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

Metal foam can be used to create a high-surface area to exchange more heat which will reduce size of heat exchange device. It is becoming more popular due to its weight-saving and impact absorbing characteristics as compared to traditional approaches. It can be used in heat exchangers for various applications to improve heat transfer characteristics. Present work is carried out in two parts as analysis of a circular pipe 1.5 m long having ID 40 mm and OD 45 mm with metal foam firstly, and in other part, analysis of double tube heat exchanger with metal foam in annular space is done. The numerical analysis was further extended to 1.5 m long heat exchanger with inner tube of SS (ID 9.5, OD 12.7 mm) and outer tube of GI (ID 28, OD 33.8 mm). Nickel metal foam having 0.9 porosity and pore density 20 PPI was used A geometry with foam was generated in Creo, and then, the simulation was carried out in Ansys fluent flow using the K-omega (2 equation) viscous model which yielded in higher heat transfer coefficients. It has been noticed that the heat transfer coefficient (HTC) was about 1.5 times higher for single circular tube after inserting a metal foam. In double tube heat exchanger, HTC was found to be 2–2.5 times higher for flow through annular space with metal foam which increased overall HTC by approximately two times. Pressure drop is higher when metal foam was inserted in both the cases. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

World University root node

School of Mechanical Engineering

Lecture Notes in Mechanical Engineering

Heat Transfer and Pressure Drop Analysis of Double Tube Heat Exchanger with and Without Metal Foam in Annular Space

Stochastic computing (SC) is an error-tolerant computing technique where computation takes place on randomized statistical bit streams. The main feature is that standard digital logic gates with low power and low area can be used to implement complex arithmetic functions. However, these advantages need to be compared against slow speed and less precision. Also, the area required by stochastic number generators (SNGs) is high as compared with the area required to implement computation circuit. So, if multiple SNGs are used, then the advantage of low area cannot be extracted. So, there is a need to design good quality, reliable and higher throughput SNGs. Out of different approaches that are used to design SNG, use of low discrepancy sequences and randomization functions has better results with respect to throughput and correlation management, respectively, at the cost of area. So, more research using these two approaches can lead to design of efficient SNG. This paper reviews the background, fundamental concepts, basic arithmetic operations using SC, various approaches to design efficient SNG’s by managing correlation in stochastic computing circuits, advantages, and drawbacks followed by conclusion and future challenges. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

School of Electronics & Communication Engineering

Lecture Notes in Electrical Engineering

Survey of Stochastic Number Generators and Optimizing Techniques

COVID-19 has caused physical, emotional, and psychological distress for people. Due to COVID-19 norms, people were restricted to their homes and could not interact with other people, due to which they turned to social media to express their state of mind. In this paper, we implemented a system using TensorFlow, which consists of multilayer perceptron (MLP), convolutional neural networks (CNN), and long short-term memory (LSTM), which works on preprocessing, semantic information on our manually extracted dataset using Twint scraper. The models were used for classifying tweets, based upon whether they indicate depressive behavior or not. We experimented for different optimizer algorithms and their related hyperparameters for all the models. The highest accuracy was achieved by MLP using sentence embeddings, which gave an accuracy of 94% over 50 epochs, closely followed by the other two. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

School of Computer Engineering & Technology

Lecture Notes in Networks and Systems

Detecting Depression in Tweets Using Natural Language Processing and Deep Learning

Materials Today: Proceedings

Investigation for the effect of stiffener on vibration response of engine cover of vehicle

Forward kinematic analysis of 5-DOF LYNX6 robotic arm used in robot-assisted surgery

Modelling and analysis of heavy commercial vehicle suspension system for fatigue life enhancement

Biometrics recognition for individuals has been flourishing over the past few years, with the introduction of these systems in almost every sector of various industries. It makes keeping a track of large numbers of people easier at the administration level, eliminating the requirement of manual checks for every individual. Biometrics traits are individual characteristics like fingerprint, face, voice, etc., on the basis of which individuals are identified. Biometric technology and its use is not only limited to its application as a verification tool but also goes beyond that. Due to its secure, powerful and distinctive capabilities, its applications can also be extended as credentials tools and also digital authentication measures. The growth and pace of development in biometrics technology have been tremendous over the past few years and is considered to grow faster in the coming decades. The framework of the proposed model consists of performing feature-level fusion with the dataset used, and the second half consists of using various deep learning models to classify the labels correctly according to the original dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Face and Fingerprint Fusion Using Deep Learning

Personal health records (PHR) are a new type of health information exchange that allows PHR possessor to share their personal health details with a wide range of people, inclusive of healthcare professionals, close relative and best friends. PHR details are typically externalization and kept in third-party cloud platforms, reducing PHR possessor of the load of managing their PHR details while improving health data accessibility. To ensure the secrecy of personal health records maintained in public clouds, encrypting the health details prior to uploading on the cloud is a typical practice. The secrecy of the information from the cloud is guaranteed since the cloud does not know the keys used to encrypt the information. Elliptic curve cryptography encryption is used to attain secure and systematic way to interact PHRs with re-encryption server. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes on Data Engineering and Communications Technologies

Novel Approach for Improving Security and Confidentiality of PHR in Cloud Using Public Key Encryption

School of Civil Engineering

Lecture Notes in Civil Engineering

An Experimental Study on Flexural Strength of Corroded-Reinforced Concrete Beam with Fly Ash

International Journal of Electrical and Computer Engineering

An efficient stacking based NSGA-II approach for predicting type 2 diabetes