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8th international conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Sareddy, Mohan Reddy Veerandra Kumar, R. Orasys LLC TX United States Saveetha Engineering College Department of Computer Science and Engineering Thandalam Chennai India

ISBN: (纸本)9798331520762

physical education (PE) is changing as a result of the incorporation of cutting-edge technology like LiDAR, virtual reality (VR), and reinforcement learning (RL). The shortcomings of subjective evaluations and environmental restrictions in conventional physical education methods are addressed by these technologies, delivering accurate motion tracking, real-time feedback, and personalised *** a way to improve safety, engagement, and inclusion in physical education, it is necessary to improve motion capture accuracy, optimise abilities using RL, and offer immersive feedback through *** algorithms optimized movement patterns, LiDAR sensors captured 3D motion data, and VR settings provided realistic feedback. With biomechanical analysis to predict the likelihood of injuries and Kalman filtering for data smoothing, the necessary accurate real-time feedback on corrections was generated. This solution increased engagement by 25.8%, injury detection by 34.9%, feedback efficiency by 31.2%, and tracking accuracy by 27.2%. The technique emerged as a good option in motion analysis and augmentation for learning purposes, compared with conventional techniques and other highly advanced technologies. This LiDAR, RL, and VR integration redefine PE in such a way that promises real motion tracking, adaptive feedback and safety. It has got enormous potential for upgrading physical education methods with encouragement for variety and participation. © 2025 IEEE.

关键词： Reinforcement learning

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Design Process and Development of Automation for Smart Buildings 1

Design Process and Development of Automation for Smart Build...

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1st international conference on Advances in computer Science, Electrical, Electronics, and Communication technologies, CE2CT 2025

作者： Sethi, Gunjan Khurana, Deepika Verma, Monika Pant, Surmadhur Chauhan, Priyanka Bhatt, Bhaskar Department of Computer Science and Engineering Delhi Technical Campus Uttar Pradesh Greater Noida India IIMT College of Engineering Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Shivalik College of Engineering Department of ECE Dehradun India Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India Bipin Tripathi Kumaon Institute of Technology Department of Mechanical Engineering Dwarahat Almora India

ISBN: (纸本)9798331518578

In order to create spaces that are secure, cozy, energy-efficient, and visually beautiful, smart buildings are becoming more and more sophisticated cyber-physical systems. However, as functional complexity, financial concerns, and market demands increase, traditional design methodologies are becoming less effective. Current framework's plan and activity have been totally changed by the presentation of automated smart building, which ensures expanded security, better inhabitant solace, and energy effectiveness. With an emphasis on MATLAB-based reproductions, this study offers a careful assessment of the plan interaction and improvement procedures for computerizing savvy structures. The study delineates how MATLAB makes it simpler to depict, reproduce, and investigate savvy building frameworks with certainty. Through the mix of numerous advancements, like sensors, regulators, and correspondence conventions, the research shows the turn of events and check of a mechanized smart building framework. The intelligent building's building automation system prioritizes a humanized interface and uses a combination of mechanical, electrical, and fire control systems, access control systems, and parking management systems to give building occupants a convenient and comfortable place to live and work. The discoveries show prominent additions in functional viability, natural adaptability, and energy utilization. The conventional heuristic and ad hoc design paradigms are becoming ineffective and inadequate for the future due to cost, the requirement to handle growing functional complexity, adaptability, supply chain fragmentation, and time-to-market pressure. © 2025 IEEE.

关键词： Smart homes

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MRAM-Based physical Unclonable Function that is Resilient to Deep Learning Attacks 1

MRAM-Based Physical Unclonable Function that is Resilient to...

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1st international conference on Advances in computer Science, Electrical, Electronics, and Communication technologies, CE2CT 2025

作者： Venkadeshwaran, Kuthalingam Alam, Intekhab Faculty of Engineering and Technology Department of Mechanical Engineering Ramnagar District Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

Electronic devices are everywhere, so strong hardware security is needed to keep private data safe from dangers. A physical Unclonable Function (PUF) device constructed using magneto-resistive random-access memory (MRAM) is shown in this study. The circuit generates appropriate outputs for problem-solving by using built-in properties derived from various manufacturing processes, such as the resistance of the magnetic tunnel junction (MTJ) cell. This proposal differs from Arbiter PUF in that it satisfies the rigorous avalanche criteria (SAC). Additionally, the proposed circuit is impervious to machine learning-based modelling assaults due to its grid-like architecture. Various ML approaches are evaluated for two- and four-array designs, including systems such as support vector machine (SVM), linear regression (LR), and multilayer perceptron (MLP). Accuracy of MLP-attack forecasts remained 53.62% for two array circuit & 49.88% for four array circuit. This demonstrates that the system continues to function well despite substantial process modifications. A convolutional neural network (CNN), a recurrent neural network (RNN), a multi-layer perceptron (MLP), and a Larq are all used in high-dimensional models that are based on deep learning. These nets have an accuracy rating of 50.32%, 50.26%, and 50.32%, along with 50.32%, correspondingly. For a simpler two-array design, the suggested circuit's efficiency at the layout stage is also looked into. Based on the simulations, the suggested circuit has an average intra-hamming distance (HD) of 0.99% and an average inter-hamming distance (HD) of 49.97%. It also has an average diffuseness of 49.08. © 2025 IEEE.

关键词： Hamming distance

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Application of generative AI technologies to engineering design 1

Application of generative AI technologies to engineering des...

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1st international conference on Digital Sovereignty, ICDS 2024

作者： Byrne, Daniel Hargaden, Vincent Papakostas, Nikolaos Laboratory for Advanced Manufacturing Simulation and Robotics School of Mechanical and Materials Engineering University College Dublin Dublin Ireland I-Form Advanced Manufacturing Research Centre Ireland

This paper explores the application of artificial intelligence (AI) technologies in the engineering design domain. Two experiments were designed for examining the abilities of diverse generative AI platforms in engineering design applications. The first experiment tested the AI models' abilities to interpret design briefs, perform arithmetic calculations, and finally to provide instructions to design a part in two separate computer-aided design (CAD) platforms, thus gaining an insight into their perception of the functionality of the CAD platforms. The second experiment required the AI tools to design a headphone holder stand from scratch, further a be bing their capabilities in CAD, but also their abilities in product design. The experiments found that these technologies show great potential in the area of engineering design. While they are not yet near the level of a human engineer, they currently exhibit capabilities that may be useful in product concept generation and design proce bes. © 2025 The Author(s).

关键词： Product design

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Deep Learning Utility for Gas/Odor Sensor Signature Analysis 2

Deep Learning Utility for Gas/Odor Sensor Signature Analysis

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2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Raut, Yashasvi Chaudhri, Shiv Nath Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra India

ISBN: (纸本)9798331505745

Gas/odor sensors are integral components of sensor systems used in diverse applications such as food quality control, environmental monitoring, medical diagnostics, odor profiling, industrial safety, agriculture, explosives detection, wine tasting, pharmaceutical quality control, and toxic gas detection. Traditional approaches in this domain of gas/odor sensing technologies face challenges related to accuracy, cross-sensitivity, and drifted real-time performance. The integration of deep learning techniques with gas sensors has shown promise in overcoming these limitations. Moreover, this amalgamation of gas sensing and deep learning strategies enables accurate identification of gases/odors, handling complex patterns, and leading optimal consumption of resources. In this paper, an overview of advancements in deep learning-enabled gas sensing has been presented that focused on methodologies, sensor types, and applications. This review also highlights the state-of-the-art techniques and identifies gaps for future directions for research. © 2025 IEEE.

关键词： Damage detection

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A Machine Learning Framework for Skin Cancer Detection using Transfer Learning 6

A Machine Learning Framework for Skin Cancer Detection using...

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6th IEEE international conference on Image Processing, applications and Systems, IPAS 2025

作者： Augustine, Mary Linda Panakal Spanogianopoulos, Sotirios Sharif, Mhd Saeed University of East London School of Architecture Computing and Engineering Department of Computer Science and Digital Technologies London United Kingdom University of Portsmouth School of Electrical and Mechanical Engineering Portsmouth United Kingdom

ISBN: (纸本)9798331506520

This paper uses deep learning algorithms including InceptionV2, InceptionV3, DenseNet, MobileNet, and VGG19 to improve skin cancer detection. This research aims to improve skin cancer diagnosis. This work aims to determine the most effective evolutionary metrics-based technique to recognizing skin cancer, which is comparable to other diseases. Ultimately, our paper aims to create a realistic skin cancer detection system that uses the best deep learning algorithm. This discovery might improve medical diagnostics, leading to earlier diagnosis and improved healthcare outcomes. © 2025 IEEE.

关键词： Adversarial machine learning

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An Algorithmic Approach to (2,2)-Isogenies in the Theta Model and applications to Isogeny-Based Cryptography 30th

An Algorithmic Approach to (2,2)-Isogenies in the Theta Mode...

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30th international conference on the Theory and Application of Cryptology and Information Security

作者： Dartois, Pierrick Maino, Luciano Pope, Giacomo Robert, Damien Univ Bordeaux CNRS UMR 5251 IMBBordeaux INP Bordeaux France INRIA IMB UMR 5251 F-33400 Talence France Univ Bristol Bristol Avon England NCC Grp Cheltenham Glos England

ISBN: (纸本)9789819608904;9789819608911

In this paper, we describe an algorithm to compute chains of (2, 2)-isogenies between products of elliptic curves in the theta model. The description of the algorithm is split into various subroutines to allow for a precise field operation count. We present a constant time implementation of our algorithm in Rust and an alternative implementation in SageMath. Our work in SageMath runs ten times faster than a comparable implementation of an isogeny chain using the Richelot correspondence. The Rust implementation runs up to forty times faster than the equivalent isogeny in SageMath and has been designed to be portable for future research in higher-dimensional isogeny-based cryptography.

关键词： Encryption algorithms

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DFT analysis of the physical properties of direct band gap semiconducting double perovskites A2BIrCl6 (A = Cs, Rb;B = Na, K) for solar cells and optoelectronic applications

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RSC Advances 2025年第17期15卷 13643-13661页

作者： Tarekuzzaman, Md. Shahadath, Nazmul Montasir, Mufrat Alsalmi, O. Mia, M.H. Al-Dmour, Hmoud Rasheduzzaman, Md. Hasan, Md. Zahid Materials Research and Simulation Lab Department of Electrical and Electronic Engineering International Islamic University Chittagong Kumira Chittagong4318 Bangladesh Department of Physics College of Science Umm Al-Qura University Makkah21955 Saudi Arabia Department of Textile Engineering Northern University Bangladesh Uttara Dhaka Bangladesh Department of Computer and Communication Engineering International Islamic University Chittagong Kumira Chattogram4318 Bangladesh Department of Physics Faculty of Science Mutah University karak61710 Jordan

Double perovskite-based optoelectronic devices are gaining attention due to their unique characteristics, including a simple and stable crystal structure. This study employs density functional theory (DFT) with the full-potential linearized augmented plane-wave (FP-LAPW) method to investigate the structural, electronic, optical, mechanical, and thermodynamic properties of A2BIrCl6 (A = Cs, Rb;B = Na, K) double perovskite halides. The primary aim is to assess their potential applicability in optoelectronic devices and renewable energy technologies. The cubic stability of the predicted compounds was confirmed through the Goldsmith tolerance factor, octahedral factor, and a new tolerance factor. Additionally, to confirm their thermodynamic stability, we assessed the formation energy, binding energy, and phonon dispersion curves. We used the TB-mBJ potential to accurately predict the optoelectronic properties. The calculations of the electronic band structure indicated that the examined double perovskites exhibit a direct band gap semiconducting nature, with the following band gap values: 1.927 eV for Cs2NaIrCl6 1.991 eV for Cs2KIrCl6, 2.025 eV for Rb2NaIrCl6, and 2.102 eV for Rb2KIrCl6. The A2BIrCl6 (A = Cs, Rb;B = Na, K) compounds demonstrate impressive optical properties, including low reflectivity and high light absorption coefficients (104 cm−1) in the visible spectrum. Their spectral response extends from the visible to the UV range, making them ideal candidates for applications in solar cells and optoelectronic devices. The mechanical stability of the titled compounds was confirmed through the Born-Huang stability conditions based on their stiffness constants. The brittle nature of all the examined perovskites is confirmed by Pugh's ratio, Cauchy pressure, and Poisson's ratio. Finally, the Helmholtz free energy (F), internal energy (E), entropy (S), and specific heat capacity (Cv) are calculated based on the phonon density of states. © 2025 The Royal Society of C

关键词： Opacity

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Advanced Photonic Crystal Fiber Sensor Design For Efficient Air Pollution Detection

Advanced Photonic Crystal Fiber Sensor Design For Efficient ...

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2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Barath Kumar, B. Hanush, B. Anbazhagan, Lavanya Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Electronics and Communication Engineering 603203 India

ISBN: (纸本)9798331529833

This paper presents a novel approach for air pollution monitoring using Photonic Crystal Fiber (PCF) with unique optical properties. Through Finite Element Method (FEM) simulations in COMSOL, the study explores how the PCF's guiding characteristics are influenced by its geometric parameters at different wavelengths. The sensor, designed for enhanced sensitivity, selectivity, and fast response, focuses on detecting air pollutants. A microstructured core in the PCF enhances light-matter interaction, improving sensor performance. The optimized PCF structure ensures effective light confinement, enabling precise detection of environmental changes like temperature and refractive index variations. The results have significant potential for telecommunications, biomedicine, and environmental monitoring applications, contributing to advanced air pollution control technologies. © 2025 IEEE.

关键词： Environmental monitoring

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Concurrent and Learned Data Structures 25

Concurrent and Learned Data Structures

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26th international conference on Distributed Computing and Networking, ICDCN 2025

作者： Chatterjee, Bapi Peri, Sathya Department of Computer Science and Engineering IIIT Delhi Delhi India Department of Computer Science and Engineering Indian Institute of Technology Hyderabad Hyderabad India

ISBN: (纸本)9798400710629

We explore the landscape of modern data structures that employ two powerful scaling mechanisms simultaneously: (a) concurrency to harness the power of today's multicore processors, and (b) learned queries - the operations employing machine learning inference by models trained on the underlying data. We focus on advancements, challenges, and potential future directions in this field. We delve into the motivation for incorporating learned queries in concurrent data structures. We discuss the key techniques, applications, and open research questions. On the theoretical side, we discuss the mathematical foundations for building the learned data structures in addition to the correctness of queries in a concurrent setting. On the practical side, we present an overview of techniques used for managing concurrency with learned queries that need training the models with concurrent real-time updates. © 2025 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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