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3rd International Conference on Advancement in electrical and Electronic engineering, ICAEEE 2024

作者： Mamun, Abdullah Al Shuvo, Mehedi Hasan Islam, Towhidul Islam, Dwin Islam, Md. Jakirul Tanvir, Faysal Amin DUET Department Of Computer Science and Engineering Gazipur Bangladesh Lamar University Department of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798350388282

Currently, electricity demand is constantly increasing all over the world, and the demand for this electricity is much higher than the production. As a result, the whole world is facing a global problem. In this decade, many researchers have been concerned about it and have suggested many ways to generate electricity in several ways, but they are not all concerned about low-cost, user-friendly, reliable data loggers and monitoring systems. To resolve the issue, we proposed an intelligent and environment-friendly way to generate electricity in all areas of a developing country. Initially, heat is generated either through household cooking activities or by burning excess or unnecessary garbage. After that, the solar panels are charged from the generated heat, and the charge is stored in a battery from the solar panel. The data logger, which is based on the ESP32 microcontroller, records all monitoring parameters on the cloud and presents them in the Android application. All the processes are completed automatically without any human interaction, and burning unnecessary garbage establishes environmental sustainability. The data logger hardware prototype that has been created incorporates four sensors to measure temperature, humidity, voltage, and current, which show up on an Android application with real-time data on many metrics. Additionally, it provides maintenance professionals with crucial information about any problems related to battery charging. To complete the work, we have created the hardware implementation of photovoltaic systems that use the IoT for remote data collection to provide us sustainability, and this prototype's total cost is affordable. © 2024 IEEE.

关键词： Sustainable development

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Build to Win: electrical Hardware Opportunities for STEM Education 14

Build to Win: Electrical Hardware Opportunities for STEM Edu...

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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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Enhancing Time Series Prediction in Industrial Processes: A Self-Attention BiLSTM Approach 7

Enhancing Time Series Prediction in Industrial Processes: A ...

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7th International Conference on Robotics, Control and Automation engineering, RCAE 2024

作者： Wen, Sicheng Xu, Jiajun University of Engineering Science Department of Electronic and Electrical Engineering Shanghai Shanghai China University of Shanghai for Science and Technology Department of Optical-Electrical and Computer Engineering Shanghai China

ISBN: (纸本)9798350355642

The development of data-driven soft sensors for modeling complex data, particularly in scenarios characterized by strong nonlinearity, high dimensionality, cross-correlation and autocorrelation, remains a significant challenge in process data analysis. Bidirectional Long Short-Term Memory (BiLSTM) networks are highly effective in capturing both forward and backward dependencies within sequences, thereby enhancing the extraction of temporal features from time series data. However, BiLSTM networks may struggle to capture global dependencies, especially in long sequences. To address this limitation, the self-attention mechanism, which excels in modeling global relationships across all positions in the input sequence, can be integrated with BiLSTM by applying weighted attention to the two different directions of BiLSTM, thereby enhancing its performance. This study proposes a novel method called SA-BiLSTM, which combines the strengths of the BiLSTM network and the self- attention mechanism. The self-attention layer captures global dependencies, while the BiLSTM layer extracts comprehensive temporal features in both directions, which are then passed to a fully connected layer for final prediction. Extensive comparisons with traditional methods such as BiLSTM, LSTM with added self-attention mechanism, LSTM, RNN, and SVM validate the superior performance of the proposed SA-BiLSTM method in handling complex time series data. © 2024 IEEE.

关键词： Spatio-temporal data

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ProTEA: programmable Transformer Encoder Acceleration on FPGA

ProTEA: Programmable Transformer Encoder Acceleration on FPG...

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2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Kabir, Ehsan Bakos, Jason D. Andrews, David Huang, Miaoqing University of Arkansas Department of Electrical Engineering and Computer Science Fayetteville United States University of South Carolina Department of Computer Science and Engineering United States

ISBN: (纸本)9798350355543

Transformer neural networks (TNN) have been widely utilized on a diverse range of applications, including natural language processing (NLP), machine translation, and computer vision (CV). Their widespread adoption has been primarily driven by the exceptional performance of their multi-head self-attention block used to extract key features from sequential data. The multi-head self-attention block is followed by feedforward neural networks, which play a crucial role in introducing non-linearity to assist the model in learning complex patterns. Despite the popularity of TNNs, there has been limited numbers of hardware accelerators targeting these two critical blocks. Most prior works have concentrated on sparse architectures that are not flexible for popular TNN variants. This paper introduces ProTEA, a runtime programmable accelerator tailored for the dense computations of most of state-of-the-art transformer encoders. ProTEA is designed to reduce latency by maximizing parallelism. We introduce an efficient tiling of large matrices that can distribute memory and computing resources across different hardware components within the FPGA. We provide run time evaluations of ProTEA on a Xilinx Alveo U55C high-performance data center accelerator card. Experimental results demonstrate that ProTEA can host a wide range of popular transformer networks and achieve near optimal performance with a tile size of 64 in the multi-head self-attention block and 6 in the feedforward networks block when configured with 8 parallel attention heads, 12 layers, and an embedding dimension of 768 on the U55C. Comparative results are provided showing ProTEA is 2.5× faster than an NVIDIA Titan XP GPU. Results also show that it achieves 1.3 - 2.8× speed up compared with current state-of-the-art custom designed FPGA accelerators. © 2024 IEEE.

关键词： Attention Encoder FPGA Hardware Accelerators High-Level Synthesis Natural Language Processing Neural Networks Transformer

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Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

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computer Modeling in engineering & sciences 2024年第9期140卷 2779-2794页

作者： Li-Woei Chen Kun-Lin Tsai Fang-Yie Leu Wen-Cheng Jiang Shih-Ting Tseng Department of Computer and Information Sciences Chinese Military AcademyKaohsiung830TaiwanChina Department of Electrical Engineering Tunghai UniversityTaichung407TaiwanChina Department of Computer Science Tunghai UniversityTaichung407TaiwanChina

Various mobile devices and applications are now used in daily *** devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile ***-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing ***,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)*** the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of *** indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES *** reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.

关键词： Mobile application security AES data encryption time parameter mobile device

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Understanding Consumer Perceptions of Green Software: A Study in the Online Social Media Marketing Context

Understanding Consumer Perceptions of Green Software: A Stud...

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2023 International Conference on Industry sciences and computer science Innovation, iSCSi 2023

作者： Irtisamul, Shadat Hassan, Marzan Binte Sadia, Farzana Hasan, Mahady Rokonuzzaman, Mohammad Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Department of Electrical Engineering and Computer Science North South University Dhaka Bangladesh

This study explores the influence of social media marketing on consumers' decisions to purchase green software and identifies key factors affecting those decisions. The findings contribute to effective marketing strategies for promoting environmentally friendly technologies and increasing the adoption of green software. Social media marketing is highlighted as a crucial platform for communication and collaboration, shaping consumers' subjective norms and influencing decision-making. By utilizing persuasive techniques and emphasizing eco-friendly choices, social media marketing can significantly impact consumers' behavior, attitudes, and decision-making processes, promoting sustainable practices and increasing the adoption of eco-friendly software. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Consumer behavior

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Performance Analysis of Cell Free-Massive MIMO with Hybrid RF/FSO Fronthaul Links

Performance Analysis of Cell Free-Massive MIMO with Hybrid R...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Mannil, Jasni Areepatta Ahmed, Imtiaz Rubaai, Ahmed Hasan, Kamrul Howard University Department of Electrical Engineering and Computer Science WashingtonDC United States Tennessee State University Department of Electrical and Computer Engineering NashvilleTN United States

ISBN: (纸本)9798331504847

In this paper, we analyze the performance of fronthaul communication links configured with hybrid radio frequency (RF) / free space optics (FSO) communication systems for a cell-free (CF) communication network. The fronthaul links are designed from access points (APs) to central processing unit (CPU) and selection combining (SC) is performed at CPU for the uplink data transmission. We derive the closed-form outage probability expression by considering Rician fading for the RF link and Gamma-Gamma fading for the FSO link. The closed-form expressions are validated with Monte Carlo simulation framework for a wide-range of use cases. Numerical results show the effectiveness of the considered hybrid RF-FSO communication links for fronthaul communications of CF communication systems. © 2025 IEEE.

关键词： Radio communication

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Investigation of a New Stator Permanent Magnet with the effects of Flux-Reversal and Flux-Switching 16

Investigation of a New Stator Permanent Magnet with the effe...

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16th Annual Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2025

作者： Sarshar, Mohammad Reza Kondelaji, Mohammad Amin Jalali Mirsalim, Mojtaba Montazeri, Seyed Hamid Amirkabir University of Technology Tehran Polytechnic Department of Electrical Engineering Tehran Iran Department of Electrical Engineering and Computer Science Cambridge United States

ISBN: (纸本)9798331533946

This article studies a new stator-permanent magnet (PM) motor with flux-switching (FS) and flux-reversal (FR) effects synergies. The proposed structure benefits from the splitting stator pole PMs and consequent-pole FRPM, which reduces the PM utilization compared to the conventional ones. Also, the proposed structure is optimized by a random search multiobjective algorithm to attain the structure with the highest output torque and minimum torque ripple. Additionally, the proposed motor is compared to a conventional FSPM to investigate the advantages of the main motor. Using finite element analysis (FEA) studies, the flux density distribution results show that the FR effect lowers the saturation risk compared to FSPM. Also, the back-EMF generation of the proposed motor has improved by 135% compared to its benchmark. Correspondingly, fullload results show that the proposed topology has enhanced the average torque by 75% and deteriorated the ripple by about 55% compared to FSPM. Therefore, the proposed structure offers a profitable for high torque density applications. © 2025 IEEE.

关键词： Permanent magnets

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Internet of things technology, research, and challenges: a survey

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Multimedia Tools and Applications 2025年第11期84卷 8455-8490页

作者： Vishwakarma, Amit Kumar Chaurasia, Soni Kumar, Kamal Singh, Yatindra Nath Chaurasia, Renu Management science and technology Khalifa University Abu Dhabi United Arab Emirates Computer science & Engineering SGT University Gurugram India Department of Information Technology IGDTUW New Delhi India Electrical Engineering IIT Kanpur Kanpur India Computer science & Engineering AIT Rooma Kanpur India

The world of digitization is growing exponentially;data optimization, security of a network, and energy efficiency are becoming more prominent. The Internet of Things (IoT) is the core technology of modern society. This paper is based on a survey of recent and past technologies used for IoT optimization models, such as IoT with Blockchain, IoT with WSN, IoT with ML, and IoT with big data analysis. Suppose anyone wants to start core research on IoT technologies, research opportunities, challenges, and solutions. In that case, this paper will help me understand all the basics, such as security, interoperability, standards, scalability, complexity, data management, and quality of service (QoS). This paper also discusses some recent technologies and the challenges in implementation. Finally, this paper discusses research possibilities in basic and applied IoT Domains. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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Fault-Tolerant Bounded Flow Preservers 35

Fault-Tolerant Bounded Flow Preservers

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35th International Symposium on Algorithms and Computation, ISAAC 2024

作者： Bansal, Shivam Choudhary, Keerti Dhanoa, Harkirat Wardhan, Harsh Department of Computer Science and Engineering IIT Delhi India Department of Electrical Engineering IIT Delhi India

ISBN: (纸本)9783959773546

Given a directed graph G = (V, E) with n vertices, m edges and a designated source vertex s ∈ V, we consider the question of finding a sparse subgraph H of G that preserves the flow from s up to a given threshold λ even after failure of k edges. We refer to such subgraphs as (λ, k)-fault-tolerant bounded-flow-preserver ((λ, k)-FT-BFP). Formally, for any F ⊆ E of at most k edges and any v ∈ V, the (s, v)-max-flow in H \ F is equal to (s, v)-max-flow in G \ F, if the latter is bounded by λ, and at least λ otherwise. Our contributions are summarized as follows: 1. We provide a polynomial time algorithm that given any graph G constructs a (λ, k)-FT-BFP of G with at most λ2kn edges. 2. We also prove a matching lower bound of Ω(λ2kn) on the size of (λ, k)-FT-BFP. In particular, we show that for every λ, k, n ≥ 1, there exists an n-vertex directed graph whose optimal (λ, k)-FT-BFP contains Ω(min{2kλn, n2}) edges. 3. Furthermore, we show that the problem of computing approximate (λ, k)-FT-BFP is NP-hard for any approximation ratio that is better than O(log(λ−1n)). © Shivam Bansal, Keerti Choudhary, Harkirat Dhanoa, and Harsh Wardhan.

关键词： Polynomial approximation

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