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

The Single Point Incremental Forming (SPIF) is considered as a rapid sheet forming method due to promising future in prototyping as well as in batch manufacturing. The SPIF process was mainly focused on metallic materials over the past decades. In the first decade of the 20th century different non-metallic materials were taken into consideration for performing SPIF. Polymer composites showed promising results in terms of formability and mechanical properties. The present study reviews the studies performed on non-metallic materials over the past decade. Polymers such as PVC, PET, PC, HDPE, PLA, etc. were tested by researchers while performing SPIF. This study reviews the research done on incremental forming of such materials. The forming abilities, geometric accuracy as well as the surface roughness are dependent on the different process parameters having their own effects such as depth of step, angle of forming and process temperature. In this study as investigation over a composite material specifically polyamide-6 (PA-6) sheet was performed. The study includes the influence of various forming process parameters on the forming abilities of the components made of PA-6. The simulation was performed in ABAQUS on a polyamide-6 sheet. The deformation of polyamide-6 sheet is examined using simulation software. The incremental forming process is a promising process to define the forming abilities of different materials. © 2022

World University root node

School of Mechanical Engineering

Materials Today: Proceedings

Incremental sheet forming of composite material

Aluminum oxide (Al2O3) nanoparticles are capable of improving the material characteristics if reinforced to soft and low strength material. The major limitation in the utilization of Al alloy 6061 in medium to heavy stress applications such as automobile, defense, transportations, and aerospace is low hardness and strength. In order to overcome the deficiency of Al6061, nano-Al2O3 reinforced Al6061 matrix nanocomposite (AMNC) was successfully fabricated on machinated aluminum stir casting furnace. Al2O3 nanoparticles in 2,4,6 and 8 wt.% were reinforced in the Al6061 matrix and the effect on mechanical and microstructure behavior was investigated by field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), hardness, and tensile testing methods. Higher magnification FESEM micrographs revealed that reinforcement of nano-Al2O3 leads to considerable grain refinement and uniform distribution with less porosity. The mechanical properties results showed enhancement in tensile strength (by 130%), hardness (by 156%), yield stress (by 360%) with reinforcement of nano-Al2O3 over the base alloy Al6061. It was observed that the nano size of Al2O3 particles, the quantity of reinforcement, and the stir casting process were effective factors on the microstructure and mechanical properties enhancement. © 2022 IOP Publishing Ltd.

Engineering Research Express

Microstructural observation and mechanical properties behavior of Al2O3/Al6061 nanocomposite fabricated by stir casting process

The techniques for making orthopaedic implants and devices have advanced significantly in recent years. The use of additive manufacturing technology enables the creation of intricate structures with biomimetic characteristics. Three-dimensional (3D) printed titanium orthopaedic implants were already used to repair severe pelvic bone abnormalities, and the production of thousands of non-individualized implants. The various adjustable variables in the 3D printing process and how they could interact with the potential variety of designs that might be produced must be understood in order to predict the efficacy and safety of AM made implants. A reasonably well-known technology known as powder bed 3D printing has revolutionised the process of creating personalised, multipurpose metallic implants for each patient's unique demands. Precise mechanical characteristics with porous implants, good pore topologies, and patient-oriented design functionalities can be created via AM. Although 3D printed Ti and its alloy Ti-6Al-4V have been studied and used in clinical applications from several years, further study is still needed to build porous AM titanium implants that would operate superbly over the long term. Although early clinical outcomes for 3D printed cups have been promising, additional extensive study is still needed, because regulatory approval systems have not fully kept up with technological innovation. For various applications, a variety of 3D printing methods, including selective laser melting, selective laser sintering, and electron beam melting, are discussed in this paper. The production of excellent porous metal implants has a lot of potential for additive manufacturing using powder bed fusion. © 2023 Elsevier Ltd. All rights reserved.

Additive manufacturing of metallic biomaterials and its biocompatibility

Human behavior is very complex and cannot be explained using traditional mathematical models. Intermediate forms, such as those obtained from personality data, can be used to predict behavioral aspects of a person, creating the hypothesis that arbitrating psychological models can be drawn directly from recordings of behavior. In recent years, smartphone addiction has increased to a great extent. Since the excessive use of smartphones has negatively affected our daily life, many applications to reduce dependence on smartphones have been developed around the world. Personal attributes or personality types can be extracted from data obtained directly from smart phones without the interaction of participants who may have social or health interventions. Many people who excessively use their smartphones have an uncontrollable urge to use the Internet. Internet addiction refers to uncontrolled use of the Internet which causes hindrance in our daily life. Due to its negative impact on the education and lives of people, it is necessary to detect tendencies of people toward addictive behavior and provide them with preventative support and treatment. Similarly, the development of social media has seen rapid growth in its usage. People often find themselves overusing utilities such as virtual communication, texting, and sharing information which have also caused various behavioral problems. This study provides a summary of the various methods and studies done on these behavioral problems and to analyze different techniques, and machine learning models are used to predict addictive personality types. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

School of Computer Engineering & Technology

Lecture Notes in Electrical Engineering

Psychoinformatics: The Behavioral Analytics

In the domain of image captioning, many pre-trained datasets are available. Using these datasets, models can be trained to automatically generate image descriptions regarding the contents of an image. Researchers usually do not spend much time in creating and training the new dataset before using it for a specific application, instead, they simply use existing pre-trained datasets. MS COCO, ImageNet, Flicker, and Pascal VOC, are well-known datasets that are widely used in the task of generating image captions. In most available image captioning datasets, image textual information, which can play a vital role in generating more precise image descriptions, is missing. This paper presents the process of creating a new dataset that consists of images along with text and captions. Images of the nearby vicinity of the campus of MIT World Peace University-MITWPU, India, were taken for the new dataset named MITWPU-1K. This dataset can be used in object detection and caption generation of images. The objective of this paper is to highlight the steps required for creating a new dataset. This necessitated a review of the existing dataset models prior to creating the new dataset. A sequential convolutional model for detecting objects on a new dataset is also presented. The process of creating a new image captioning dataset and the gained insights are described.

Fulltext

Engineering, Technology and Applied Science Research (ETASR)

The New Dataset MITWPU-1K for Object Recognition and Image Captioning Tasks

The globe's population is increasing day by day, which causes the severe problem of organic food for everyone. Farmers are becoming progressively conscious of the need to control numerous essential factors such as crop health, water or fertilizer use, and harmful diseases in the field. However, it is challenging to monitor agricultural activities. Therefore, precision agriculture is an important decision support system for food production and decision-making. Several methods and approaches have been used to support precision agricultural practices. The present study performs a systematic literature review on hyperspectral imaging technology and the most advanced deep learning and machine learning algorithm used in agriculture applications to extract and synthesize the significant datasets and algorithms. We reviewed legal studies carefully, highlighted hyperspectral datasets, focused on the most methods used for hyperspectral applications in agricultural sectors, and gained insight into the critical problems and challenges in the hyperspectral data processing. According to our study, it has been found that the Hyperion hyperspectral, Landsat-8, and Sentinel 2 multispectral datasets were mainly used for agricultural applications. The most applied machine learning method was support vector machine and random forest. In addition, the deep learning-based Convolutional Neural Networks (CNN) model is mainly used for crop classification due to its high performance with hyperspectral datasets. The present review will be helpful to the new researchers working in the field of hyperspectral remote sensing for agricultural applications with a machine and deep learning methods. © 2022 Elsevier B.V.

Ecological Informatics

A systematic review on hyperspectral imaging technology with a machine and deep learning methodology for agricultural applications

Tehni{\v{c}}ki glasnik

Salient Features Selection Techniques for Instruction Detection in Mobile Ad Hoc Networks

One of the most important problems that the world is currently facing in terms of its impact on the environment is figuring out how to properly manage textile effluents. Photocatalysis has been shown to be successful in the removal of intractable chemicals and is regarded as a viable wastewater treatment technology. This work focused on the photocatalytic degradation of rhodamine-B (RB) in an aqueous solution, as well as the photocatalytic behavior of niobium pentaoxide (Nb2O5) as a photocatalyst was tested. It is important to note that good photocatalytic efficiency is highly dependent on the operating conditions. There are several process parameters that influence RB photocatalytic degradation, including the amount of photocatalyst (Nb2O5) used, the concentration of RB at the start of the reaction, and the pH of the solution optimized under visible-light irradiation. According to the findings, the conditions in which the greatest amount of RB was degraded were those in which the concentration of the catalyst was 10 mg/l, the dosage of the catalyst was 1 mg/l, and the pH was 11. The results also revealed that after utilizing the catalyst three times in a row, catalyst efficiency was maintained, and the degradation rate was maintained at a greater level. © 2022 The Authors.

School of Chemical Engineering

School of Civil Engineering

Aqua Water Infrastructure, Ecosystems and Society

Niobium pentaoxide (Nb2O5) as an efficient photocatalyst for photocatalytic degradation of rhodamine-B

Human affect is an important consideration in several cognitive and AI-driven applications. Efficient and timely determination of affect is crucial in detecting various physiological and psychological illnesses affecting humans globally. Cognitive science advocates the use of different modalities such as voice, text, images, and gestures in initiating/promoting human cognition. Thus, multimodality is an inherent nature of cognition. In this work, we have performed experimentation on real-time voice samples collected from four participants and attempted to determine patterns of affect. With suitable use of spectrogram, chroma features, beats, etc., we present various visualizations that depict the inter-individual acoustic differences. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Use of Speech Analysis in Determining Human Affect: A Proof of Concept

Industrial Flyash (IFA) is a fine powder made from non-combustible materials and a residue of carbon from incomplete combustion. Phosphogypsum (PG) is also a solid by product of phosphoric acid processing, which is employed in a variety of fertilisers and chemicals. Traditional construction material manufacturing processes destroy the earth's vital natural resources. Furthermore, IFA and PG is a solid waste, which is frequently dumped in open spaces. IFA and PG contains natural mineral which can be used as admixture in concrete. It can be used as partial replacement to the cement in the concrete up to certain limit. The experimental findings include compressive strength (CS), flexural strength (FS) and split tensile strength (STS) by partially cement replacement with Industrial IFA and PG employing 0 %, 5 %, 7.5 %, 10 %, 12.5 %, 15 %, and 20 % on M40 grade concrete and water-binder ratios of 0.45. The CS is determined by testing cube specimens for 7 and 28 days, as well as FS and STS is found by testing the beams and cylinders specimens for 7 and 28 days respectively. The optimal proportion shows maximum strength at 15 % IFA and 7.5 % PG respectively. Further increase in percentage, strength of concrete decline marginally. 10 % substitution of cement with IFA + PG (combined 50 % each) used shows the optimal proportion to achieve maximum strength, and further increase in IFA and PG causes a decrease in strength. The addition of IFA and PG increases the amount of water required due to increase in fine particles or a bigger surface area. When compared to the control mix, the workability of concrete with IFA and PG reduces slump value by up to 15 %.4 © 2022