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

Construction projects and its complexities are increasing in recent years along the demand of customers towards the quality of construction projects in its high level. The implementation of qualitymanagementsystem(QMS) has been a solution to achieve the required level of quality as per ISO 9001 standards. The paper includes major factors affecting the quality of residential buildings during the construction particularly in execution phase and the level of management commitment towards the implementation of quality management at residential construction projects. The data was collected through questionnaire; interview and document review which includes visiting ofsome construction companies and conduct the questionnaire survey then analysis in quality management to find the results and conclusion. The findings have shown that the companies need of a higher level of management commitment with respect to critical parameters towards the implementation of quality management at residential construction projects.

World University root node

School of Civil Engineering

International Research Journal of Engineering & Technology

Quality Management System(QMS)at Residential Construction Project

India loses 3% of its GDP due to road accidents. Significance of Geopathic stress as a causative factor of road accidents has been studied by few researchers; however its effect on Pavement distresses and hence road accident is yet unexplored. The aim of this research is to determine the correlation between average number of accidents, Pavement Condition Index (PCI) values and Geopathic stress. Accident data was collected from Pune traffic department for 3 years period from 2015-16 to 2017-18. Based on the number of accidents during this period accident blackspots were found. On each black spot pavement distresses survey was carried out and its condition was analyzed by Indian Road Congress (IRC) 82:2015 code method. At these accident blackspots detection of geopathic stress was done by using 2 copper L-rods, lecher antenna. Intensity was measured in terms of electrical and magnetic field. Electrical field reading was measured using Esmog-spion and magnetic field reading was measured by magnetometer. Data was analyzed using Karl Pearson’s correlation coefficient and a linear regression model is developed for average number of road accidents (Ā) with Pavement Condition Index (PCI). Utility of the equation is for forecasting the number of fatal accidents at similar black spots based on their pavement distress condition. A further attempt is to investigate the effect of electric and magnetic characteristics of geopathic stress on road accidents.

Fulltext

International Journal of Innovative Technology and Exploring Engineering

Geopathic Stress:Apossible cause of pavement Distresses and Road Accidents

In aerospace and aircraft construction it is essential that materials with a high strength to weight ratio be used. For thisreason, the designer tries to get the last ounce of strength out of each part. An increasing scarcity of resources and their growing expensedemands a reduction in energy consumption for passenger and goods transportation. Here, the aerospace and aviation sector plays a specialrole with respect to the application of new materials. There is probably no other material more closely related to aerospace and aircraftthan titanium and its alloys. With a density of 4.Jg/cm³, titanium alloys are only about half as heavy as steel or Ni-based super alloys,yielding a unique combination of strength and lightness. Furthermore, then have exceptional corrosion resistance favorsthe use of titaniumalloys in the aerospace and aviation sector.

School of Mechanical Engineering

International Journal of Creative Research Thoughts

Use of titanium and its alloy in aerospace and aircraft industries

Automatic number plate recognition recent the recent Trend in current environment, various systems has already developed by existing authors to detect the license plate as well as number plate using machine learning and deep learning algorithms. Internet of things (IoT) and some machine learning techniques for image processing is also contributed many classical systems. In this paper we proposed automatic number plate recognition for smart toll system, in traditional approach it is very tedious to perform the entire process with manual human interfaces. Sometime it also generate long traffic queue on toll plaza, to eliminate such a problem with this propose systems. This system initially deals with some IoT devices which contains camera sensor and arduino based microcontroller. The deep learning libraries have used to process the capture image by IoT environment with OCR library. This system also deals with user applications to auto debit toll charges. The state of art provides the conceptual model of entire system execution with real time as well as synthetic dataset, and theoretical experiment analysis shows the effectiveness of system.

School of Computer Engineering & Technology

CLIO Annual Inter disciplinary Journal of History

Vechile Number Plate Recognition for automatic toll tax collection using IoT and Machine Learning

School of Electronics & Communication Engineering

International Journal of Scientific Research and Engineering Trends

INTELLIGENT TRAFFIC MONITORING SYSTEM USING IOT

Cardiac Arrhythmia is a condition in which the heartbeat is may be fast or slow than the normal ones. Nowadays, a consistent electrocardiogram (ECG) analysis and classification play an important role in the diagnosis of cardiac abnormalities. ECG provides useful information about the functional status of the heart. Analysis of ECG is of great importance in the detection of cardiac anomalies. This paper provides different medical data mining and machine learning techniques are being implemented to extract valuable information from ECG signal for prediction of heart disease. But, the accuracy of the desired results is not yet satisfactory.

Journal of Emerging Technologies and Innovative Research

Heart Disease Detection Using ECG Waves: A Survey

Blockchain is very emerging trend in recent years; it is basically decentralized approach whichprovides transparency to transactional data. While data security is the most essential requirement inthe 21st century, distributed as well as the centralized environment. Identifying or validate the user'sidentity based on educational histories is a very tedious task. Many commercial applications validateby respective organizations based on physical verification. Search systems do not provide trustworthyinformation when declared on a centralized data basis, due to two database security concerns. Variousdatabase and software base intrusion attacks can harm centralized data and change the actualinformation. This paper, the system illustrates blockchain base e certificate generation for theeducational field. In a real- time scenario, many organizations make document verification ofparticular employees on traditional approaches like physical verification, etc. The system proposes isE-certification and token generation using a strategic process which provides hassle-free e verificationfor the organization of specific employee. This system also carried out custom blockchainimplementation with dynamic smart contract, and mining policy, which generate the UniqueIdentification (UID) number and QR code for each user for online verification. The final phase providesvarious consensus algorithms for drastic data verification and majority voting in the P2P network. Thepartial implementation of the system shows the effectiveness of the proposed system over the traditionalapproaches.

CLIO An Annual Interdisciplinary Journal of History (CLIO AIJH), ISSN: 0976-075X

Generation of E-Certificates using Custom Blockchain for Peer to Peer Network

Nowadays, There is a need to think about the major causes of pollution, one of which is crude oil, the plastic is used worldwide today. Plastic is found everywhere. Creation of plastics was a boon for low cost substitution to metal, being cheap is now causing environment problem. Plastic and polymer-carbon chains have long life and could be classified according to the uses. This has lead us to a point where waste plastics in the tons are causing various environmental hazards, not to mention the shame it bring to one’s mind when he sees his own country littered with it. It is still on the places of landfills and oceans, which has become major concern of the world. There is a need to think of this issue as it’s leading to impact environment seriously. There is ever increasing global demand for energy in recent years. A pyrolysis process provides an alternative energy source which reduces pollution and recycles waste plastics. In this study, pyrolysis of waste plastic is solution for the issue in the current world, disposal of waste plastic will also be minimized if applying pyrolysis process in different cites & make the environment clean. This paper deals with extracting pyrolysis oil/pyro fuel from waste plastic that is found in everyday life & by recycling to make out pyrolysis fuel & reduce carbon emission. This project leads to a meaningful contribution to Swatch Baharat Abhiyan & Paris climate deal.

GIS Science Publication

Waste Plastic Pyrolysis: An efficient way of Plastic recycling

Aesthetic&nbsp;assessment&nbsp;of&nbsp;images&nbsp;has&nbsp;been&nbsp;getting&nbsp;a&nbsp;lot&nbsp;of&nbsp;attention&nbsp;for&nbsp;the&nbsp;past decade&nbsp;in&nbsp;the&nbsp;field&nbsp;of&nbsp;computer&nbsp;vision.&nbsp;Large&nbsp;amounts&nbsp;of&nbsp;social&nbsp;media&nbsp;and&nbsp;advertising&nbsp;data&nbsp;in the&nbsp;form&nbsp;of&nbsp;images&nbsp;is&nbsp;continuously&nbsp;analysed&nbsp;to&nbsp;assign&nbsp;it&nbsp;an&nbsp;aesthetic&nbsp;quality&nbsp;value&nbsp;to&nbsp;improve businesses&nbsp;as&nbsp;well&nbsp;as&nbsp;for&nbsp;gaining&nbsp;more&nbsp;popularity&nbsp;across&nbsp;the&nbsp;web.&nbsp;Visual&nbsp;perception&nbsp;by&nbsp;humans cannot&nbsp;be&nbsp;fully&nbsp;replicated&nbsp;by&nbsp;a&nbsp;machine&nbsp;and&nbsp;continuously&nbsp;more&nbsp;work&nbsp;is&nbsp;being&nbsp;published&nbsp;on&nbsp;aes- thetic&nbsp;classification&nbsp;of&nbsp;images.&nbsp;In&nbsp;this&nbsp;paper,&nbsp;we&nbsp;have&nbsp;presented&nbsp;a&nbsp;convolutional&nbsp;neural&nbsp;network model&nbsp;which&nbsp;automatically&nbsp;extracts&nbsp;high&nbsp;level&nbsp;features&nbsp;and&nbsp;distinguishes&nbsp;a&nbsp;set&nbsp;of&nbsp;images&nbsp;into pleasing&nbsp;and&nbsp;non-pleasing&nbsp;categories.&nbsp;Our&nbsp;dataset&nbsp;has&nbsp;been&nbsp;compiled&nbsp;from&nbsp;a&nbsp;variety&nbsp;of&nbsp;sources on&nbsp;the&nbsp;web&nbsp;to&nbsp;make&nbsp;it&nbsp;as&nbsp;diverse&nbsp;as&nbsp;possible.&nbsp;Compared&nbsp;to&nbsp;the&nbsp;traditional&nbsp;handcrafted&nbsp;meth- ods&nbsp;and&nbsp;other&nbsp;machine&nbsp;learning&nbsp;models,&nbsp;our&nbsp;CNN&nbsp;model&nbsp;has&nbsp;provided&nbsp;a&nbsp;better&nbsp;classification accuracy of 68% on our&nbsp;dataset.

International Journal for Research in Applied Science and Engineering Technology

Assessing High level Aesthetic Image Features using Deep Learning

Nowadays, there is a rapid growth in the number of video cameras at public and private sector because of the monitoring and security purposes. As video surveillance using Closed Circuit Television (CCTV) is in boom nowadays, it has got more research attention due to increased global security concerns. This rapidly growing data can be used to automatically detect the anomalous activities which are going around in our surrounding. Anomalous activity is something that deviates from its normal nature or something that opposes the normal events. This research mainly focuses on detecting anomalous activities in crowded scenes by using video data. Automatically detecting the anomalous activity without using the handcrafted feature has become the need of the hour. This paper contains a survey of different approaches used for anomaly detection in the past. Different incremental and transfer learning approaches are discussed in this paper and it was found that incremental learning has not been used for video-based anomalous activity detection.