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

School of Electronics & Communication Engineering

International Journal of Management, Technology And Engineering

AI Coach for Badminton

Agriculture is a very important factor for human beings to make economy. 45% of world’s population depends on agriculture for their livelihood. Fruit production and harvesting is too essential. It has a great demand in national as well as international markets. But fruits harvesting is still done with the traditional methods which requires huge man-power, too much of cost and time consuming. Therefore, the use of innovative agriculture based technologies and systems are very needful for the agriculture field. So in this paper, combination of all the very recent fruit detection and fruit segmentation techniques using deep-learning (DL) approach have been considered. Comparative study of all the fruit detection and fruit segmentation techniques has been done. Based on review, conclusions have been made to give directions to future research challenges along with the future scope.

World University root node

Second International Conference on Image Processing and Capsule Networks. ICIPCN 2021

A Review on Fruit Detection and Segmentation Techniques in Agricultural Field

Diabetic Retinopathy (DR) is a diabetes complication that affects vision. It is caused by damage to the blood vessels of retina. Early and accurate detection of DR is crucial to reduce likelihood of progression to proliferative retinopathy and blindness. This paper proposes a method for classifying the severity of DR using deep learning. Experiments were conducted by blending the members of EfficientNet for classification of the diabetic retinopathy image as no DR, mild, moderate, severe, or proliferative DR. The models have been trained using different datasets and best model achieved a quadratic kappa score of 0.924377 on the APTOS test dataset. The results are promising and warrant further investigation. The presented model has the potential aid in fast diagnosis for better early detection of DR.

School of Computer Engineering & Technology

2021 International Conference on Emerging Smart Computing and Informatics, ESCI 2021

Diabetic retinopathy classification using a combination of EfficientNets

School of Mechanical Engineering

Materials Today: Proceedings

Analyzing Relation of Canal Operating Force and Canal Curvature in RCT: A Mathematical Overview

Two different alternatives over conventional leaf spring are developed in this work, such as composite and hybrid composite-based leaf springs. In composite type, carbon-epoxy based multi-leaf springs are used and the combination of metal and carbon fiber material is used to develop hybrid composite leaf springs. The outputs namely deflection, maximum stress, and fatigue tests are determined using the finite element analysis approach. Besides, the optimal outcomes are set as the target for hybrid deep neural network-rat swarm optimization based prediction. The findings shows that the hybrid composite leaf spring provides better and enhanced results than the composite leaf spring. © 2021 Taylor & Francis Group, LLC.

Mechanics Based Design of Structures and Machines

Investigation and prediction of hybrid composite leaf spring using deep neural network based rat swarm optimization

Water contamination by heavy metal is a great environmental concern. It leads to many health issues ranging from diarrhea, vomiting to life-threatening diseases like cancer, lung/kidney damage. This also affects soil biota/plant growth. Metal-ions have a tendency of bioaccumulation, hence pose a major issue upon entry in the food-cycle. Their removal from water is necessary before use for human/agricultural applications. Different methods reported for metal-ion separation are conventional methods viz. chemical-precipitation, ion-exchange, adsorption, coagulation, flocculation, flotation, electrochemical possess good separation efficiency, but the generation of a secondary pollutant, recovery issues restrict their applicability. Hence, there is a need of reliable techno-economical, environment-friendly, sustainable separation, recovery method. Membrane-based methods viz. reverse-osmosis, nanofiltration, electrodialysis, ultrafiltration has ability to treat water for heavy metal recovery without chemical contamination. Recovered materials can be recycled/utilized further. Among different membrane-based processes, micellar/polymer enhanced ultrafiltration requires chemical addition and affects purity. Electrodialysis, reverse-osmosis, nanofiltration processes require large energy/operational issues. Hence, simple ultrafiltration with membrane modification is preferable as low-energy requirements. This paper discusses details of conventional/advanced methods for heavy metal separation with the fundamental process, parameters, advantages/limitations. © 2021 Mahajan-Tatpate et al.; Licensee Cosmos Scholars Publishing House. This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

School of Polymer Engineering

International Journal of Membrane Science and Technology

Removal of heavy metals from water: Technological advances and today's lookout through membrane applications

Twitter analytics is a classic research area especially with the widespread presence of Big Data in various online media such as—social network sites, online portals for shopping, e-commerce, forums, chats, recommendation systems, and online services. Ascertaining the sentiment behind, the various types of tweets by different persons can provide great insights on various aspects including behavioral patterns. Besides highlighting the newest trends in the field, we retrieved real-time twitter data pertaining to three currently popular hashtags in the Indian context and carried out extensive experimentation analysis about the prevailing sentiment of a strata of population. Inclusion of current challenges, future trends and applications of sentiment analysis from Twitter data makes this novel work very useful for fellow researchers. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Networks and Systems

A Novel Proof of Concept for Twitter Analytics Using Popular Hashtags: Experimentation and Evaluation

This research work discusses the design and simulation of essential blocks of Field Programmable Gate Arrays (FPGA), such as N-channel metal-oxide-semiconductor (NMOS) Pass Transistor, Static Random-Access Memory (SRAM), Input/Output block (IOB), and Slice in LTspice. The blocks are referred from the Spartan-3 FPGA family and are designed in 180 nm technology. The blocks designed here can be configured to the desired functionality by placement and routing of the individual blocks in Verilog to routing (VTR). © 2021 IEEE.

2021 4th International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2021

Design of FPGA Building Blocks Using LTspice®

REVISTA GEINTEC-GESTAO INOVACAO E TECNOLOGIAS

Execution Evaluation of AODV Protocol Using NS2 Simulator for Emergency Automobile

Objective: Quantum algorithms are stronger and more secure than classical computers because they run on faster, harder ones and require fewer steps. With Quantum computers, the attackers have high computing power, and with a quantum, the algorithm can easily break the cryptographic system. Lattice is a regularly spaced grid of points stretching to infinity. Quantum safe security algorithms are resistant to both attacks caused by quantum computers and attacks caused by classical computers. Lattice-based cryptography is the post-quantum cryptographic standards resistant to the attacks from quantum computers, hence having the advantage of strong security and high efficiency. The paper's main objective is to study Lattice, lattice properties, Lattice – based cryptographic algorithm to design new Lattice-based cryptographic algorithms that are quantum resistant in the future. Methods: In this paper, lattice-based cryptography is discussed right from its seminal work to its efficient cryptographic schemes. Paper discusses Lattice, lattice properties, lattice problem, the algorithmic solution to lattice problem, and lattice-based cryptography. Findings: After studying post-quantum cryptographic algorithms using Lattice, lattice-based post-quantum cryptographic algorithms are resistant to quantum computer attacks. Novelty: The paper discusses Lattice, properties of Lattice in a simple way. Widely used cryptographic algorithms like RSA, Diffie-Hellman Key exchange, Elliptic Curve Cryptography are not resistant to quantum computer attacks. Paper discusses the importance of a post-quantum algorithm using Lattice that is resistant to quantum computer attacks. © 2021 Seventh Sense Research Group®.