MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

Engineering and Technology

Opportunistic forwarding mechanism in Delay Tolerant Networks (DTN), are prone to get disconnected from the nodes in the network. These types of networks deal with intermittent connectivity, large delays.Existing routing protocols of DTNs fights with these issues, but fail to integrate the security available for delay tolerant networks,it is necessary to design a secure routing protocol to overcome these issues. There are centralized Trust Authority (TA) based security systems but the disconnection or failure of TA, affects the security model and network performance. It becomes crucial to have the distributed approach for security system and have multiple TAs working on security model. This reduces the possibility of poor network performance. The paper presents a distributed misbehavior detection system, and implements multiple TAs for implementing the security model for DTN.

School of Computer Engineering & Technology

World University root node

Fulltext

International Journal of Innovative Technology and Exploring Engineering

Distributed Misbehavior Detection System for Delay Tolerant Networks

Stress has become a universal emotion that people experience in day to day life. In this paper, emotion detection is carried out using benchmark DEAP dataset by implementing a new feature extraction techniques named as Teager-Kaiser Energy Operator (TKEO) with a k-nearest neighbor (KNN), neural network(NN) and Classification Tree (CT) classifiers based on Electroencephalography (EEG). The study evaluates the performance and accuracy of emotion detection which is further used for stress identification as EEG gives good correlation with stress. Also, the present work compares the implemented TKEO feature extraction technique with Relative Energy Ratio (RER), and Kernel Density Estimation (KDE) techniques regarding accuracy. This paper demonstrates how the inclusion of TKEO enhances feature extraction and proves a promising approach to emotion detection as compared to other conventional techniques. The experimental results show that TKEO when used with KNN, NN, CT classifier gives comparatively higher accuracy than KDE and RER for channel 1 alpha band and channel 17 beta band for stress detection.

International Journal of Innovative Technology and Exploring Engineering (IJITEE)

Human Emotion Detection and Stress Analysis using EEG Signal

Hand gesture recognition is challenging task inmachine vision due to similarity between inter class samples andhigh amount of variation in intra class samples. The gesturerecognition independent of light intensity, independent of colorhas drawn some attention due to its requirement where systemshould perform during night time also. This paper provides aninsight into dynamic hand gesture recognition using depth dataand images collected from time of flight camera. It provides userinterface to track down natural gestures. The area of interest andhand area is first segmented out using adaptive thresholding andregion labeling. It is assumed that hand is the closet object tocamera. A novel algorithm is proposed to segment the hand regiononly. The noise due to ToF camera measurement is eliminated bypreprocessing algorithms. There are two algorithms which wehave proposed for extracting the hand gestures features. The firstalgorithm is based on computing the region distance between thefingers and second one is about computing the shape descriptor ofgesture boundary in radial fashion from the centroid of handgestures. For matching the gesture the distance between twoindependent regions is computed for every row and column. Sameprocess is repeated across the columns. The number of totalregion transitions are computed for every row and column. Thesenumber of transitions across rows and columns forms the featurevector. The proposed solution is easily able to deal with static anddynamic gestures. In case of second approach we compute thedistance between the gesture centroid and shape boundaries atvarious angles from 0 to 360 degrees. These distances forms thefeature vector. Comparison of result shows that this method isvery effective in extracting the shape features and competentenough in terms of accuracy and speed. The gesture recognitionalgorithm mentioned in this paper can be used in automotiveinfotainment systems, consumer electronics where hardwareneeds to be cost effective and the response of the system should befast enough.

School of Electrical Engineering

International Journal of Engineering and Advanced Technology (IJEAT)

Real Time Static Gesture Recognition using Time of Flight Camera

Earthquake forces on structure are of great concern to the engineers. To minimize the effects of an earthquake and lateral loads,the steel braced frames are used. It is one of the systems which plays an effective role in resisting the lateral loads the new type of bracingsystem called buckling restrained braces are introduced to overcome the drawbacks of conventional bracing system. The project work is tostudy buckling restrained braces. The analysis is done using MATLAB. In the present study, a code for a building model is developed toanalyze the behaviour of the structure without BRB. Time history method is used to determine the dynamic response of the structure. Amathematical model was created to perform modal time history analysis. Time stepping was performed using Newmark’s Beta modified forlinear acceleration. The response parameters such as Base Shear, Story displacement, Time period, Inter-story drift are evaluated to studythe structural performance. The same model results are validated in ETABS v16. Further, a code will be developed for a building structurewith BRB to compare the response of both structures.

School of Civil Engineering

International Journal of Scientific and Technology Research

Design and Development of Buckling Restrained Brace using MATLAB

Predicting the binding mode of flexible polypeptides to proteins is an important task that falls outside the domain of applicability of most small molecule and protein−protein docking tools. Here, we test the small molecule flexible ligand docking program Glide on a set of 19 non-$α$-helical peptides and systematically improve pose prediction accuracy by enhancing Glide sampling for flexible polypeptides. In addition, scoring of the poses was improved by post-processing with physics-based implicit solvent MM- GBSA calculations. Using the best RMSD among the top 10 scoring poses as a metric, the success rate (RMSD ≤ 2.0 \AA for the interface backbone atoms) increased from 21% with default Glide SP settings to 58% with the enhanced peptide sampling and scoring protocol in the case of redocking to the native protein structure. This approaches the accuracy of the recently developed Rosetta FlexPepDock method (63% success for these 19 peptides) while being over 100 times faster. Cross-docking was performed for a subset of cases where an unbound receptor structure was available and in that case, 40% of peptides were docked successfully. We analyze the results and find that the optimized polypeptide protocol is most accurate for extended peptides of limited size and number of formal charges, defining a domain of applicability for this approach.

School of Electronics & Communication Engineering

School of Management PG

Management

ASM's International E-Journal on ‘Ongoing Research in Management {&amp;} IT

Effect of Organizational and Occupational Commitment on Satisfaction and Performance of Medical Representatives

Energy of nodes plays an important role in all kinds of networks whether it is wired network or wireless network, since most of the nodes are battery powered and it is not possible to recharge the battery whenever necessary. In most of the networks, the data cannot be sent completely when the connection is terminated from source to destination. Hence, the concept of delay-tolerant network (DTN) is introduced. In DTN, due to the mobility of nodes most of the nodes have sufficient amount of energy which is required for transferring of data. Energy is crucial issue in the concept of DTN, especially in disastrous like scenario, where recharging of battery becomes difficult. The proper use of energy for data transmission increases nodes lifetime and network lifetime situation. In this paper, some of the energy-saving techniques are explained to reduce the energy consumption of the node and also increase the packet delivery ratio. © Springer Nature Singapore Pte Ltd. 2019.

Advances in Intelligent Systems and Computing

Social energy-based techniques in delay-tolerant network

Technology is being used everywhere in our daily life to fulfill our requirements and aid our lives in every sphere including communication, traveling, entertainment, etc. But it has not been used up to its full potential in the field of health care. Real-time monitoring of patients and doctors is the primary concern of any healthcare facility and the conventional methods used in the hospitals are not being able to address these concerns efficiently. Our proposed system aims to provide a better service to the patients as compared to the conventional methods. It comprises of sensors for measuring temperature and pulse rate. A processor working in synchronization monitors the vitals of the patient and sends the captured data to the personal digital assistant (PDA) of head nurse and the doctors. In the PDA, an intelligent application gives statistical data of the vitals of patient in real-time manner. This data is used to analyze the health condition of patient over a period of time as well as monitor the patient in a real-time environment, remotely. We are also incorporating a coronary heart disease (CHD) predicting mechanism to determine whether a patient is susceptible to CHD. This mechanism is based on the concept of Traditional Chinese Medicine (TCM), which states that a large number of diseases (immaterial of the amount of severity they pose) can be diagnosed by sensing the pulse variations. This methodology is the foundation on which support vector machine (SVM) is predicting CHD in patients. © 2019, Springer Nature Singapore Pte Ltd.

A proposed system for the prediction of coronary heart disease using raspberry pi 3

According to the census of India 2011. In India, 70 million people have some kind of disability, among of that 18% of people are speech and hear impaired. That means India is the country which has a large number of people having this kind of disability. These people experience the problem to participate in society and the enjoyment of equal rights and opportunities. Because they don't have the power to express feelings in the form of words and sentence. So the people try to deal with this problem using different techniques. In this paper, a smart hand sign interpretation system using a smart glove is proposed to reduce the communication gap between speech impaired people and the normal people. This wearable system utilizes five flex-sensors, 3-axis accelerometer, one Bluetooth module and 16∗2 LCD display. In this system, processor collects data from the 5 flex sensors and accelerometer. Further processor matches the data which is received from the sensors and the previously saved data. If data matched with the saved data then assigned meaning for that data will be displayed on LCD screen and also send it to the Android mobile through Bluetooth. Android mobile app can convert this into voice. So this system has an ability to convert sign language into a voice in a very simple way. © 2018 IEEE.

Proceedings of the 2nd International Conference on Intelligent Computing and Control Systems, ICICCS 2018

Hand Sign Recognition Based Communication System for Speech Disable People

IN Patent App. 201,721,045,801

AUTOMATIC CHANNEL SWITCH SYSTEM TO ESCAPE COMMERCIAL BREAK

This research paper is focused on Industry 4.0's importance, effect and thus the Internet-connected techniques for organizations and society to create value-Added structure. Industry 4.0 is the fourth industrial revolution which is based on cyber-physical systems, where assets can gather, store, and analyze the real-Time data to improve utilization efficiency. The internet of things pivotal to the new industrial revolution has resulted in 'Industry 4.0'. This paper's aim is to synthesize the recognized theory and methods of Industry 4.0 and to study the modifications resulting from Industry 4.0 and the development of the internet of things. The case study based on digitizing radiator and intercooler manufacturing processes to improve utilization efficiency is presented. © 2019 IEEE.