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14th IEEE Integrated STEM Education Conference, ISEC 2024

作者： Monagle, Daniel Ponce, Eric A. Leeb, Steven B. Saathoff, Erik K. Brooks, Dylan E. Krause, Thomas C. Green, Daisy H. Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science United States University of Hawai'i Department of Electrical and Computer Engineering Manoa United States

ISBN: (纸本)9798350352801

engineering outreach and introductory courses are essential for motivating and training the next generation of capable engineers. Accessibility and portability of the infrastructure for a STEM course is critical for spreading STEM education and motivation efforts. The ubiquity of student personal computers and laptops provides a convenient platform for introducing computer programming, but the relatively cumbersome equipment deemed necessary for a hands-on electronics learning environment contributes to the lack of electronic circuit hardware exposure for many K-12 students and university undergraduates. This paper presents the relatively low-cost, versatile, electronics platform we have developed at MIT upon which our new, hands-on introductory STEM electrical engineering course has been built and taught in recent years. This paper focuses its discussion on the power supply and measurement systems we have produced that allow students and instructors to engage in hands-on electric circuit exercises and projects without the requirement for expensive laboratory infrastructure. Example demonstrations of introductory laboratory exercises using our platform are shown. © 2024 IEEE.

关键词： Students

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A novel IoT-based arrhythmia detection system with ECG signals using a hybrid convolutional neural network and neural architecture search network

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International Journal of Applied Decision Sciences 2024年第5期17卷 636-656页

作者： Şentürk, Ümit Gülen, Ceren Polat, Kemal Department of Computer Engineering Faculty of Engineering Abant Izzet Baysal University Bolu Turkey Department of Computer Engineering Education of Graduate Institute Abant Izzet Baysal University Bolu Turkey Department of Electrical and Electronics Engineering Bolu Abant Izzet Baysal University Bolu Turkey

Electrocardiogram (ECG) signals are the most common tool to evaluate the heart’s function in cardiovascular diagnosis. Irregular heartbeats (arrhythmia) found in the ECG play an essential role in diagnosing cardiovascular diseases (CVD). In this paper, we proposed an arrhythmia classification method with the neural architecture search network (NASNet) model, an optimised version of the convolutional neural networks (2D-CNN) model, which performs very well in visual information analysis classification. We aimed to use the arrhythmia classification problem in IoT and mobile devices with the NASNet model with low parameter numbers and processing capacity without performance loss. 2D input data have been obtained by converting the classified heart rate signals in the datasets into image files. The 2D data obtained have been classified by machine learning, CNN, and NASNet models. As a result of classification, 2D CNN accuracy was 97.51%, and the NASNet model was 96.89% accuracy. As a result of arrhythmia classification, the accuracy rates of the NASNet and the 2D CNN models were close. In conclusion, the proposed IoT-based arrhythmia detection system with ECG signals using a hybrid CNN and NASNet is a promising tool for the early detection of arrhythmias. Furthermore, it could help to reduce the mortality associated with these potentially fatal conditions. © 2024 Inderscience Enterprises Ltd.

关键词： Convolutional neural networks

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Optimizing Cloud Computing Task Schedules Through Advanced Intelligent Optimization Methods

Optimizing Cloud Computing Task Schedules Through Advanced I...

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International IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024

作者： Ammari, Ahmed Chiheb Al Hmouz, Rami Khriji, Lazhar Zhou, MengChu Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9789819747832

The number of Distributed Green Cloud Datacenters (DGCDs) is globally increasing. Such DGCDs deploy different types of renewable sources to generate clean energy and save money. They are located in different regions depending on the availability of renewable energy sources, costs of bandwidth and grid electricity prices. This paper focuses on applications within them, which are sensitive to delay and looks into a way to schedule different applications with respect to time constraint. The paper uses the Firefly algorithm, bat algorithm and simulated annealing-bat algorithms as optimization techniques to minimize total operational cost of such DGCDs. These algorithms have been compared through data-driven experiments carried out in this study. Of particular note is the Firefly algorithm's superior performance when compared with others. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Simulated annealing

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End-To-End Encryption Enabled Lightweight Mutual Authentication Scheme for Resource Constrained IoT Network

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computers, Materials & Continua 2025年第2期82卷 3223-3249页

作者： Shafi Ullah Haidawati Muhammad Nasir Kushsairy Kadir Akbar Khan Ahsanullah Memon Shanila Azhar Ilyas Khan Muhammad Ashraf Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Computer Engineering Section Malaysian Institute of Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Electrical Engineering Section Universiti Kuala LumpurBritish Malaysian InstituteSalengor53100Malaysia Electrical Engineering Department Mehran UniversityKhairpur-Mirs76062Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.

关键词： Mutual authentication lightweight end-to-end encryption elliptic curve cryptography industrial internet of things curve25519 machine-to-machine communication

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Scalable Modular Battery Management System Using Model-Based Approach for EV Applications 2

Scalable Modular Battery Management System Using Model-Based...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Kumar, Srinath Jawaharram, Vishnu Ram Balashivakumaran, R. Chandrakala, K.R.M. Vijaya Kumar, S. Sampath Nadar, Kannan Paulish Amrita School of Engineering Department of Electrical and Electronics Engineering Coimbatore India Institute of Technology Jijiga University Department of Electrical and Computer Engineering Ethiopia

ISBN: (纸本)9798350328202

The global automotive industry is in the phase where Internal Combustion vehicles are in decline and witnessing a shift towards sustainable development. The major parameter of a successful EV is an efficient battery pack and the protection for it which is the Battery management system (BMS). In this work model-based approach in the design of a Modular Battery Management System (BMS) takes into account various protection schemes such as over and under-voltage scenarios adopted in Li-ion batteries and monitoring the State of Charge (SoC) using the Coulomb Counting technique. The design and the simulation-based approach are adopted to study the behaviour of Li-ion Battery and BMS in a wide operational condition where the testing is difficult using MATLAB/Simulink. The proposed technique is a Modular Battery Management System that works on the Master-Slave Architecture. © 2024 IEEE.

关键词： Battery management systems

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Secured IIoT against trust deficit - A flexi cryptic approach

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Multimedia Tools and Applications 2025年第9期84卷 5625-5652页

作者： Padmapriya, V.M. Thenmozhi, K. Hemalatha, M. Thanikaiselvan, V. Lakshmi, C. Chidambaram, Nithya Rengarajan, Amirtharajan Department of Computer Sciences Marquette University MilwaukeeWI53233 United States School of Electrical & Electronics Engineering SASTRA Deemed University Thanjavur613401 India Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah22254 Saudi Arabia School of Electronics Engineering Vellore Institute of Technology Vellore632014 India

This research allows the secure surveillance approach for the Internet of Things (IoT) methodology to be developed by integrating wireless signalling and image encryption strategy. Since the Cloud Service Telco (CST) is a semi-trusted body in cloud services, user data is encrypted before uploading to a cloud server for data protection from disclosure. The flexibility of encrypted data sharing is essential for cloud storage users. This study investigates the Discrete Wavelet Transform (DWT) technique with modified Huffman compression and Elliptic Curve Cryptography (ECC). It encrypts and decrypts the data and enhances industrial security surveillance in transmission. It uses the wireless network’s next generation (5G or 6G) as uplink Single Carrier Frequency Division Multiple Access (SC-FDMA) strategies via the IoT. This study presented a novel approach to proposing hardware architecture for a secure web camera integrated with the Atmel in the mega AVR family (ATMEGA) microcontroller, suitable for IoT applications. The experimental results confirm the proposed model’s efficacy compared with existing robustness and security analysis algorithms. These systems are also used by implementing industry-standard protocols using IoTs to monitor industrial applications. The proposed framework can also minimise bandwidth, transmission cost, storage space, tracking data, and decisions about abnormal events such as potential fraud and extinguisher detection in surveilling applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： 5G mobile communication systems

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Performances comparison of Reluctance Machines Energized Bipolar and Unipolar Sinusoidal Current

Performances comparison of Reluctance Machines Energized Bip...

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2024 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2024

作者： Uemoto, Satoshi Aiso, Kohei Shibaura Institute Of Technology Electrical Engineering And Computer Science Tokyo Japan Shibaura Institute Of Technology Department Of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798331529277

In this paper, SRM, DC-VRM, and VRM with same pole-slot combinations of 8 poles/12 slots and 10 poles/12 slots are designed, the mechanism of generating torque in the energization by the sinusoidal current with and without DC offset is analyzed by Finite Element Analysis (FEA). Through these analyses, the structure that satisfies high torque and the excitation methods suitable for each speed range in reluctance motors with applying sinusoidal current will be clarified. © 2024 IEEE.

关键词： Reluctance motors

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High Efficient Delta-Sigma Modulator Utilizing Multi-Stage Noise Shaping Structure

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Journal of Lightwave Technology 2024年第8期42卷 2693-2701页

作者： Jian, Yin-He Wei, Tzu-Chieh Chow, Chi-Wai National Yang Ming Chiao Tung University Department of Photonics Graduate Institute of Electro-Optical Engineering College of Electrical and Computer Engineering Hsinchu30010 Taiwan

Recently, several Delta-Sigma modulators (DSMs) with ultra-high quadrature-amplitude-modulation (QAM) order larger than one million, e.g., 1048576 and 4194304 QAM are reported. As different DSM works were implemented with different oversampling rates (OSRs), and pursuing a higher DSM QAM order seems to deviate from its original idea to achieve high spectral efficiency. Up to the authors' knowledges, there is still no comprehensive comparison of the intrinsic efficiencies of different DSM works. In this work, we first summarize the recent DSM works and compare their efficiencies. We also propose and demonstrate a 1-bit DSM and a 2-bit multi-stage noise shaping (MASH) DSM for the baseband-over-fiber system. The modified 1-bit DSM can achieve record efficiencies of 0.589 and 0.665 under the hard-decision (HD) and the 25% soft-decision (SD) forward error correction (FEC) requirements, respectively. The 2-bit MASH DSM can also achieve record efficiencies of 1.025 (HD) and 1.150 (SD) respectively. © 1983-2012 IEEE.

关键词： Low pass filters

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An Initial Solution Based Selective Harmonic Elimination Method for Multilevel Inverter

CPSS Transactions on Power Electronics and Applications

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CPSS Transactions on Power Electronics and Applications 2024年第1期9卷 63-78页

作者： Kala, Peeyush Sharma, Abhinav Jately, Vibhu Joshi, Jyoti Yang, Yongheng Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Ghaziabad201204 India Department of Electrical and Electronics Engineering Dehradun248007 India Dehradun248007 India Graphic Era Hill University Department of Computer Science and Engineering Dehradun248002 India College of Electrical Engineering Zhejiang University Hangzhou310027 China

This article presents an initial solution based selective harmonic elimination (SHE) method for multilevel inverter (MLI) that aims to solve SHE problem with high accuracy while significantly reducing the number of iterations. Initial SHE solution is defined as a set of initial switching angles that has less accuracy as compared to the final SHE solution. To find initial SHE solution, tunicate swarm algorithm (TSA), grey wolf optimization (GWO) and whale optimization (WO) are used to solve five-dimensional SHE problem. A comparative analysis demonstrates that TSA achieved the desired initial SHE solution within lesser iterations as compared to GWO and WO for a wide range of modulation indices. The initial switching angles found using TSA are further optimized using Newton-Raphson (NR) method being the proposed TSANR method, which exploits the SHE search space with quadratic rate of convergence to find final SHE solution. The proposed TSANR method significantly minimizes the computational time and further improves the accuracy of the SHE solution as compared to the state-of-the-art SHE methods. Detailed simulations, experimental and harmonic analysis under dynamic change in modulation index are presented to show the efficacy of the proposed SHE method in terms of control over fundamental and detrimental harmonics. © 2017 CPSS.

关键词： Harmonic analysis

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Automatic emotion recognition using deep neural network

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Multimedia Tools and Applications 2025年 1-30页

作者： Sujatha, R. Chatterjee, Jyotir Moy Pathy, Baibhav Hu, Yu-Chen School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of CSE Graphic Era University Dehradun India School of Electrical Engineering Vellore Institute of Technology Vellore India Department of Computer Science Tunghai University Taichung City Taiwan

Emotions are a vital semantic part of human correspondence. Emotions are significant for human correspondence as well as basic for human–computer cooperation. Viable correspondence between people is possibly achieved when both the importance and the emotion of the correspondence are perceived by all groups included. Understanding the significance of language has generally been concentrated on in natural language processing (NLP) as a semantic examination. In NLP, the text can be handled appropriately for classification. Emotion detection from facial emotion is the subfield of social signal processing applied in a wide assortment of regions, explicitly for human and PC collaboration. Many researchers have proposed various approaches, generally utilizing machine learning concepts. Automatic emotion recognition (AER) is significant for working with consistent intuitiveness between a person and a smart device toward fully acknowledging an intelligent society. Many researchers examined cross-lingual and multilingual speech emotion as a stage toward language-free emotion acknowledgment in natural speech. In the present work, we are proposing a deep learning-based AER system using four openly accessible datasets, namely Basic Arabic Vocal Emotions Dataset (BAVED), Acted Emotional Speech Dynamic Database (AESDD), Urdu written in Latin/Roman Script (URDU), and Toronto Emotional Speech Set (TESS), by utilizing the Jupyter notebook and a Python library for music and audio synthesis named Librosa. The experimental results exhibited that the proposed approach achieves better than the existing approaches, i.e., the accuracy of the proposed system with the URDU dataset is 96.24%, the TESS dataset is 99.10%, the AESDD dataset is 65.97%, and the BAVED dataset is 73.12%. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantics

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