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

Air pollution is a growing threat towards society and various measures are being taken recently to control it. The problem of concern which remains is the efficient prediction of air pollution to work in the right direction for reducing the same. Since the AQI follows a periodic pattern, deep learning models can be used to effectively predict the future AQI values. LSTM being a prominent time series forecasting model can be integrated with a separate DNN model to effectively add the impact of weather, temperature and other factors that can affect the future AQI values. The paper also explores the impact of having a parallel DNN to the LSTM cell instead of using the cell alone. © 2020 IEEE.

World University root node

School of Computer Engineering & Technology

2020 International Conference for Emerging Technology (INCET)

Air Quality Index forecasting using parallel Dense Neural Network and LSTM cell

Materials used currently in dental implantology include pure titanium and titanium alloy namely- along with polymers and ceramics. Owing to their excellent mechanical properties such as lower modulus of elasticity, better fatigue strength, and higher corrosion resistance, they are more preferred for replacing a missing tooth in patients. The surface of dental implant plays a crucial role in determining the success for osseointegration with the human cells. Broadly classified, a successful implantation is the outcome of correlation between three factors, namely: osseointegration, fatigue endurance, and longevity of the implants subjected to masticatory forces offered by humans. The main objective of this review is to comprehensively understand the causes of fatigue and analyse through a mechanical aspect. The central theme of this article is the surface properties of a dental implant. A sequential breakdown of parameters such as dimensions of the implant, surface roughness, and surface coating thickness along with the advantages and disadvantages of surface treatment and surface coating methods on the fatigue life performance of implants have been presented. The experimental validity of all attributes mentioned in most of the literature have confirmed that fatigue failure is the most common mode of failure occurring in dental implants. Hence it becomes imperative to research the causes in depth and aim at controlling the factors to enhance the fatigue life of dental implants. This review gave an outline of the different attributes which affect fatigue failure in dental implants when subjected to masticatory forces. © 2020 Elsevier Ltd.

School of Mechanical Engineering

Materials Today: Proceedings

A comprehensive review of factors affecting fatigue life of dental implants

According to the World Health organization, 5% of the world population, approximately 466 million people, is deaf and/or mute or has disabling hearing loss. There is often a wall of distinction between handicapped people and normal people. We communicate to share our thoughts but for a disabled person (mainly deaf and dumb), it becomes difficult to communicate. Inability to speak is considered to be a true form of disability. For such people, sign language or Braille is the only means of communication. Sign Language is a way of communication using hand gestures. However, it becomes difficult for them to communicate with others as most don't understand sign language. Hence, we aim at bridging this communication gap, between a deaf/mute person and others, by developing a system which acts as a mediator between both. We propose a hand gesture recognition system which works in 4 steps: 1. Generate a live stream of hand gestures using web-cam. 2. Form images from the video using video frames. 3. Preprocess these images. 4. Recognize sign language hand-gestures and convert into text/audio output. The system is implemented using the concepts of image processing and neural networks. We have tested the proposed models using Kaggle dataset, our dataset and a dataset formed after combining both. We propose to eliminate the ambiguity introduced in the results by inculcating variation in the background. Most of the models give similar accuracy of the test results for both plain and cluttered background. © 2020 IEEE.

2020 IEEE 5th International Conference on Computing Communication and Automation, ICCCA 2020

Models for Hand Gesture Recognition using Deep Learning

Even though water is a renewable resource, most of the water present on the earth’s surface is not suitable for direct human consumption. Besides, due to increasing population, urbanization, environmental pollution and growth of industries, the requirement for pure water is found increasing day by day. Also, natural resources of water can meet freshwater demand to only to a limited extent. Hence, there is a need to find a way to purify saline water with the help of an effective water desalination technique. Solar still is one such method which makes use of naturally available sunlight to purify impure/saline water. In this paper, a double-effect passive solar still is designed for experimental investigations to determine the freshwater collected at the output channel. Also, a two-phase, three-dimensional model of the unit is developed in ANSYS FLUENT for the transient state to simulate various temperatures inside the solar still and to estimate the production rate of distilled water produced. The simulation was run for 8 h, and the results have been compared with the experiment performed. Experimental investigations show a total distilled output of 3.2 L/m2 collected in channel, whereas according to analysis results, 3.74 L/m2 output is observed. Here, simulation results follow the similar trend as the experimental results and show good agreement with each other.

Journal of The Institution of Engineers (India): Series C

Experimental Investigation and Performance Analysis of Double-Basin Solar Still Using CFD Techniques

The data aggregation highly reduces the energy consumption in the network and hence their is a requirement for involving aggregation of data from multiple nodes. These techniques are considered as remove the crucial for successful applications in Wireless Sensor Network (WSN). This paper proposes Group Search Optimization (GSO) algorithm with Neural Network (NN) for developing the novel query-based data aggregation model. The Querying Order (QO) model in the scheme uses Query Order that can be ranked on the basis of latency and throughput. The paper aims to build up the QO model with low latency and high throughput thereby enhancing existing data aggregation techniques. Thus it can assist the network administrator to get the knowledge regarding the best queries for enhancing the performance of the sink. Further, it compares the performance of conventional methods by analyzing the latency as well as throughput of the network. It reveals that the data aggregation performance of the proposed model outperforms the conventional models as it minimizes latency and maximizes throughput.

Ad-hoc & Sensor wireless network

Optimized Query Ordering Data Aggregation Model using neural Networks and Group Search Optimization in Wireless Sensor Network

Texture segmentation is one of the popular researchdomains and researchers across the globe are working on texturesegmentation to enhance segmentation performance to address itsrequirements in many fields. Color texture segmentation has widespectrum of applications in diverse fields such as segmentation ofnatural images, medical image analysis, remote sensing, shapeextraction and inspection of products etc. This paper presentscolor texture segmentation algorithm which can satisfyrequirements for such applications. Proposed algorithm is basedon Markov Random Field (MRF) model eliminating the need ofmajor contributor viz. Gabor filter used in past four decades forfeature extraction and use only color as texture feature. Highlycrude segmentation results are produced using only color astexture features. Crude segmentation results are enhanced byusing Median filter with enlarged window size quantitativelydetermined by using parameters viz. structural similarity index(SSIM), mean square error (MSE) and peak signal to noise ratio(PSNR). Feature space dimensions are reduced by factor of 11 inproposed approach and this reduced computations by a factor of11. The experimentation is carried out on 80 multi-class colortexture benchmark images from Prague texture segmentationdataset and 4 benchmark images in Vistex dataset. Meansegmentation accuracy achieved for Prague texture dataset is87.55% and it is higher by 9.82% over the best performingalgorithm among 11 state-of-art algorithms suggested in mostrecent literature. Accuracy achieved for Vistex dataset is 98.21%.Average SSIM for Prague dataset is 0.91403 and Vistex dataset is0.9405.

School of Electronics & Communication Engineering

Fulltext

International Journal of Recent Technology and Engineering

Markov Random Field based Color Texture Segmentation

The stringent emission norms, increasing demands for higher efficient and reliable engine operation and rapid depletion of petroleum resources, motivated researchers to explore on advanced combustion and ignition technologies as well as the use of alternative fuels for internal combustion (IC) engines. Lean burn combustion with high spark energy is an advanced combustion approach that improves thermal efficiency, reduces knocking tendency, exhaust emissions, especially NOx (Nitrogen oxides), and heat transfer. However, there are many difficulties in current operating engines with lean mixtures like slower flame initiation, incomplete combustion, increased cyclic variation and potential misfiring, etc. which causes decreased efficiency, power output, and excessive emission. The exhaust gas recirculation (EGR) can reduce nitrogen oxide (NOx) emissions but increases particulate matter (PM) and have ignition problem during engine idle operation.The conventional electric discharge ignition system performs well at normal operating conditions; however, for igniting lean mixtures require significantly higher spark energy with multi-point ignitions. The higher spark energy will increase the ignitibility but decrease the life of spark plug due to electrode erosion, and electrodes act as a thermal energy sink. However, multi-location ignitions with conventional electric discharge systems will require several electrodes. Therefore to overcome these difficulties, the multi-point laser-induced ignition is an innovative alternative approach to burn lean mixtures compared to the conventional electric discharge ignition system. A laser is a high energy electrode less ignition source with the easy possibility of multi-location ignitions. Therefore, this article aims is to review various techniques used for multi-point laser ignition and its impact on combustion characteristics and engine performance. The effect of laser energy and ignition locations on combustion characteristics has also been reviewed. Also, demonstration and realization of the laser spark plug with multiple beam output, which can be used as multi-point igniters in internal combustion engines has been reviewed.

Optics and Laser Technology

Review: Multipoint laser ignition system and its applications to IC engines

Availability of Crude oil in India is tend to be light and sweet. The generalproduction value per barrel per day is 880, with specific gravity varying from32 API to 38 API.This text covers all forms of enhanced oil recoverytechniques with both fundamental principles and specialized applications.Students in all areas of fluid flow in permeable media and professionalresearchers can benefit from the unified approach to EOR based on commonfirst principles, conservation of mass, momentum, and energy. Mathematicaltechniques based on phase behavior and the method of characteristics (MOC)are fundamental to the text.

School of Petroleum Engineering

International Journal of PetroleumScience and Technology

Review of Enhanced oil recovery techniques

Biodiesel as an alternative fuel is overcoming to replace petroleum diesel partially. The tribological performance of biodiesel is crucial with respect to application in automobiles. Cast iron is widely used in for manufacturing of many automobile engine parts such as piston, valves, piston rings, etc. This research article evaluates the wear behavior of spheroidal graphite cast iron which is used for the manufacturing of piston rings with respect to different blends of biodiesel. Many experiments were carried out under metal to metal contact and lubricated sliding condition on, pin on disc wear testing machine. This shows the metallographic changes due to wear damage. Previous experimental result shows that friction coefficient and wear loss decreases significantly due to decrease in lubrication percentage of palm biodiesel. The test parameters used under this work were 8 kg, 10 kg, 12 kg, 14 kg and 16 kg loads for 1 h, at speed 300 rpm and at ambient temperature. Wear behavior of spheroidal graphite cast iron is evaluated using five different blends of biodiesel, B0 (100% petroleum diesel), B5 (5% biodiesel), B10 (10% biodiesel), B20 (20% biodiesel), B100 (100% palm biodiesel)).The period for which cast iron can sustain is determined by its wear and abrasion resistance. Due to formation of lubrication layer of ester compounds in palm biodiesel wear resistance of nodular cast iron increases as biodiesel percentage increase in the blend. Therefore, high wear resistance is critical for ensuring a long life of the cast iron in biodiesel environment. The results showed that the B100 has higher coefficient of friction and lowest surface roughness and wear volume loss as compared with petroleum diesel (B0). It also shows that wear and friction decrease as percentage of biodiesel increases. Scanning electron microscopy (SEM) investigations used to analyze the structure and surface morphology. Wear scar diameter (WSD) was investigated using optical microscopy in tested specimen. The wear rate was found to be more in petroleum diesel compared with palm biodiesel than other blends.