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 pressing concern that the entire world is striving to combat. Among air pollutants, particulate matter poses a significant threat to human health. The Sustainable Development Goals (SGD3, SGD7 and SGD11) include initiatives to address air pollution. Two innovative methods are proposed in this research to predict the PM2.5 concentration in advance. While multivariate time series prediction models typically employ multiple features as inputs, this research reduces the number of inputs, which makes the proposed combination of approaches simple and effective. The approaches involve the development of two new indexing methods, namely, the Hourly Relative Mean Index and the Hourly Weighted Index. This research offers innovative hybrid deep learning models that incorporate the newly developed indices, Long Short Term Memory (LSTM) models, and robust preprocessing techniques. Multivariate Isolation Forest Relative Index Bidirectional LSTM and Multivariate Isolation Forest Weighted Index LSTM methods are used to forecast PM2.5 concentration for an hourly time frame. Further, Multivariate Isolation Forest Relative Index LSTM and Multivariate Isolation Forest Weighted Index LSTM methods are used to forecast PM2.5 concentration 48 h ahead. The study establishes that the proposed combination of approaches outperform traditional ways to achieve superior performance with reduced complexities requiring fewer inputs for predictions. © 2023 IOP Publishing Ltd.

World University root node

School of Computer Engineering & Technology

Physica Scripta

Deep learning approach to forecast air pollution based on novel hourly index

In this invention a test jig for testing electric bicycle and electric motors used in electric bicycle is developed. The motors used in bicycles can be tested. The performance of the bicycles on road with slope can be tested on the developed jig. In the developed jig performance of the motors also can be tested. There is a facility of loading the motor is provided in this developed jig. Various types of electric motors can be tested on the jig. There is a facility of record speed torque temperature of motor and other parameters of motors. The facility of loading the motor is also provided. The load is applied on the motor in proportion to slope of the motor. Various sensors are fixed in the test jig. Internet of things is used to transfer the data collected. The data is received remotely on the computer. The data collected automatically stored in a computer. The data received can be accessed remotely using internet. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

School of Electrical Engineering

Lecture Notes in Networks and Systems

Electric Sports Bicycle Motor Testing in a Laboratory Jig Using Cloud Computing and Internet of Things

Magnesium alloys are suitable biological material because of its favourable mechanical qualities, high biocompatibility, and biodegradability. However, it has poor corrosion resistance and has rapid dissolution in the corrosive environment which will weakens its mechanical characteristics. The surface characteristics of magnesium alloy must thus be changed using a suitable surface modification technology, such as micro arc oxidation (MAO). It was observed that characteristics of MAO coating can changed by varying electrical parameters like duty cycle, current density, type of power output, frequency, and processing time. It was noticed that when all other factors are held constant, duty cycle, processing time, and frequency primarily effect the coating's porosity, number of cracks and thickness, which in turn influences how well the coating performs. DC, AC, pulsed bipolar, and pulsed unipolar, are the four categories into which the current regimes are classified. It was found that, unipolar current mode MAO coatings found to be rough, highly porous, and vulnerable to microcracks due to stronger spark discharge. MAO coating produced in a bipolar current type of mode have larger pores but are more uniform in thickness and compact. It was noticed that the in-vitro cell assays showed cells L929 on the Ca-P coated Mg alloy to have considerably good adhesion, a high growth rate, and strong proliferation (p 0.05). In other words, the cytocompatibility was greatly enhanced by the Ca-P coating. It was discovered that the Ca-P coated Mg alloy improved cell responsiveness and encouraged early bone formation at the implant/bone interface by both conventional pathological examination and immunohistochemistry investigation. The Ca-P coating was found to be an effective method for raising the surface bioactivity of Mg alloy. It was also observed that the calcium phosphate coating deposited by MAO process improve surface biomineralization which is the main mechanism behind bioactivity. Functional groups that are present on surface engage electrostatically through calcium and phosphate ions from solutions to start the biomineralization process. Calcium phosphates have excellent biocompatibility and are quite comparable to the mineral makeup of bone. The current study aims to investigate the bioactivity of calcium phosphate coatings and the characteristics of magnesium and its alloys. © 2023 Trans Tech Publications Ltd, Switzerland.

School of Mechanical Engineering

Key Engineering Materials

Recent Advances on Biocompatible Coating on Magnesium Alloys by Micro Arc Oxidation Technique

The use of cutting-edge techniques is beneficial for the research and development of biomaterials and the production of new sustainable biomaterials. Eco-friendly biomaterials should be promoted. As prospective substitutes for conventional materials, a variety of biomaterials have been conceived and produced to date and successfully used in various biomedical disciplines. The sustainability component in the additive manufacturing of biomaterials is the main goal of this article. There is discussion of various metallic biomaterials, including titanium, stainless steel, magnesium, cobalt-chromium alloy, zinc, tantalum etc. The effects of several additive manufacturing techniques on sustainability are examined. Also, the properties of additive manufactured biomaterials and sustainability aspect of biomaterials are discussed in detail. By reducing material waste and using time and energy efficiently, additive manufacturing can assist to lower costs and having less harmful effects on the environment. This article discussed sustainability aspects of different additive manufacturing techniques used for manufacturing of biomaterials. © 2023 Chinese Institute of Industrial Engineers.

Journal of Industrial and Production Engineering

Additive manufacturing of metallic biomaterials: sustainability aspect, opportunity, and challenges

Exploring the effective incorporation of natural fibers into polymer composites offers a sustainable approach to finding eco-friendly alternatives that do not harm the environment. Sheep wool–based polymer composites have emerged as a promising and sustainable alternative in the field of materials science. This review comprehensively examines the recent advancements and developments in the utilization of sheep wool as reinforcement in polymer composites. The abundant availability of sheep wool as a natural and renewable resource makes it an attractive option for enhancing the properties of synthetic polymers. The unique structural characteristics of wool fibers, such as their high aspect ratio, surface morphology, and chemical composition, contribute to the improved mechanical, thermal, and flame-retardant properties of the resulting composites. This review explores the various techniques employed for preparing sheep wool fibers, including mechanical treatments, chemical modifications, and functionalization approaches, to optimize their compatibility with polymer matrices. The interfacial interactions between wool fibers and polymer matrices are also discussed, along with the effects of various processing parameters on the overall performance of the composites. The introduction of sheep wool fiber reinforcement results in a significant uptick in tensile strength, showcasing enhancements of up to 25% compared to unmodified polymers. The inherent thermal stability of sheep wool fibers leads to an enhanced thermal resistance, as demonstrated by a 15 °C elevation in the onset degradation temperature. Moreover, sheep wool fiber reinforcement precipitates a remarkable 50% reduction in peak heat release rate, thereby spotlighting augmented flame-retardant attributes. Additionally, the integration of sheep wool fibers yields a notable reduction in water absorption by up to 30%, signifying improved resistance against moisture-related degradation. Moreover, this review highlights the potential applications of sheep wool–based polymer composites in diverse fields, including construction materials, automotive components, textiles, and packaging materials. Furthermore, the environmental benefits of utilizing sheep wool as a renewable resource and its role in waste reduction from the textile industry are emphasized. However, challenges and limitations associated with sheep wool–based polymer composites are addressed, paving the way for future research directions. Overall, this review presents a comprehensive assessment of the current state of knowledge regarding sheep wool–based polymer composites, providing valuable insights for researchers, engineers, and industries interested in sustainable materials development and environmentally friendly technologies. Sheep wool is an exciting biomass which has a potential to create sustainable and innovative materials. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

School of Polymer Engineering

Biomass Conversion and Biorefinery

Review on biomass sheep wool–based polymer composites

Being one of the fast emerging Internet of Things (IoT) technologies, low power wide area networks (LPWANs) offer power-efficient, long range and low bit rate communication for the machine to machine (M2M) and other IoT use cases. Long Range (LoRa), a prominent LPWAN technology, utilizes the unlicensed Industrial Scientific and Medical (ISM) band, which is already getting crowded because of dense deployments of Wireless Local Area Network (WLAN), Low Rate Wireless Personal Area Network (LR-WPAN) and other applications. To avoid channel congestion in LoRa networks, the use of TV white spaces (TVWS) is a promising solution. This paper presents a new path loss model for LoRa based communication using TVWS for outdoor applications. We studied and evaluated energy consumption and uplink delivery rate for a number of end devices, gateways, and coverage at TVWS frequencies. The proposed model reduces path loss and energy consumption at the TVWS frequencies by 4% and 18%, respectively, compared to the existing techniques. The results also show an improvement in uplink delivery rate by 4%, 19% and 25% for different scenarios with varying area radius, number of gateways and end devices, respectively. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

School of Electronics & Communication Engineering

International Journal of Information Technology (Singapore)

Energy efficient LoRa transmission over TV white spaces

Materials Today: Proceedings

Hydrogen fuel cell: Parametric analysis of their stockpiling and different types

School of Civil Engineering

Lecture Notes in Civil Engineering

Structural Audit and Assessment of Application of External Post Tensioning Method on Bridge Girder

Lecture Notes in Electrical Engineering

A Comprehensive Comparison Between Pre-trained and Custom Trained Object Detection Model for Indian Traffic Scenarios

International Journal of Advanced Manufacturing Technology

Lie group dee learning technique to identify the precision errors by map geometry functions in smart manufacturing