and exceptionally canny. Here we built up a model to perform nostalgic examination onthe motion picture surveys and foresee whether it is a positive or negative audit.
Vehicle Ignition Locking System Using Fingerprint with Gsm Module
Authors:- Asst . Prof. Venkatesh Munagala, Jagadeesh Gade, Vinay Reddy Mekka, Anudeep Kurganti, Sravan Kumar Kunchala
Abstract:- Biometric systems have overtime served as robust security mechanisms in various domains. Fingerprints are the oldest and most widely used form of biometric identification. A critical step in exploring its advantages is to adopt it for use as a form of security in already existing systems, such as vehicles. This research work focuses on the use of fingerprints for vehicle ignition, as opposed to the conventional method of using keys. The prototype system could be divided into the following modules: fingerprint analysis software module that accepts fingerprints images; hardware interface module and the ignition system module. The fingerprint recognition software enables fingerprints of valid users of the vehicle to be enrolled in a database. Before any user can ignite the vehicle, his/her fingerprint image is matched against the fingerprints in the database while users with no match in the database are prevented from igniting the vehicle. Control for the ignition system of the vehicle is achieved by sending appropriate signals to the parallel port of the computer and subsequently to the interface control circuit. The developed prototype serves as an impetus to drive future research, geared towards developing a more robust and embedded real-time fingerprint based ignition systems in vehicles.
An Implementation of Fpga Based Smart Meter For Home Energy Management
Authors:- K. Banumathi M.Tech. Asst. Prof., A. Thameem Ansari, R. Thinesh Kumar, L. Vignesh
Abstract:-Home Energy Management (HEM) for Smart Grid focuses on the power management on consumer side, where home appliances can be monitored and controlled to balance and optimize the power supply and consumption. Among various applications of Smart Grid technologies, Home Energy Management is probably the most important one to be addressed. HEM basically consists of smart meters, smart appliances and advanced control systems. The fundamental task of the HEM system is improving energy efficiency, data measurement, and transmission. The real-time consumption data gathered from each appliance of home are measured and transferred to a data concentrator and back to the utility and view of power consumption data and electricity pricing can be enabled in smart meter. Smart meter initiatives seek to enable energy providers and consumers to intelligently manage their energy needs through real time monitoring, analysis, andcontrol. In this paper the new architecture of FPGA implementation of Home Energy Management for Smart Grid is developed. It estimates the energy consumption of appliances by measuring the voltage, current drawn by the appliances. The other function such as price predictor, communication to the consumer can also be performed in this architecture.
Assessment of Thermal Performance of Closed Loop Pulsating Heat Pipe: Review
Authors:- Nilesh D. Gedam, Harshu A. Bhimgade, Surendra S. Nagpure
Abstract:- In this paper, the effect of different orientation and an internal diameter of pipe on the thermal performance of Closed Loop Pulsating Heat Pipes (CLPHPs) has been studied experimentally. Simultaneously other major parameters that affect the system dynamics include the volumetric filling ratio of the working fluid, input heat flux and the total number of turns has been observed. An experimental set-up of CLPHPs made of copper tubes of different internal diameters heated by constant temperature water bath and cooled by constant temperature water-ethylene glycol mixture (50% each by volume) is used to study the thermal performance with the fixed number of turns in the evaporator. The working fluids employed are water, ethanol, and R-123. The results indicate a strong influence of gravity and the number of turns on the performance. The thermo-physical properties of working fluids affect the performance which also strongly depends on the boundary conditions of pulsating heat pipe operation.
Home automation using Google assistant
Authors:- Dhiraj Rathore, Akash Vasule, Pankaj jharbade, Vivek Bhise, Nilesh Mishra
Abstract:- Home automation is a important aspect we will have in future so here we are designing a simple home automation
System in low cost so that we can help in changing the old technology of manual switches. This technology costs so badly in today’s world around 2000rs to 5000rs so we have made some small adjustments and used it with google assistant which gets a significant reduction in cost of the home automation. we can interact with Google assistant and it can search on internet, schedule events, set alarms, control appliances, etc. This service is available on smart phones with Google Assistant and it is free to use. our project hardly costs 1000rs for 4 manual switches I hope everyone will like it.
Study on Brain Abnormalities Using IoT
Authors:- M .Tech. Scholar Arpitha M S, Manogna D Raj, Asst. Prof. Deepika
Abstract:- It is important to understand the mechanisms of learning disabilities in order to evaluate electroencephalography (EEG) parameters. Diagnosis of abnormalities is one of the major continuously ongoing researches in medical science field. Brain Computer Interface for controlling elements commonly used at home. It includes EEG device needed to acquire signals associated to the brain activity. To understand the complex behavior of brain EEG is very effective tool. IoT revolution has made health care more advanced by narrowing gap between medical condition and the response from specialist. This paper mainly presents an idea related to brain by reforming the existing access control system detecting medical conditions and getting timely response from doctors in case of emergency.
A Review Paper on Automatic Power Factor Detcetion and Correction
Authors:- Shailendra Singh, Sahil Chauhan, Mukesh Chaurasiya, Sarvesh Kumar, Rupesh Kumar
Abstract:- The conception of conserving electrical energy is not new to us,it is widely recognized that electrical energy is being wasted in many forms , such as copper loss, iron loss but these are hard to compensate. Because of the fact that most loads are inductive in nature reactive energy is wasted. So, the required energy is can be utilized in which the energy can have the major correction to form a power factor In simple words power factor can be defined as how far the energy provided has been utilized. And in technical terms it is defined as the ratio of active power to the apparent power .In this paper we do a study of a proto type for automatic power factor correction using some capacitor bank which helps in increasing the power factor which is done by reducing reactive power. In this project load power factor can be increased by Arduino microcontroller. Current and voltage transformer are also used for sampling of the circuit current and voltage for measuring the power factor.
Impact of Co-curricular activities on leadership Qualities of UG students
Authors:- Rubeena
Abstract:- This study to investigated the impact of co-curricular activities on leadership qualities. college graduates recognized as a community leader we’re selected from Government degree college of Nizamabad district. The study was delimited to sports, Elocution, debates, essays and athletic. The sample of 450 students was selected. Data were collected by questionnaire of leadership qualities which was developed by researcher. The data was analyzed by using statistical techniques mean, standard deviation, Pearson coefficient of correlation, and t-test. On the basis of data analysis was found that co-curricular activities how significant impact on leadership qualities of undergraduate students.
Digital Donation Box
Authors:- Prof. D.G.Wadnare, Sarika Pathare, Pratibha Pandit Pratiptsangam Sinha, Neha Waghmar
Abstract:- The now a day’s people go to temples and donates lots of money to temple. The devotees don’t know the exact money, the temple have. Even the government don’t have the data of amount the temple have. This leads to generate in black money. In the current donation box the man power is used to count the money and the money is not counted accurately. And the money is also at risk of being stolen. People also donate fake money which is accidently counted by the workers of temple this will lead to improper counting of money. The current donation box has no security provided. The temple people don’t know that how much amount is there in the donation box, so they have to open the donation box frequently for counting the money. So to solve all these problem we have come with a solution of digital donation box. In our project the money is immediately shown on the website of the temple and on LCD screen of the donation box. This will lead to reduction in black money. In our project no use of man power is required because money is automatically counted by our project.in our project fake coin detection is also there, this will help to reduce in fake coin cases.
Object Detection & Tracking Based Holistic Approach Using SIFT
Authors:- K.V. Kavin
Abstract:- Crowd behavior detection is very promising area of research these days in field of computer vision and artificial intelligence. A novel framework based algorithm has been proposed in this research paper which focuses three key elements of moving crowd [i] Dynamics based appearance of the crowd [ii] Temporal Spatial deviation based anomaly [iii] Intrinsic interaction based deviation flow change . This framework deals with micro as well as macro level anomaly detection using SIFT techniques in structured & Semi-Structured crowd. This proposed framework out performs several existing state of art techniques being used for anomaly detection.
Question Generation using NLP
Authors:- Kaksha Mhatre, Akshada Thube, Hemraj Mahadeshwar, Prof. Avinash Shrivas
Abstract:- In this paper, we have proposed a method to question generation using coreNLP and tree regular expressions for parse tree manipulation. In addition to this we have used spaCy for named entity recognition to recognize entities for question word identification.
Fake Review Management
Authors:- Asst. Prof. B. Ravi Kumar, K. Prabhu, S. Swarup Teja
Abstract:- Today’s, everyone is buy a products in online shopping carts without see a product in physically they buy a product based on the reviews of a buyers, but in online shopping carts any one can provide a review about products, it will be the chance for the spammers to provide a spam reviews about the product in online shopping carts the spam reviews are not identified by the buyer’s so they think the review is genuine and they buy a product, admin only known that review is not a genuine review, in an existing system admin can find the spam reviews but they can’t able to remove the review from the review list, proposed system we can provide a option to remove the spam reviews from the list of review, who will buy the product then they provide review that review is an genuine, one who not buy a product but they provide a review the review will automatically stored in spam review database then admin can remove the review from the list.
Fire and Gas Accident Avoider System
Authors:- Kanchan Marskole, Reena Bodkhe, Shraddha Yadav, Twinkle Thakre, Prof. Meena Sune
Abstract:- The main aim of this project is to monitor for liquid petroleum gas(LPG) leakage to avoid fire accidents, providing house/industry safety feature where the security has been an important issue. The “fire and gas accident avoider system” detects the LPG leakage using a gas sensor, and this system detects the flames by a flame sensor that alert the consumer about that event with GSM module.If due to gas leakage, any fire accident occurred, then the flame sensor will send an alert to the microcontroller and that information also send to the user through GSM module. Any number of consumer mobile number are included while programming the microcontroller in Embedded C language, to which SMS must be send about the gas leakage and fire accident details.The software program for the proposed system is written in the Embedded C language.The fire and gas accident avoider system using GSM system is used to detect any fire, smoke or gas leakage in any premises, building or industry This project is used as a security system in applications like homes, hospitals, hostels, industries. Because of its low power consumption, reliability, portability this system used in other applications like smoke detection. It is very useful in house for detecting LPG gas, which can cause huge loss of property & life.
Effect of Polymer and Micro silica in Preplaced Ballast Concrete
Authors:- Suriya.V, Yogaraj.S, Syed Murtaza Ahmed, Lavan. M
Abstract:- This paper presents the study of Preplaced Ballast (Aggregate) Concrete method in railway track for providing ballast less track. Preplaced Ballast Concrete method employing the injection of cement mortar into voids between preplaced ballast aggregates has recently emerged as a promising approach for the makeover of existing ballasted railway tracks to concrete tracks. This method typically involves the use of a polymer liquid to enhance the durability of the resulting recycled aggregate concrete. However, the effects of the amount of polymer on the mechanical properties of recycled ballast aggregate concrete were not clearly understood. In addition, the effects of the cleanness condition of ballast aggregates were never examined. This study targeted at investigating these two aspects through Ballast samples taken from the track and conducting compression, tensile strength of concrete. The amount of polymer (3%, 6%, 9%) added to the concrete and the test were conducted. The use of a higher polymer ratio improved the microstructure of the interfacial transition zones between recycled ballast aggregates and injected mortar. In order to enhance the compressive strength of concrete, Micro silica (5%, 10%, 15%) were used and the test results revealed the increase in mechanical properties of concrete in Polymer and Micro silica mix. In addition, a higher cleanness level of ballast aggregates generally enriched the mechanical and durability qualities of concrete.
Treatment of Dairy Waste Water Using Stabilization Vessels
Authors:- Jigar Parmar, Joanna John, Prasad Mishra, Sacchit Shah, Asst. Prof. Seema Myakal
Abstract:- Dairy industry is one of the major industries causing water pollution. Considering the increased milk demand, the milk food industries in India is expected to grow rapidly and have waste generation and related environmental problems. Poorly treated wastewater with high levels of pollutants caused by poor design, operation or treatment system creates major environmental problems when discharged to surface water or land. Various pre-treatments methods are available to neutralize the effect. Waste sample from dairy has been experimented on daily basis to calculate “pH, Suspended Solids, Chemical Oxygen Demand, and Biochemical Oxygen Demand”. Various types of locally available chemicals are used to study and analyze the treatment of dairy waste water.
Segmenting and Replication of Data in Cloud for Protection and Maximum Throughput
Authors:- Reshma R, Asst. Prof. Vijay G R
Abstract:- The information is being redistributing to outsider into the distributed computing requires the security to be done while getting to. Be that as it may, while giving the security there comes the execution issues which should be taken to be thought, to expand the execution of the cloud alongside secure information getting to the new SRDCPM technique has presented. SRDCPM procedure manages the separating the information among the hubs of the cloud as, the principle information is being appropriated more than a few hubs while getting to the client must give the label an incentive from that label esteem the sub information partitioned among hubs is being followed by making T-way and is being recovered from fundamental hub. In any case, in this idea the information put away early might be put away again this can be progressed by evading the information which is now present in the cloud consequently execution is expanded while recovering or downloading the required information by the client.
New Generation Cursor and Video Control System
Authors:- Aakash Jadhav, Malik Tamboli, Prashant Gore, Sagar Pachkhande, Shivraj Pattanshetti, Prof B.D. Jitkar
Abstract:- This paper proposes an innovative method to interact with computer system. The proposed system is based on image processing technology. The objective is to create a virtual mouse system and a mechanism for controlling video play-pause option automatically with the help of face detection. The system uses web camera to interact with the computer in a more user friendly manner. Various mouse actions such as cursor movement left click and right click operations are performed based on the colour which is detected by the system.
Study of Scheduling In Microsoft Project Software
Authors:- Shubhashree P. Deshmukh, Akshay V. Sagale, Dr. Manish M. Bais
Abstract:- Planning and scheduling are important task in construction projects. In this project, scheduling in Microsoft (MS) Project software, was undertaken. For planning and scheduling work huge amount of paperwork is required, which makes the management very burdensome. These problems can be solved using project management software which helps to give a planned approach to planning. This analysis was done because of their comparable technical features and to evaluate on the basis of the function to manage the project. Each software had many benefits; MS Project also scored best in terms of easy to use. In this study, a case of an apartment building has been taken to display how proper planning and scheduling is done using MS project.
Greenhouse Environment Monitoring System Based on Wireless Sensor Network
Authors:- Asst. Professor Deepika, Bhanushree V K, Spoorthi P
Abstract:- As an important agricultural infrastructure, greenhouse plays an important role in the development of modern agriculture to supply proper environment for plants. The wireless sensor network has the advantages of simple structure, high efficiency, low cost, safety and reliability compared with the existing wired monitoring technology. This paper describes a design of greenhouse environment monitoring system based on wireless sensor network, the system integrates detection, wireless communication, alarm, display, control and other functions into one, using temperature and humidity sensor SHTll and light intensity sensor BH1750 for data monitoring, using CC2530 as microprocessor, man-machine interface is realized by using Lab VIEW software. The system is mobile and flexible, strong expansibility, low cost, low power consumption, flexible operation, the experiment proved that the system measurement accuracy, control stable operation. It can satisfy the demand of the greenhouse monitoring.
A Study on Patient Health Monitoring Using Iot
Authors:- Shafiya S, Ashwini M C, Asst. Prof. Deepika
Abstract:- IoT is Internet of Things. The Internet of Things refers to the ever-growing network of physical objects that feature an IP address for internet connectivity, and the communication that occurs between these objects and other Internet-enabled devices and systems. These devices are used in various application fields to make our day to day life comfortable. These days frequent monitoring of health is very important for every individual in order to stay healthy. The various advances in Health monitoring using Iot, sensors, Arduino, Raspberry Pi etc are discussed in the paper.
Digitally Automated Incubation System For Complete Seed Germination
Authors:- K.A. Bhosale, S.A. Sawant, P.R. Hasolkar, S.S. Jadhav, B.B. Gayali, V.T. D’souza
Abstract:- Ongoing period has brought upon a noteworthy worldwide sustenance lack because of the climatic changes on the planet. So as to manage this issue of worldwide sustenance lack individuals must need to grow a sensible arrangement of vegetables and different harvests utilizing distinctive methodology and artificially controlled framework yields more products contrast with open field development since the microclimatic parameters that determine crop yield are persistently inspected and controlled to guarantee that an ideal environment is made. This research paper addresses and endeavors to determine a few issues that are looked by plants guardian utilizing the engineering methodology so he/she could stay fulfilled even when he/she physically away for a long time because the automated the system will take care of everything in the absence. This automated framework works utilizing sensors and actuators, which are controlled by microcontroller, monitor and deals with each ecological parameter required for the sound development of plants.
Extending Capability of Air Drones in Military
Authors:- Vibhor Rajawat
Abstract:- Giant AI and robotics leaps, drones and intensive defence hacking systems are no longer limited to science fiction films. Although the current systems are not advanced like the hand of Tony Stark, with each passing day, AI’s defence applications are seeing rapid progress. Unmanned Aerial Vehicles (UAVs) contribute significantly to the warfare capability. UAV’s assumption is that piloted, remotely piloted, and autonomous vehicles have advantages and disadvantages in military activities and vary in different levels of conflicting situations. This article shows the drones and their use possibilities. A drone is powered by batteries, which is the big drawback because after a few minutes of flight it is exhausted, causing the drone to fall on the ground. Military drones differ in size and driving mode from civil / civilian drones. This then includes fundamental legal perspectives to be taken into account when designing UAVs. Two extreme cases of drones and their companion robots have been shown.
Different kinds of Web Crawler
Authors:- Vishakha
Abstract:- A Web crawler is an Internet bot which helps in indexing the web. It crawls one page at a time through a website until all pages has been indexed. Web crawler helps in collecting information about a website and the links related to them. A web crawler is defined as mechanized program that accurately scans through Internet pages and downloads any page that can be reached by links A Web crawler is also known as a Web spider, automatic indexer or simply crawler. Nowadays finding the relevant information over millions bytes of data is very difficult. For this task we need to use efficient crawler so that it can give us best result within minimum time. This paper basically focused on the discussing different crawlers with their efficiency.
Motor control using DTMF
Authors:- Tanushree Patel, Jyoti Hazare, Tinkeshwari Bamne, Sangeeta Barde, Prof. Mukesh Sana
Abstract:- This venture chips away at the rule of DTMF tone order so got from any telephone to remotely switch and control electrical burden, for example, farming siphon, household and modern burdens and so forth. In businesses, the heaps are spread over an extensive region and in this manner, working these heaps is an extremely troublesome undertaking. In horticultural fields additionally, siphons and different burdens are associated over a substantial zone and henceforth it is troublesome for the rancher to work every one of the heaps and also for house hold loads. Thus to overcome these problems, the proposed system has been designed which uses DTMF technology to control the loads remotely.
Ψgs-Irresolute Functions in Topological Spaces
Authors:- J. Sona, N. Balamani
Abstract:- The aim of this paper is to introduce a new class of irresolute functions called ψgs-irresolute functionsin topological spaces. Also we study some characterizations of ψgs- irresolute functions.
Cathodic Protection to Reinforcements
Authors:- Chirag Patidar, Sajjan Singh Gujjar, Shubham Mishra Vivek Dubey, Asst. Prof. Pankaj Jadhav
Abstract:- Corrosion in the reinforcement is one of the major cause for cracks in structure. Usually beams are provided with slab at the top, so top of the beam is not exposed to environment. Bottom of the beam are exposed to atmospheric conditions and if the cover to reinforcement is insufficient, then corrosion of reinforcement takes place. These cracks generally appear near the side face of the beam near the bottom reinforcement along its length. Corrosion in reinforcement can cause expansion of reinforcement bars due to which cracks are formed. In severe cases it can be prevented by good quality control during its construction by providing Cathodic Protection. Cathodic Protection has been widely used in ship building and underground pipeline.
Research Paper Casa Automatics an Automated Home System
Authors:- B. Tech. Scholar Arjun Sehgal, Dr. Neha Agrawal
Abstract:- Home automation system achieved great popularity in the last decades and it increases the comfort and quality of life. In this paper an overview of current and emerging home automation systems is discussed. Nowadays most home automation systems consist of a Smartphone and microcontroller. A smart phone application is used to control and monitor the home appliances using different type of communication techniques. While the potential benefits of smart home technology are widely recognized, a lightweight design is needed for the benefits to be realized at a large scale. We introduce the CASAS “Smart Home automation system”, a lightweight smart home design that is easy to install and provides smart home capabilities out of the box with no customization or training. We discuss types of data analysis that have been performed by the CASAS group and can be pursued in the future by using this approach to designing and implementing smart home technologies. Technology is a never ending process. To be able to design a product using the current technology that will be beneficial to the lives of others is a huge contribution to the community. It presents the design and implementation of a low cost but yet flexible and secure cell phone based home automation system. The design is based on a standalone Arduino BT board and the home appliances are connected to the input/ output ports of this board via relays. The communication between the cell phone and the Arduino BT board is wireless. This system is designed to be low cost and scalable allowing variety of devices to be controlled with minimum changes to its core. To develop a Bluetooth based home automation system with Arduino UNO Board and an Android application. Remote controlled home automation system provides a simpler solution with Android application technology. Remote operation is achieved by any smart phone/Tablet etc., with Android OS, upon a GUI (Graphical User Interface) based touch screen operation.
The role of mobile technology in improving Food productivity in sub-Saharan Africa
Authors:- O. Akinpelumi
Abstract:- With the increasing need to improve food productivity in meeting the growing population’s food demandin sub-Saharan Africa. This essay takes a look at how rising acceptance of mobile technology in this region is been leveraged using SMS and USSD service features, in addressing critical issues facing small-holder farmers. These mobile service features are fully explained and the resulting technical solutions proffered by indigenous agri-tech start-ups to such farming challenges like inadequate access to information, financial transaction and supply chain issues are also discussed.
A Review Article Development of Embedded System For Functional Electrical Simulator
Authors:- Anila Sheikh, Mr. Kshitij Singhal
Abstract:- A virtual prototyping system is constructed by replacing real processing components with component simulators running concurrently. The performance of such a distributed simulation decreases drastically as the number of component simulators increases. Thus, we propose a novel parallel simulation technique to boost up the simulation speed. In the proposed technique, a simulator wrapper performs time synchronization with the simulation backplane on behalf of the associated component simulator itself. Component simulators send null messages periodically to the backplane to enable parallel simulation without any causality problems. Since excessive communication may degrade the simulation performance, we also propose a novel performance analysis technique to determine an optimal period of null message transfer, considering both the characteristics of a target application and the configurations of the simulation host. Through intensive experiments, we show that the proposed parallel simulation achieves almost linear speedup to the number of processor cores if the frequency of null message transfer is optimally decided. The proposed analysis technique could predict the simulation performance with more than 90% accuracy in the worst case for various target applications and simulation environments we have used for experiments.
A Review of Human Facial Expressions Recognition Methodologies
Authors:- Naila Sheikh, Mr. Kshitij Singhal
Abstract:- At present, researches on gestures at home and abroad mostly focus on the study of the hand, and there is less research on facial gestures. Based on the premise of multi-channel human-computer interaction and the rapid development of artificial intelligence, facial gestures based on facial features are proposed. Firstly, the definition of facial gestures and the recognition of facial gestures, as well as the introduction of facial gesture processing, are analyzed. Then facial detection technology based on Face and a set of interactive gestures based on facial features are designed according to the detected facial features, to achieve the interaction with the computer. Finally, a facial gesture application is implemented in Java language and the facial gesture technology is tested and analyzed. The results show that facial gestures are more conducive to hands-on disability for people with disabilities to more easily interact with computers and reduce the burden on their hands.
Images Retrieval using Hybrid Features Mechanism
Authors:- M.Tech. Scholar Alok Kumar Prajapati, Asst. Prof. Deepak Pancholi
Abstract- To recover vital pictures from a divergent gathering by utilizing visual questions as inquiry contentions are the exhausting and significant open issues. In this paper the scholars have referenced the structures and executions of a straightforward yet successful Content-Based Image Retrieval (CBIR) framework. The hues, surfaces and the shapes highlights are the imperative pieces of this framework. With the three principle ensuing looking advances the seeking winds up staggered. Such propounded frameworks are exceptionally one of a kind as they think of one as highlight at each progression and utilize the aftereffects of the past advance as the contribution for the following coming advance in staggered design while in the prior techniques every one of the highlights are joined on the double for the single-level hunt of a normal CBIR framework. The propounded strategy is extremely basic and agreeable to receive. The recovery evaluation of the propounded technique is valuated utilizing bi-benchmark datasets for a picture characterization. The above arrangement of strategies indicates extremely great outcomes as far as improvement in recovery characteristics, when contrasted and the writing. In proposed work we get exactness like between 68.15 % to 94.86% in utilized diverse highlights.
IoT Based Smart E-Learning System Using Machine Learning
Authors:- Shinde Swapnil S., Bansode Mithilesh M., Jadhav Pandurang B., Pawar Rohit P.
Abstract- The smart e-learning system is a web application which establishes an environment between web application server and end users. This project is developed using machine learning and IoT .using this web-application user can stream the videos live and access the files stored on the server. The medium to access the recourses is internet. This E-learning System is Beneficial to the Distance Education.
Design and Implementation of a Robot for Maze-Solving using Wall Following Algorithm
Authors:-K.Surya Teja, Koyi Rajesh, M. Gopi Krishna, CH.Pavan Naga Sai
Abstract- Maze solving robots in the past had great impact in robotics which is based on decision making algorithm, the main result of this project is to detect the objects and it should avoid them for colliding. if the object in on right and front then it should turn left, if the object is on left and front then it should turn right, if the object is on front and left and right then it should go back or stop there. Not only turning here we have decided to display the output in LCD if it turns right ,right is displayed in Lcd and also same for left, back, front, stop. By doing this project we can solve the daily problems very quickly.
Survey on Big Data Concepts, Technology, Applications and Challenges
Authors:-Asst. Prof. Sapna S. Kaushik
Abstract- Big data is a new driver of the world economic and societal changes. Incredible amounts of data is being generated by various organizations like hospitals, banks, e-commerce, retail and supply chain, social media and smart phones, Internet of Things and cloud computing etc. by virtue of digital technology . While the data complexities are increasing including data’s volume, variety, velocity and veracity, the real impact hinges on our ability to uncover the `value’ in the data through Big Data Analytics technologies. The voluminous data generated from the various sources can be processed and analyzed to support decision making. Analysis of these massive data requires a lot of efforts at multiple levels to extract knowledge for decision making. Big Data Analytics is the process of examining large amounts of data (big data) to discover hidden patterns or unknown correlations. A key part of big data analytics is the need to collect, maintain and analyse enormous amounts of data efficiently and effectively. Analyzing Big Data is a challenging task as it contains huge dispersed, diverse and complex file systems which should be fault tolerant, flexible and scalable. There is an immense need of constructions, platforms, tools, techniques and algorithms to handle Big Data. The technologies used by big data application to handle the massive data are Hadoop, Map Reduce, Apache Hive, HBase,HDFS – Distributed File System.
IoT Based Delivery Boys Safety Control and Bike Analyzer
Authors:-Harshith H., Lokesha G.N, Kishor Kumar R., Mrs. Deepika
Abstract- Two wheelers are widely used than other form of vehicles due to its low cost and simplicity. Most of the time rider doesn’t like to wear helmet which could be result in fatal accidents. Drunken driving and Drowsy driving are the major factors for such road accidents. Some statics shows that 35% of the accidents are caused by two wheelers and in that 60% of the two wheeler accidents are caused due to lack of consciousness, drunken driving and not wearing helmet. The primary concern of all riders is safety. From above, taking in to consideration the safety of delivery boys who works for online business travels across areas using two wheelers, where safety of bike rider counts. Hence to track the activities of such rider and to provide safe riding this paper has been proposed. This paper aims for avoidance of accidents and develop helmet detection system. The proposed system is an intelligent/safety helmet. A module affixed in the helmet, such that, the module will sync with the module affixed on bike and will also ensure that biker has worn Helmet. Additional feature of accident avoidance detection module will be installed on the bike.
Road Detection and Segmentation from Aerial Images using a CNN based System
Authors:-V. Chinnapu Devi, V.Tarun Sai, M. Narendra Kumar, Y. Pavan Kumar Reddy, S.L.Viswanath Naidu
Abstract- This paper proposes a system architecture based on deep convolutional neural network (CNN) for road detection and segmentation from aerial images. These images are acquired by an unmanned aerial vehicle(UAV) . The algorithm for image segmentation has two phases: the learning phase and the operating phase. The input aerial images are decomposed in their color components, preprocessed in Matlab and next partitioned in small boxes of dimension 33 × 33 pixels using a sliding box algorithm. These boxes are considered as inputs into a deep CNN. The CNN was designed using MatConvNet and has the following structure: four convolutional layers, four pooling layers, one ReLu layer, one full connected layer, and a Softmax layer. The whole network was trained using a number of 2,000 boxes. The CNN was implemented using programming in MATLAB on GPU and the results are promising.The CNN output gives pixel by pixel information on what category each falls into (ROAD/NON-ROAD).Road pixels are labeled with “1’s”(white) and non-road pixels are labeled with “0’s”(black). The proposed system has the advantage of processing speed and simplicity from the previous sytem which has a less speed and complexity.
Comparative Study on Microarray Data Analysis Techniques of Machine Learning
Authors:-M.Tech. Scholar Sanjay Kumar Sharma, Asst. Prof. S.R. Yadav
Abstract- Machine learning models has been applied for prediction and prognosis of disease development and it become an irrevocable part of microarray data analysis aimed at betterment of the subsequent therapy and management of patients. The application of machine learning models for accurate prediction of survival time in cancer disease on the basis of clinical data is research work of the presented study. The paper discusses an approach to the problem in which the main factor used to predict survival time is the originally developed tumor-integrated clinical feature, which combines tumor stage, tumor size, and age at diagnosis. Two datasets from corresponding liver cancer studies are united by applying a data integration approach based on horizontal and vertical integration by using proper document-oriented and graph databases which show good performance and no data losses. Aside from data normalization and classification, the applied machine learning methods provide promising results in terms of accuracy of survival time prediction. Clustering has been used extensively as a vital tool of data mining. A neuro-fuzzy method is proposed in this research for analyzing the gene expression data from microarray experiments. Analysis of gene expression data leads to cancer identification and classification, which will facilitate proper treatment selection and drug development. The proposed approach was tested on three benchmark cancer gene expression data sets. Experimental results show that neuro-fuzzy method can be used as an efficient computational tool for microarray data analysis. The neuro-fuzzy classification system, which is based on a built clustering algorithm reached recognition rates than other classifiers. Gene expression data sets for liver cancer were analyzed in this research. A training and test data set for each cancer was used to analyze the quality of the genes. Use of computational methods to predict Gene Regulatory Networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this research work, semi-supervised methods have been proposed for GRN prediction by utilizing two machine learning algorithms, namely support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabeled data for training. Inductive and transductive learning approaches has been investigated, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabeled data. Then semi-supervised methods are applied to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of the methods using the gene expression data. This analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.
Partial Replacement of Cow Dung With Cement
Authors:-Hardik H. Chauhan, Swarupanand V. Munj, Harsh M. Rawal, Jay P. Patil, Prof. Mrunalini Deshmukh
Abstract- This research project presents the result on the study for the use of Cow Dung Ash (CDA) as partial replacement in production of concrete. The experiments were designed to study the effects of adding Cow Dung Ash (CDA) in various percentages by weight (10%, 13%, 16% and 20%) of cement and cure for the periods of 7, 14, and 28 days respectively before testing for the Compressive strengths. It also involves determination of setting time, Bulk Density, and Workability of Cow Dung Ash in various percentages by mixing with Portland cement. The Compressive test results are 22.00 N/mm2, 20.22 N/ mm2, 19.55 N/mm2, 13.78 N/mm2 and 12.13 N/mm2 for 0%, 10%,13%, 16% and 20% replacement of cement with CDA respectively at 28 days. The Workability results gives 112mm, 127mm, 130mm, 72mm and 80mm respectively for 0%, 10%, 13%, 16% and 20% replacement of cement with CDA. Test results indicated that the consistency limits increased up to an optimum content and decreased further with the increase in the % of CDA in cement. CDA has an advantage that offers lightness of weight and low thermal conductivity, Cow Dung Ash concrete is recommended for use only when a thirteen percentage (13%) of Cow Dung Ash is added.
Automated Human Action Recognition System Using Machine Learning
Authors:- Sagar Goyal, Susmitha Shereef
Abstract- Human action recognition is an important research topic, nowadays because of security and safety constraints. An action recognition is helpful in gesture recognition, posture detection, video surveillance and many more important activities that are desirable in today’s world. Action recognition can help in reducing the criminal acts or in detecting any kind of that activity at correct time so that appropriate action against that activity can be taken. There are various conventional action recognition methods that recognize actions in a video directly which can often give incorrect results because analyzing videos directly requires great speed in detection of actions. However, detecting images is much simpler and easier job to do. So, we convert an input videos into static image frames for easy analysis and interpretation of actions. There are many problems in current action recognition methods which face deficiency in labelled videos or some methods use lot of labelled videos in training dataset that further face the problem of over-fitting the training data and inaccuracy in detecting actions in online testing dataset. Hence, in this project, we use a semisupervised learning approach to make a balance between labelled and unlabeled videos and utilizing both simultaneously that overcomes the problem of overfitting the data and also provide the best results in least amount of time. The experimental results show that our action recognition method works for online testing dataset and gives accurate results with very good performance and is better than any other action recognition method.
Extraction of Metadata and it’s Parsing for PubMed articles
Authors:- Aarti Mete, Priyanka Kanthale, Pritam Bhaye, Rahul Subhedar, Mrs. Shafali Gupta
Abstract- Most of the data is in the form of articles and papers. Identifying the important articles form the millions of available papers is a need for today. Metadata extraction returns hidden information from the documents that are not in structured form to the one with semi – structured or standard form. This useful information contains authors, title, ID’s, etc. about the article. Metadata is data (information) that is supposed to provide information from other data. This information is the basic information that can be further useful for the analysis of article.The extraction of metadata and the technique of parsing it have been discussed further.
A Review on Analysis of Data Search Scheme for Secure Information Retrieval in Cloud Computing
Authors:- M.Tech. Scholar Nitin Kumar Sahu, Asst. Prof. Anuj Kumar Pal
Abstract- Today’s businesses want it all: secure data and applications accessible anywhere from any device. It’s possible with cloud technology, but there are inherent challenges to making it a reality. What can enterprise businesses do to reap the benefits of cloud technology while ensuring a secure environment for sensitive information? Recognizing those challenges is the first step to finding solutions that work. . Increasingly numerous companies plan to move their local data management systems to the cloud and store and manage their product information on cloud servers. An accompanying challenge is how to protect the security of the commercially confidential data, while maintaining the ability to search the data. In this paper we are analysis of different securities scheme for encryption of item information and also for data search scheme in cloud computing.
Study of Rubber Dam
Authors:- Siddharth Soni, Manjunath Pai, Nandini Singh, Pankaj kumar Yadav, Asst. Prof. Mrunalini Deshmukh
Abstract- Rubber dams are inflatable and deflatable hydraulic structure. Thousands of rubber dam have been installed worldwide for various purpose: irrigation, power generation, tidal barrier, environmental improvement, flood control and recreation. The newest material in the construction of water structures in recent years, is the rubber material that is widely used in the construction of short dams or dams. The simplicity and flexibility of the rubber dam structure has proven reliability and are the key consideration in its wide scope of application. The estimation of rubber dam is based on personal communications with the expert of manufacturers and the practitioners of the subject areas as well as case studies of already constructed rubber dam in India install for the purpose other than hydropower. It is recommended to use inflated weir in small hydropower projects which is being cost effective and also energy efficient. Rubber dam is a new technology which control water in flexible way. Average life cycle cost of Imported rubber dam and life cycle cost of Indian rubber dam is about 3 times more than the cost of Indian rubber dam. In this paper we are going to study the working of Rubber Dam and conventional dam and compare the cost of both the dam. And based on the study, will conclude whether Innovation of Rubber dam is cost effective and useful or not.
Sentiment Analysis for Understanding Students Learning Experiences: A Survey
Authors:- ME Aaquib Multani, Assistant Professor Atul Agrawal
Abstract- Social media allows the creation and interactions of user created content. Social medium places include Facebook, Twitter etc. Student’s casual discussion on social media focused into their educational experience, mind-set, and worry about the learning procedure. Now days, Social media craze is mounting to heights of success for every individuals. The amount of social media data provides chances to understand students’ experiences, but their methodological difficulties to use social media data for educational purpose. Therefore, there is need to identify students’ emotions by analysis of their sentiments. In this survey paper, we discuss about the sentiments analysis and their patterns. Additionally, we proposed an approach for predicting sentiments of user specifics and classifying them in to ‘negative’ or ‘positive’. We are implementing this method on JAVA environments using “Twitter” dataset..
Disease and Cure Prediction in Crops Using Neural Networks Authors:- Prathyusha Mukkarla, Prof. Asha, Phani Deepthi Yarlagadda
Abstract- Social media allows the creation and interactions of user created content. Social medium places include Facebook, Twitter etc. Student’s casual discussion on social media focused into their educational experience, mind-set, and worry about the learning procedure. Now days, Social media craze is mounting to heights of success for every individuals. The amount of social media data provides chances to understand students’ experiences, but their methodological difficulties to use social media data for educational purpose. Therefore, there is need to identify students’ emotions by analysis of their sentiments. In this survey paper, we discuss about the sentiments analysis and their patterns. Additionally, we proposed an approach for predicting sentiments of user specifics and classifying them in to ‘negative’ or ‘positive’. We are implementing this method on JAVA environments using “Twitter” dataset..
Pothole Repair by using PET (Polyethylene Terephthalate) and Zyco Therm Authors:- Amol Bhosale, Siddhesh Katkar, Shubham Shinde, Suraj Shrivastav, Deepika Bhulla, Mrunalini Deshmukh, Neha Badiger
Abstract- In India, Most of the pavements are of flexible pavement as they are economical compared to rigid pavements but its maintenance causes more trouble and also increase cost of flexible pavement construction. Bitumen and aggregates being an important aspect of the flexible pavement from cracking and deterioration of the pavement. . Bitumen acting as a binding material in the pavement when mixed with the Polyethylene Terephthalate (PET) and ZycoTherm (upgraded version of ZycoSoil) brings more stability to the roads and helps ion resisting the forces from the vehicles. Hence in this study different test is to be done regarding more stable and effective proportions to be used between bitumen and plastic waste comprising of Marshal Stability test, Ductility test, Penetration test and Softening point test for Bituminous mix and Bitumen.
An Advanced ETL Technique for Error Free Data in Data Warehousing Environment
Authors:- Marzana Ifat Moly, Ovijit Roy, Md. Alomgir Hossain
Abstract- A large store of data accumulated from a wide range of sources within a company and used to guide management decisions. Data Warehousing is one of the common words for last 10-20 years, whereas Big Data is a hot trend for last 5-10 years. Now we are trying to find out that how the ETL process work with the Data Warehouse and how to manage after transform the data into data warehouse. ETL is the stand for extract, transform and load. This is a very new concept for Data warehouse. Many of know about the ETL but it’s just a theoretical concept. So we try to find out how ETL works with Data warehouse. And we try to build a prototype of ETL and that’s ETL design include in this paper.
Concrete Containing Crumb Rubber and Slag Cement
Authors:- Dinesh Choudhary, Jayashri Poojary, Khushboo Shukla, Abhishek Singh, Prajakta Mukadam
Abstract- The treatment, utilization and disposal of scrap tyre rubber is major environmental issue. Up till now only small quantity of scrap tyreis recycled and remaining is dump, ignited and landfill. The manufacturing growth rate of tyre is increasing at a very fast rate. One of the possible solutions for the reuse of scrap type rubber is to incorporate it into concrete in the form of crumb rubber by replacing some of proportion of the coarse aggregate. This project study has been conducted by replacement of aggregate with crumb rubber and replacement of whole quantity of cement with slag cement. Addition of crumb rubber is done by 3%, 5%, 7% of total weight of coarse aggregate. After casting and curing, compressive strength and flexural strength test had been performed to find strength of the concrete and behavior of the concrete under the test has been studied.
Green Supply Chain Management with Artificial intelligence based optimization
Authors:- Dhananjay Kumar Yadav, Mr. Kamlesh Gurjar
Abstract- Green supply chain management (GSCM) has become a topic of interest for both business leaders and academic researchers alike. Over the last decade or so, the GSCM literature has grown considerably. Although sufficient literature exists about various aspects and facets of GSCM, earlier works and reviews have a limited focus and narrow perspective. This paper presents a comprehensive integrated view of the published literature of GSCM so as to facilitate further study, practice and research. First, we introduce the different definitions of GSCM and its’ development. Second, we focus on reviewing the research on GSCM’s decisions and models. Finally, we discuss the limitations of existing research on GSCM and indicate future research opportunities.
Object Detection and Classification Using Yolo
Authors:- Naman Mittal, Akarsh Vaidya, Asst. Prof. Shreya Kapoor
Abstract- The cutting edge world is encased with monstrous masses of computerized visual data. Increment in the pictures has asked for the improvement of hearty and effective article acknowledgment procedures. Most work announced in the writing centers around skilled systems for item acknowledgment and its applications. A solitary article can be effectively recognized in a picture. Various items in a picture can be recognized by utilizing distinctive article locators all the while. The paper examines about article acknowledgment and a technique for different item identification in a picture.In spite of the fact that various systems have been proposed with the end goal of picture acknowledgment, Convolutional Neural Network or CNN, is a method which has had the capacity to effectively take care of the picture acknowledgment issue productively.We demonstrate YOLO, a way to deal with item recognition. Earlier work on item discovery re purposes classifiers to perform location. Rather, we outline object location as a relapse issue to spatially isolated bouncing boxes and related class probabilities. A solitary neural system predicts bouncing boxes and class probabilities legitimately from full pictures in a single assessment. Since the entire discovery pipeline is a solitary system, it very well may be upgraded start to finish straightforwardly on identification execution.
Study and Analysis of Disputes
Authors:- Rohit V. Shewale, Ranjit Kumar Elumalai, Dilip S. Shirivastav, Abhijeet Jaiswar, Prof. Basweshwar Bansode
Abstract- Unforeseen circumstances, prompting debate, are an ordinary element of every construction industry since conditions experienced are typically unique in relation to those arranged or anticipated. Construction disputes emerge because of a series of components that consolidate in different approaches to deliver differences, disagreements and lastly dispute. These dispute might be of different nature like technical, money related or quality related, time related, or staff related, etc. Since, conflict and disputes are the reason of stress on the grounds that an well planned construction project cannot run smoothly, efficiently because of these problems. Therefore it is essential to oversee them for better and proficient finish of projects. The research methodology is based on questionnaire survey primarily focusing on Indian construction projects. This paper will help to find out major causes of disputes and is relied upon to be assistance for the management of the same.
Cloud Based Secured Locker
Authors:- Shilpashree P.S, Abhishek Kumar Tiwari, Ashutosh Prakash, Saurabh Kumar Singh
Abstract- In the modern era, security plays a significant role. Every individual has valuable accessories like gold, jewellery or cash. It is not enough to have these accessories, but security of this is very important, for this purpose some people prefers to keep them in bank lockers. Still it is common to hear or read in news that some fake person accessed the locker of another person and have stolen their accessories. In order to deal with this type of frauds, verification of the person who wants to use the locker is very important. In this project, advance secured system is designed which will make sure the authentic access of the locker overcoming all the misuses. For this purpose, it is better to have unique password technique through the OTP verification and use of biometric verification which is more effective, secured and fast. If an unauthorized user tries to breach the locker, the alarm signal would be raised to notify the security guards. The owner is also notified by sending the snapshot of unauthorized user to authenticated email id. In this system locker will have a wireless module which connects to the Internet and communicates with the user and admin through internet from anywhere in the world. The main objective of this project is to embed a locking system in the door consisting of two step with locking positions, controlled by the user and admin using android app and burglar alert system when someone tries to open the locker manually.
Lung Cancer Detection Using Digital Image Processing and Artificial Neural Networks
Authors:- M. Tech Scholar Shubham Bhardwaj, Asst. Prof. Shalini Bhadola, Asst. Prof. Kirti Bhatia
Abstract- Cancer detection is generally carried out manually by trained professionals and these techniques are majorly helpful in the advanced stage detection, also it involves a very tedious procedure and highly dependent on the given individual. This introduces the high possibility of human error in the detection process which necessitate an automated process. Hence, this paper aims at early detection of cancer through an automated process to minimize human error and making the process more accurate and hassle-free. In the proposed work, image processing algorithms and artificial neural network have been employed to design an automated process for early stage detection of lung cancer. In today’s world ,image processing methodology is very rampantly used in several medical fields for image improvement which helps in early detection and analysis of the treatment stages ,time factor also plays a very pivotal role in discovering the abnormality in the target images like-lung cancer ,breast cancer etc. this research focuses upon image quality and accuracy. image quality assessment as well as improvement are dependent upon enhancement stage where low pre-processing techniques are used based upon gabor filter within Gaussian rules; thereafter the segmentation principles are applied over the enhanced region of the image and the input for feature extraction is obtained, further depending upon the general features, a normality comparison is made .in the following research the crucial detected features for accurate image comparison are pixel percentage and masking labeling. In this research we have done classification based upon artificial neural networks which is more satisfactory than other current classification methods.
Optical Oscillator Using HEMT
Authors:- Aditya Tiwari, Praveen Singh, Akshay Singh
Abstract- The existing processors have lower frequencies due to which multitasking operations and all the high end software which require more processing power cannot be performed efficiently. so the main task is to build a processor which has higher frequency of operation for which we need a device which can work on higher frequency and high electron mobility transistor is one such device which works on higher frequency relative to other devices, so with the help of hemt we will be designing an optical oscillator which can work on high frequency end the simulation of this oscillator will be performed on visual tcad software. here we will check the response of the oscillator by simulating it on the software so that a desired frequency can be obtained and the device can be fabricated so that multitasking operations can be achieved easily
Controlling Set Top Box using Hand Gestures
Authors:- Deepti Gupta, Yash Goel, Neeraj Sharma
Abstract- Controlling the T.V set top box has been done through an infrared remote control since its inception but with the growth in smart technology all around us our control can be more interactive and easy by the use of hand gestures. Main motive behind this gesture based remote control is to remove the constraint of a handheld device. This hand gesture based remote control will also be useful for people with disabilities as compared to traditional handheld remote in which a key has to be pressed to control the STB which can cause muscle strain to people with physical disability whereas a simple gesture will not cause such strain and will also make it easier for them to control their T.V effortlessly. This system will be built on Arduino microcontroller board and use Ultrasonic sensor to detect hand gesture and an infrared LED to transmit the decoded signal to the Set Top Box.
Providing Security and Privacy for communication in Vehicular Cloud Computing
Authors:-Patil Nilochana, P. Kavitha
Abstract- Vehicular cloud computing (VCC) uses unused vehicle storage and computing resources to collaboratively provide end users such as drivers and passengers with traffic management, road safety and infotainment services. It is a hybrid technology that enhances the use of vehicle resources and is capable of performing complex computing tasks that a single vehicle cannot handle. Despite the appealing benefits of sharing resources among unfamiliar vehicles, there are severe threats to security and privacy in VCC. In this paper, we identify security goals for VCC interoperability and provide an authentication key agreement (AKA) framework for VCC. Specifically, to design a reliable AKA with strong safety guarantees for VCC, we present the research challenges and open issues first. Then we propose a secure and efficient message access control and authentication scheme in VCC. For message sharing, a hierarchical, Cipher Policy Attribute Based Encryption (CP-ABE) technique is used to ensure that vehicle whose persistent or dynamic attributes satisfy access policies can access the broadcast message with equipped cloud. Finally, to illuminate the further directions of research on AKA for VCC, several interesting issues are discussed.
Smart Grid Load Balancing Using Renewable Resources and Genetic Algorithm
Authors:- Research Scholar Manish Verma, Asst. Prof. Ashish Sethiya, Asst. Prof. RP Kumawat HOD
Abstract- With increase in load Smart Electrical Grids are required for proper distribution of electrical load. Here this balancing is not straight switching because of random electric requirements. Considering these facts work has focus on developing a smart grid for balancing the renewal load distribution, by using genetic algorithm. Here propose work will utilize Teacher Learning Based optimization algorithm, where two phase learning is done. Here proper set of solar or wind mill generators are assigned for fulfilling particular load requirement is estimate by this genetic algorithm. In this work proper fitness function was used where distance of source plant is also consider for loss of power dissipation and reduce it. This work increases the resource utilization with minimum loss. Experiment was done on real dataset from authentic datasets and result shows that proposed work is better as compared to previous other approaches n various evaluation parameters.
Computer Interfaced Smart A.I Battle Field Tank
Authors:- ME Scholar S. Alaguganesan, Asst. Prof. D. Siva Kumar
Abstract- As the potential for disastrous consequences from threats increases in prevalence, the speed which such cyber threats can occur presents new challenges to understandings of self-defence. This paper first examines the prevention of threats nations could face. It next looks at existing concepts of self-defence with particular focus on anticipatory and pre-emptive self-defence, and then moves to a review of the underlying criteria which govern the right to resort to such actions. Highly sophisticated electronic sensors attached to the tank’s hull will project images of the surrounding environment back onto the outside of the vehicle enabling it to merge into the landscape and evade attack. The electronic camouflage will enable the vehicle to blend into the surrounding countryside in much the same way that a squid uses ink to help as a disguise. Unlike conventional forms of camouflage, the images on the hull would change in concert with the changing environment always insuring that the vehicle remains disguised.
A Review on Different Face Spoof Detection Techniques in Biometric Systems
Authors:- M. Tech. Scholar Kanika kalihal, Asst. Prof. Jaspreet Kaur
Abstract- Biometric systems are increasingly used in different security systems for the last few years. Fingerprints, Iris recognition, face recognition systems have grabbed attention from academicians and researchers all over the world. But there are certain issues associated with these systems that make them vulnerable. One such issue is the spoof attack in which an impostor attacks the system by presenting a printed photograph of the genuine user to the system. These attacks compromise the security of the system and therefore need to be addressed. This paper presents an overview of different techniques that are used in face spoof detection and discussed parameters that are used to evaluate the performance of different face spoof detection techniques.
Design and Implementation of Smart Sensor Integrated Chair For Medical Diagnosis
Authors:- ME Scholar M. Kiruthika, Asst. Prof. K. Abhirami
Abstract- With the design of an Internet of Things (IoT) and telemedicine based health monitoring system- The Smart Chair. Sensors and associated hardware needed to monitor the vital physiological parameters of the human body are available on the chair, thereby leading to the idea of a Smart Chair. It enables the subject to be seated in a relaxed posture during the acquisition of physiological signals from various sensors attached to his/her body. The raw signals from the sensors are processed digitally by an onboard microcontroller and analyzed for any common abnormalities in the health parameters of the subject. The results are then transmitted to a personal computer. The data can be viewed at any later time by a doctor’s computer that is connected to Internet. The Smart Chair also sends an SMS with all the health details to a remote doctor’s phone in case of an emergency, thus facilitating telemedicine in rural areas. The key focus of the presented work is to propose the design of a chair that will be useful and easily affordable by the people of developing nations who have limited access to proper healthcare facilities. The results Presented show that the proposed system is definitely a low cost affordable solution for IoT based telemedicine system, as compared to existing systems.
A Review of Android Security System
Authors:- M. Tech. Scholar Shipra Joshi, Asst. Prof. Rahul Sharma
Abstract- Android operating system uses the permission-based model which allows Android applications to access user information, system information, device information and external resources of Smartphone. The developer needs to declare the permissions for the Android application. The user needs to accept these permissions for successful installation of an Android application. These permissions are declarations. At the time of installation, if the permissions are allowed by the user, the app can access resources and information anytime. It need not request for permissions again. Android OS is susceptible to various security attacks due to its weakness in security. This paper tells about the misuse of app permissions using Shared User ID, how two factor authentications fail due to inappropriate and improper usage of app permissions using spyware, data theft in Android applications, security breaches or attacks in Android and analysis of Android, IOS and Windows operating system regarding its security.
Data Sharing With CP-ABE to Data Owner-Side And Cloud-Side Access Control For Encrypted Cloud Storage
Authors:- M. Tech. Scholar Diguvasadum Deepika, Asst. Prof. G.Varaprasad, Asst. Prof. Karamala Suresh
Abstract- People support the great power of cloud computing, but cannot completely trust the cloud providers to host privacy-sensitive information, due to absence of user-to-cloud controllability. To ensure confidentiality, data owners outsource encrypted data instead of plaintexts. To distribute the encrypted files with other users, Ciphertext-Policy Attribute-based Encryption (CP-ABE) can be utilized to carry out fine-grained and owner-centric access control. But this does not adequately become make safe against other attacks. Many earlier schemes did not grant the cloud providers potential to verify whether a downloader can decrypt. Therefore, these files have to be available to everyone accessible to the cloud storage. A malicious attacker can download thousands of files to launch Economic Denial of Sustainability (EDoS) attacks, which will mostly consume the cloud resource. The customer of the cloud service bears the expense. Besides, the cloud provider serves both as the accountant and the payee of resource consumption fee, lacking the transparency to data owners. These concerns should be resolved in real-world public cloud storage. In this paper, we propose a solution to secure encrypted cloud storages from EDoS attacks and provide resource consumption accountability. It uses CP-ABE schemes in a black-box manner and complies with arbitrary access policy of CP-ABE. We present two protocols for different settings, followed by performance and security analysis.
Analysis of Classification Algorithms using Machine Learning
Authors:- M. Tech. Scholar Soniya Rathore, Asst. Prof. Ankur Taneja, Asst. Prof. Mahesh Patidar
Abstract- In this work our main focus is on regression which is one of the most important methods in machine learning algorithm. Regression is a statistical approach that is used to find the relationship between variables. It is basically used to predict the outcome from the given dataset. In this work we will discuss the regression algorithms which are available in machine learning algorithm and propose one algorithm that will have less train error and test error as compared to other existing algorithm. The accuracy measure will be in the form of train and test error.
Effect Reinforcement of Boron Carbide and Silicon Carbide on AA 2024 Hardeness
Authors:- Arnav Singh, S M Uruf Nezami, Sadaf Kamaran Ali, Ankit Kr. Yadav, Asst. Prof. Rahul Malik, Asst. prof. Vishal Sharma
Abstract- Aluminum matrix composites are emerging as advance engineering materials due to their strength, ductility and toughness. The aluminum matrix can be strengthened by reinforcing with hard ceramics particles like silicon carbide and boron carbide etc. In the present study, an effort is made to enhance the mechanical properties like tensile and hardness of AMCs by reinforcing 2024 Al matrix with boron carbide and silicon carbide particles by stir casting route. It is observed that by adding 5% reinforcement our hardness Brinell hardness as well as Rockwell hardness becomes 119 BHN and 49 HRB & further adding 10% reinforcement our hardness Brinell as well as Rockwell hardness is 185 BHN and 97 HRB respectively.
Application of Influence Function for calculation of Mining Subsidence and Displacement Prediction
Authors:- Nabyendu Neogi
Abstract- In the present world underground mining is carried out hundreds of meter deep from the surface and creating voids after mining out minerals and coal, these minerals were previously bearing the load of the surrounding strata, but due to the voids created after extractions, cracks are formed in the immediate roof, and these cracks travel to the surface causing the surface strata to come down and cause subsidence. This is a brief study on the estimated calculation of mine subsidence of a mine using mathematical influence function by which we divide the underground mining area into several annular rings and find out the effect of these area on the surface and plot a subsidence profile and hence the displacement calculation due to the void created in the mined-out spaces. From the subsidence profile of the mine area we can not only predict the extent of area which is going to subside but also with how much vertical displacement and thus saving life and livelihood.
Snake Game for Android
Authors:- Tushar Tokas, Karan Arneja, Sparsh Goel
Abstract- This project is aimed at creating a version of the snake game for android devices which can not only serve as a means of entertainment but also as a means to understand the development of technology in the past two decades from when the snake game was first popularized on Nokia devices. Even in the original snake game, there was multiplayer facility available provided that two devices were present and connected via an infrared connection. It presents a simple means to compare the technology used then and now, such as the difference in programming languages, algorithms and electronic devices. Traditional methods of creating Snake game usually include the use of coding languages to create an Engine and the main game, but this project implements use of script-free software to create the software. This is made possible by software called Clickteam Fusion. Clickteam Fusion is a game engine that uses an event based system instead of coding. The game helps get a good grasp of Clickteam Fusion as well, so new games can be made with this new understanding of modern technology.
Integrating IoT with SAP Success Factors: Automating Time and Attendance Tracking Through Biometric Devices
Authors: Manoj Parasa
Abstract: Enterprise time and attendance tracking systems have historically relied on manual inputs and fragmented technologies, creating vulnerabilities in compliance, payroll accuracy, and employee trust. This paper investigates the integration of biometric Internet of Things (IoT) devices—including fingerprint scanners, RFID terminals, and facial recognition sensors—into SAP SuccessFactors Time Management using SAP Cloud Platform Integration (CPI). A mixed-methods methodology is applied, encompassing middleware simulation, data flow prototyping, and three real-world case studies across manufacturing, logistics, and healthcare. Quantitative results reveal a 27% improvement in attendance data accuracy and a 32% reduction in payroll discrepancies. Compliance audit readiness improved by 50% following integration. Drawing from interdisciplinary literature in IoT middleware, biometric security, and enterprise HRIS architecture, this study provides a scalable and secure blueprint for intelligent workforce time tracking.
DOI: https://doi.org/10.5281/zenodo.15718647
The Red Hat Difference Building A Robust Hybrid Cloud With Enterprise Linux And Middleware
Authors: Meera Joshi
Abstract: Hybrid cloud architectures are increasingly central to enterprise IT strategies, requiring platforms that integrate legacy systems with modern cloud-native applications. Red Hat Enterprise Linux (RHEL) and its middleware portfolio, including JBoss EAP, Fuse, and AMQ, provide a robust foundation for building secure, scalable, and resilient hybrid cloud environments. This review explores RHEL’s core capabilities, middleware integration, automation with Infrastructure as Code and CI/CD pipelines, and DevOps workflows. Security, compliance, and governance frameworks are examined to ensure regulatory alignment and operational integrity. Real-world case studies in financial, healthcare, and public sectors highlight best practices and lessons learned. Finally, emerging trends such as containerization, Kubernetes orchestration via OpenShift, and AI-driven automation are discussed, illustrating strategies for future-ready, efficient, and agile hybrid cloud deployments.
Kickstarting Your CRM A Strategic Guide To Integrating Salesforce With Legacy Systems
Authors: Sai Dubey
Abstract: Enterprises increasingly rely on hybrid IT environments that combine modern CRM platforms, such as Salesforce, with legacy systems like ERP, mainframes, and on-premises databases. Integrating these disparate systems is essential for operational efficiency, data consistency, and enhanced customer engagement. This review examines best practices for Salesforce-legacy system integration, including middleware solutions, API-based connections, data migration strategies, workflow automation, and CI/CD orchestration. The article also addresses identity and access management, security, and compliance considerations, highlighting real-world case studies in financial, healthcare, and public sector deployments. Finally, emerging trends such as AI-driven predictive analytics, cloud-native integration, and hybrid architectures are explored, providing insights into future-proofing CRM modernization efforts while maintaining operational resilience and regulatory compliance.
DOI: https://doi.org/10.5281/zenodo.17132099
Identity As The New Perimeter LDAP/AD Best Practices For A Hybrid IT Environment
Authors: Harshita Verma
Abstract: As enterprises adopt hybrid IT environments, traditional network perimeter defenses are no longer sufficient to protect critical resources. Identity has emerged as the new perimeter, with LDAP and Active Directory (AD) serving as foundational technologies for managing authentication, authorization, and access control across distributed systems. This review examines best practices for LDAP and AD management, including role-based access control, multi-factor authentication, automated provisioning and deprovisioning, monitoring, and incident response. It also explores integration strategies with cloud platforms, Single Sign-On (SSO), and DevOps workflows, highlighting real-world implementations and lessons learned from finance, healthcare, and government sectors. Finally, the article addresses emerging trends such as Zero Trust architecture, AI-driven behavioral analytics, and multi-cloud orchestration, emphasizing the evolving role of identity in securing hybrid IT infrastructures and ensuring compliance, operational efficiency, and resilience.
DOI: https://doi.org/10.5281/zenodo.17132184
Beyond The Sales Funnel Salesforce Automation And The Future Of Hybrid Infrastructure
Authors: Rohan Chopra
Abstract: Salesforce automation has become a critical component of enterprise CRM strategies, particularly within hybrid infrastructure environments that combine on-premises systems with cloud resources. By automating workflows, approvals, and data management, organizations can improve operational efficiency, reduce errors, and enhance customer engagement. This review examines the technical and business aspects of Salesforce automation, including integration strategies, middleware, CI/CD pipelines, and monitoring frameworks. Real-world case studies from financial services, healthcare, and government highlight lessons learned, best practices, and measurable benefits of automation in hybrid contexts. The article also explores emerging trends, including AI-driven predictive workflows, multi-cloud deployments, and edge computing, demonstrating how these innovations extend the value of Salesforce automation while ensuring scalability, compliance, and operational resilience.
DOI: https://doi.org/10.5281/zenodo.17132340
The UNIX Revival Why Solaris And AIX Still Matter In Todays Hybrid Cloud Landscape
Authors: Kiran Pandey
Abstract: Despite the rise of modern operating systems and cloud-native platforms, Solaris and AIX continue to play a critical role in enterprise IT infrastructure. These UNIX systems are renowned for their reliability, security, high availability, and performance, making them indispensable for mission-critical workloads in finance, healthcare, government, and other sectors. As enterprises adopt hybrid cloud strategies, integrating legacy UNIX workloads presents both challenges and opportunities. This review explores the technical strengths of Solaris and AIX, including virtualization, clustering, and resource management, as well as strategies for hybrid cloud integration, migration, and coexistence. Case studies illustrate real-world applications, lessons learned, and best practices for maintaining operational continuity while leveraging cloud scalability and modern services. The article concludes by assessing emerging trends, such as containerization, multi-cloud adoption, and AI-driven automation, demonstrating that Solaris and AIX remain strategic assets for hybrid cloud environments.
The Business Of IT How Kickstart Methodologies Drive Value In Hybrid Cloud Projects
Authors: Nisha Kumar
Abstract: Hybrid cloud adoption has become a critical strategy for enterprises seeking scalability, flexibility, and operational efficiency. However, the complexity of managing heterogeneous on-premises and cloud infrastructures often leads to deployment delays, resource inefficiencies, and increased operational risk. Kickstart methodologies provide a structured framework for automation, standardization, and repeatable deployment processes, enabling organizations to streamline hybrid cloud projects while ensuring consistency, reliability, and governance. This review explores the technical and business implications of applying Kickstart in hybrid cloud environments, highlighting benefits such as cost efficiency, accelerated time-to-market, risk mitigation, and improved operational agility. Real-world case studies illustrate practical applications, lessons learned, and best practices for leveraging Kickstart to optimize deployment pipelines, integrate DevOps workflows, and enhance IT value. By combining automation with strategic operational planning, Kickstart methodologies empower enterprises to achieve measurable business outcomes and future-proof their hybrid cloud initiatives.
DOI: http://doi.org/
The Websphere Modernization A Practical Guide To Migrating To Open-Source Jboss
Authors: Payal Verma
Abstract: Enterprise IT landscapes are increasingly seeking modernization pathways to reduce costs, enhance flexibility, and adopt cloud-native architectures. IBM WebSphere, long a cornerstone of enterprise middleware, presents challenges related to licensing costs, vendor lock-in, and scalability limitations. Red Hat JBoss (WildFly), as an open-source alternative, offers modular architecture, community-driven support, and adaptability for modern DevOps and containerized deployments. This review article provides a comprehensive guide for migrating from WebSphere to JBoss, covering architectural comparisons, migration planning, technical execution, integration strategies, testing methodologies, and post-migration operational considerations. Practical insights are drawn from case studies and lessons learned, emphasizing best practices in risk mitigation, automated deployment, security compliance, and performance optimization. By systematically analyzing the migration process, the article equips IT architects, system administrators, and enterprise decision-makers with actionable strategies to achieve a seamless transition while maintaining operational continuity, performance reliability, and long-term scalability.
DOI: http://doi.org/
The Impact Of AI-based Behavioral Monitoring On Insider Threat Detection
Authors: Hasina Chowdhury
Abstract: Insider threats, caused by malicious or negligent actions of employees, contractors, or trusted users, pose a significant challenge to organizational cybersecurity. Traditional security measures, including access control and periodic audits, often fail to detect subtle deviations in user behavior that indicate potential insider risks. AI-based behavioral monitoring has emerged as a transformative solution, leveraging machine learning, anomaly detection, and predictive analytics to identify unusual patterns, deviations, and risky activities in real time. By analyzing user interactions, access patterns, and contextual data, AI systems can generate dynamic risk scores, prioritize alerts, and guide security teams in taking proactive measures. This review examines the conceptual foundations, architectural frameworks, enabling technologies, and operational methodologies that underpin AI-driven behavioral monitoring. It highlights the techniques used to detect insider threats, including supervised and unsupervised learning, clustering, sequence analysis, and predictive modeling. The paper also discusses real-world applications across industries such as finance, healthcare, and critical infrastructure, demonstrating measurable improvements in threat detection, incident response, and compliance. Additionally, challenges such as data privacy, model interpretability, and false positives are analyzed. Finally, the review explores future directions, including explainable AI, adaptive learning, and privacy-preserving monitoring, positioning AI-based behavioral monitoring as a strategic enabler for proactive, resilient, and context-aware insider threat management.
DOI: http://doi.org/10.5281/zenodo.17882976
The Influence Of Intelligent Configuration Management On Reducing System Downtime
Authors: Tharushi Jayasuriya
Abstract: System downtime poses significant challenges for modern IT and industrial operations, often resulting in financial losses, productivity reductions, and compromised service quality. Traditional configuration management approaches, reliant on manual processes and static documentation, are prone to human error and delays, which can exacerbate system failures and prolong downtime. Intelligent configuration management systems (ICMS) have emerged as a transformative solution, leveraging artificial intelligence, machine learning, and predictive analytics to monitor, validate, and optimize system configurations in real time. These systems enable automated change tracking, anomaly detection, and proactive remediation, reducing the likelihood of misconfigurations and preventing system disruptions. By analyzing historical data and system dependencies, ICMS can predict potential failures and recommend corrective actions before incidents occur. This review examines the conceptual foundations, architectural frameworks, enabling technologies, and operational strategies that underpin intelligent configuration management. Additionally, it explores practical applications across IT infrastructure, cloud environments, manufacturing systems, and critical industrial operations, highlighting measurable reductions in downtime, improved reliability, and enhanced resource efficiency. The review also addresses challenges related to integration, data quality, security, and human oversight, while identifying future research directions such as autonomous self-healing systems, edge-enabled monitoring, and AI-enhanced root cause analysis. Intelligent configuration management is positioned as a strategic enabler for resilient, high-availability systems in complex operational environments.
DOI: http://doi.org/10.5281/zenodo.17883050
The Impact Of AI-driven Risk Scoring On Prioritizing Cybersecurity Vulnerabilities
Authors: Priya S. Bhatia
Abstract: The increasing sophistication and frequency of cybersecurity threats have made effective vulnerability management a critical priority for organizations of all sizes. Traditional approaches to vulnerability assessment often rely on manual evaluation or static scoring systems, which can be slow, resource-intensive, and unable to adapt to evolving threat landscapes. AI-driven risk scoring has emerged as a transformative solution, enabling automated, data-driven prioritization of vulnerabilities based on likelihood, potential impact, and exploitability. By integrating machine learning, predictive analytics, and real-time threat intelligence, AI systems can evaluate vulnerabilities across heterogeneous environments, dynamically assign risk scores, and guide security teams in allocating remediation resources efficiently. This approach not only reduces response times but also enhances accuracy by identifying high-risk vulnerabilities that might otherwise be overlooked. The review examines the conceptual foundations, architectural frameworks, and enabling technologies behind AI-driven risk scoring, alongside methodologies such as supervised and unsupervised learning, anomaly detection, and graph-based analysis. Additionally, it highlights practical applications across enterprise networks, cloud environments, and critical infrastructure, illustrating measurable improvements in threat prioritization and remediation effectiveness. Finally, the review discusses challenges related to data quality, model interpretability, and integration with existing security operations, while outlining future research directions in explainable AI, adaptive models, and autonomous vulnerability management. AI-driven risk scoring is positioned as a strategic enabler for proactive, scalable, and resilient cybersecurity operations.
DOI: http://doi.org/10.5281/zenodo.17883072
Intelligent Configuration Management For Enterprise Linux Using AI-Assisted Infrastructure-as-Code
Authors: Vinay Kumar Reddy Vangoor
Abstract: Enterprise Linux environments face persistent challenges in configuration management at scale, including configuration drift, compliance violations, and the high manual overhead required to maintain consistent system states across large server fleets. Traditional Infrastructure-as-Code (IaC) tools such as Ansible, Puppet, and Chef provide automation frameworks but demand significant human expertise to author, validate, and evolve configuration playbooks, creating a critical bottleneck in operational efficiency. This paper presents the AI-Assisted Configuration Management Framework (AICMF), an end-to-end system that integrates large language models (LLMs) with existing IaC pipelines to automate playbook generation, semantic policy validation, and continuous configuration enforcement across enterprise Linux environments. The framework employs a fine-tuned transformer-based model augmented with retrieval-augmented generation (RAG) to interpret natural language configuration intents and produce syntactically correct, policy-compliant IaC artefacts. A continuous drift detection module performs real-time state reconciliation against defined baselines, triggering automated self-healing pipelines with tiered human-in-the-loop approval gates for risk-proportionate oversight. Experimental evaluation across a 1,000-node heterogeneous Linux testbed comprising RHEL 9, Ubuntu 22.04 LTS, and CentOS Stream 9 over a 12-week period demonstrates a playbook accuracy rate of 94.3%, a 78.6% reduction in mean-time-to-remediate compared to manual baselines, a drift detection latency of 47 seconds with a 3.8% false positive rate, and a CIS Level 2 benchmark compliance rate of 91.3%. These results establish that AI-assisted IaC substantially reduces operational overhead while improving system reliability, security posture, and auditability in enterprise Linux deployments.
DOI: https://doi.org/10.5281/zenodo.19183576
Machine Learning For Cloud Cost Anomaly Detection
Authors: Sanduni Fernando
Abstract: The rapid migration of organizational workloads to cloud environments has introduced unprecedented scalability but also significant financial complexity. Cloud billing is often characterized by high-volume, granular data where "anomalies"—unexpected spikes or shifts in spending—can remain undetected for weeks, leading to "cloud sprawl" and budget overruns. Traditional threshold-based monitoring systems often fail in these dynamic environments due to their inability to distinguish between legitimate scaling and genuine waste. This article reviews the shift toward Machine Learning (ML)-centric approaches for cloud cost anomaly detection. By leveraging time-series forecasting, clustering, and deep learning, ML models can learn the "seasonal" rhythms of business operations and flag deviations with high precision. This review explores the architectural foundations of these systems, evaluates supervised versus unsupervised learning paradigms, and discusses the operational challenges of implementing AI-driven FinOps. Ultimately, the integration of ML transforms cost management from a reactive reporting task into a proactive, automated defense mechanism, ensuring operational stability and financial efficiency in modern cloud-native architectures.
DOI: https://doi.org/10.5281/zenodo.19491753
Deep Learning-Based Intrusion Detection Systems For Enterprise Networks
Authors: Siti Amina
Abstract: Deep learning-based intrusion detection systems (IDS) have emerged as a transformative approach for securing enterprise networks in the face of increasingly sophisticated cyber threats. Traditional signature-based and rule-based IDS solutions struggle to detect zero-day attacks, polymorphic malware, and advanced persistent threats due to their reliance on predefined patterns. In contrast, deep learning models offer the ability to automatically learn hierarchical feature representations from large-scale network traffic data, enabling improved detection accuracy and adaptability. This review examines the evolution, methodologies, and practical implementation of deep learning-based IDS in enterprise environments. It highlights the role of architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and transformer-based models in identifying anomalous and malicious activities. The study further explores data preprocessing techniques, feature engineering, and benchmark datasets commonly used for training and evaluation. Key challenges, including data imbalance, model interpretability, computational overhead, and real-time deployment constraints, are critically analyzed. Additionally, the integration of deep learning IDS with emerging technologies such as cloud computing, edge computing, and software-defined networking (SDN) is discussed. The review concludes by outlining future research directions focused on improving scalability, explainability, and resilience against adversarial attacks. Overall, deep learning-based IDS represent a promising paradigm shift in enterprise cybersecurity, offering intelligent, adaptive, and proactive defense mechanisms.
DOI: https://doi.org/10.5281/zenodo.19491764
Published by: vikaspatanker
