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4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： Rojas, Julio Ernesto Quispe Tuesta, Julio Enrique Quispe Universidad Nacional Pedro Ruiz Gallo Computing and Electronic Departament Lambayeque Peru Universidad Nacional Tecnológica de Lima Sur System Engineering Program Lima Peru

ISBN: (纸本)9798350395914

The purpose of this research is to present an improved project method and the results obtained in its use for the application work of the electrical machines course of an electronic engineering program of the Pedro Ruiz Gallo National University of Lambayeque in Peru. Previously, from 2013 to 2018, the project method was used, and based on these experiences, a proj ect method was prepared with greater detail of the activities and deliverables in each phase of the method, the results are better information, planning and organization by part of the students and a better evaluation by the facilitator, who acts as a referee and not as a coach as in traditional vocational training. The improved project method that has been applied in the 2019-11 semester and completed the validation in the 2023 semesters, due to the COVID 19 quarantine in the years 2020 to 2022, no real application work was carried out. In order to train professionals with new skills, vocational training must be innovated with new teaching-learning modes, such as the project method. The projects carried out in 2019-11 gave 4 very good projects: Automotive alternator as direct current generator, DC generator based on a DC motor, Construction of a windshield wiper system, Construction of a single-phase induction motor;2 good projects and 5 regular projects. © 2024 IEEE.

关键词： AC generator motors

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Exploring the Impact of Early Detection on DL-Based NIDSs Models 14

Exploring the Impact of Early Detection on DL-Based NIDSs Mo...

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14th IEEE Annual Ubiquitous computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Wang, Minxiao Yang, Ning Weng, Ning Southern Illinois University Computer Engineering Program School of ECBE CarbondaleIL United States Southern Illinois University Information Technology Program School of Computing CarbondaleIL United States

ISBN: (纸本)9798350304138

Deep learning (DL) has been proposed as a promising solution for network intrusion detection systems (NIDSs). While most DL-based NIDSs focus on high accuracy, they often overlook the critical issue of NIDSs response time for intrusion behavior. Recently some existing works presented time-aware evaluation metrics or design DL-based solutions for early intrusion detection, yet they primarily focus on the post-performance of NIDSs, without thoroughly investigating the impact of early intrusion detection on DL-based NIDSs due to the black-box nature of DL models. To address this research gap, we explore the impact of early detection on DL-based models' detection accuracy and input features. In our empirical study, we implement two different existing deep learning-based NIDSs methods and evaluate them on three published benchmark NIDSs datasets. Based on the experiment results on DL-based NIDSs detection accuracy, we observe that the early detection scenario will lead to the NIDSs model's detection accuracy decreasing up to 50%. To understand the reasons behind it, we adopt the SHapley Additive exPlanations (SHAP) to analyze the importance of features and we observe the varying feature distributions. The feature importance and feature distribution results show that early intrusion detection may lead to a degradation of feature quality. © 2023 IEEE.

关键词： Intrusion detection

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Smart Energy Management with Integrated WSN and WMN: Advancing Efficiency and Sustainability

Smart Energy Management with Integrated WSN and WMN: Advanci...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Ali Alrasheedi Mousa Al-Abdulhadi Raha Almutairi Abdullah AlRuwaiei Almas Khlaif Abdullah AlAlati Omar R. Daoud Electrical and Computer Engineering Program School of Engineering and Computing American International University Aljahra Kuwait

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

The aim of this paper is to provide an advanced WSN solution for power-sustainable energy management and efficient communication, integrating the latest developments from the SEMS. This work will focus on the research effort directed at improving M2M communication and integrating WSNs with wireless mobile networks, as well as addressing PAPR, energy consumption, and scalability. It now applies to real-time monitoring of power usage, room temperature, and lighting by integrating renewable resources of energy with sophisticated algorithms and sensor networks. Key results include a 16.6% saving in energy consumptions, 78% in system delay improvements, and the implementation of solar energy systems that have realized significant cost savings while assuring environmental sustainability. This work proves the ability of the approach through wide simulations and real-world deployments for scalable and eco-friendly energy management solutions. Besides, this work is closely related to worldwide goals for reduction of carbon footprints and efficient resource utilization.

关键词： Wireless sensor networks Renewable energy sources Energy consumption Scalability Peak to average power ratio Real-time systems Parity check codes Energy efficiency Delays Sustainable development

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A Low-Power Level-2 Discrete Haar Wavelet Transform with Approximate Adders for ECG Signal

A Low-Power Level-2 Discrete Haar Wavelet Transform with App...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Henrique Seidel Morgana da Rosa Rodrigo Lopes Eduardo da Costa Rafael Soares Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

We present an energy-efficient implementation of the level-2 Pruned Discrete Haar Wavelet Transform (PDHWT-2) for R-peak detection in ECG signals. Approximate computing techniques were employed, including five well-established approximate adders (AxPPA, COPY, ETA-I, LOA, and Trunc) and bit truncation (T), to reduce energy consumption while maintaining accuracy above 99% for reliable R-peak detection. By focusing on the second-level detail coefficient $(D_{2})$ for peak detection and pruning the approximation coefficient, the PDHWT-2 design achieves significant reductions in computational complexity. The architecture, evaluated with ECG signals from the MIT-BIH database, maintained accuracy above 99% even with aggressive bit truncation and approximation, ensuring reliable medical-grade analysis. Integration of approximate adders (AxAs) and truncation enabled significant power and area savings. Specifically, the use of the AxPPA demonstrated power savings of up to 40% with area reductions of around 45%, making the PDHWT-2 a highly efficient solution for low-power ECG monitoring systems.

关键词： Accuracy Approximate computing Transforms Computer architecture Electrocardiography Energy efficiency Discrete wavelet transforms Reliability Adders Monitoring

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Exploring Approximate Adders for Accuracy- and Energy-Quality VLSI Watermarking Systems Design

Exploring Approximate Adders for Accuracy- and Energy-Qualit...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Morgana da Rosa Eduardo da Costa Rafael Soares Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

Approximate computing (AxC) has emerged as a viable alternative to enhance computational efficiency by leveraging the intrinsic error resilience of many applications. One of the leading strategies of AxC involves exploring different approximation adder (AxA) configurations as a viable form of reducing power consumption in many applications. This work explores the use of AxAs in a hybrid watermarking technique that combines discrete Haar-Wavelet (DHWT) and discrete cosine transforms (DCT). The proposed hybrid method, HyDHWCT, integrates these transforms to improve robustness and imperceptibility in watermarking systems while optimizing for energy efficiency. We evaluate the performance of various AxAs, including Copy, ETA, LOA, Truncation (Trunc), VLSPPAs, and the AxPPA, regarding energy consumption, circuit area, and error resilience. Our results demonstrate that the AxPPA-based HyDHWCT offers superior accuracy and energy-quality trade-offs over other state-of-the-art AxAs. Specifically, the AxPPA on HyDHWCT with K = 1 achieves up to 72.85% energy savings and 88.32% area savings compared to the exact HyDHWCT while maintaining high accuracy, with a normalized cross-correlation (NC) of 0.9949 and a structural similarity (SSIM) of 0.9920 for the extracted watermark. These results make the AxPPA-based HyDHWCT a highly effective solution for robust and energy-efficient watermarking systems.

关键词： Energy consumption Accuracy Energy conservation Watermarking DH-HEMTs Energy efficiency Robustness Discrete cosine transforms Adders Resilience

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Exploring Approximate Adders for Energy-Efficient Discrete Walsh-Hadamard Transform

Exploring Approximate Adders for Energy-Efficient Discrete W...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Leonardo Antonietti Rodrigo Lopes Morgana da Rosa Eloisa Barros Eduardo da Costa Rafael Soares Graduate Program on Computing - Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This work investigates the use of the Discrete Walsh-Hadamard Transform (DWHT) for cryptographic applications, particularly within resource-constrained environments like microcontrollers such as RISC-V. DWHT's use of adder and subtractor arithmetic operations makes it highly suitable for low-complexity algorithms. In order to enhance efficiency further, our work integrates various approximate adders (AxAs) such as AxPPA, COPY, ETA-I, LOA, and Trunc into both forward (DWHT) and inverse (IDWHT) transform architectures. Our approach outperforms existing methods from the literature regarding accuracy metrics, particularly for lower approximation levels $(K=1\ \text{to}\ K=3)$ , with substantial improvements in PSNR and SSIM. Additionally, our designs significantly reduce power and area compared to existing hardware implementations, show-casing their potential for deployment in real-world cryptographic and hardware security applications.

关键词： Measurement Accuracy Microcontrollers Circuits and systems Hardware security Transforms Energy efficiency Encryption Adders Arithmetic

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Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection

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Neural computing and Applications 2025年第6期37卷 4567-4583页

作者： Sayem, Faizul Rakib Islam, Md. Sakib Bin Naznine, Mansura Nashbat, Mohammad Hasan-Zia, Mazhar Kunju, Ali K Ansaruddin Khandakar, Amith Ashraf, Azad Majid, Molla Ehsanul Kashem, Saad Bin Abul Chowdhury, Muhammad E. H. Department of Electrical and Electronic Engineering University of Dhaka Dhaka Bangladesh Department of Biomedical Engineering Military Institute of Science and Technology Dhaka Bangladesh Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Chemical Engineering Department University of Doha for Science and Technology Doha Qatar Department of Electrical Engineering Qatar University Doha2713 Qatar Computer Applications Department Academic Bridge Program Qatar Foundation Doha Qatar Department of Computing Science AFG College With the University of Aberdeen Doha Qatar

Given the severity of waste pollution as a major environmental concern, intelligent and sustainable waste management is becoming increasingly crucial in both developed and developing countries. The material composition and volume of urban solid waste are key considerations in processing, managing, and utilizing city waste. Deep learning technologies have emerged as viable solutions to address waste management issues by reducing labor costs and automating complex tasks. However, the limited number of trash image categories and the inadequacy of existing datasets have constrained the proper evaluation of machine learning model performance across a large number of waste classes. In this paper, we present robust waste image classification and object detection studies using deep learning models, utilizing 28 distinct recyclable categories of waste images comprising a total of 10,406 images. For the waste classification task, we proposed a novel dual-stream network that outperformed several state-of-the-art models, achieving an overall classification accuracy of 83.11%. Additionally, we introduced the GELAN-E (generalized efficient layer aggregation network) model for waste object detection tasks, obtaining a mean average precision (mAP50) of 63%, surpassing other state-of-the-art detection models. These advancements demonstrate significant progress in the field of intelligent waste management, paving the way for more efficient and effective solutions. © The Author(s) 2024.

关键词： Deep learning for waste management Intelligent waste management Object detection in waste management Sustainable waste processing Urban solid waste Waste image classification

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Coupled PFAS Transport and Seepage Models to Evaluate Retardation due to Air-Water-Interface Adsorption

Coupled PFAS Transport and Seepage Models to Evaluate Retard...

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Geo-EnvironMeet 2025: Geoenvironmental Contamination and Waste Containment

作者： Alam, Md. Khorshed Farid, Arvin Computing Ph.D. Program Boise State Univ. BoiseID United States Dept. of Civil Engineering Boise State Univ. BoiseID United States

ISBN: (数字)9780784485699

The term Per- and polyfluoroalkyl substances (PFAS) refer to a class of manmade very stable chemicals popular for their ability to withstand heat and moisture. Hence, they are used in manufacturing a variety of goods and firefighting aqueous film-forming foams (AFFF). The discharge of these chemicals into the soil occurs when they are introduced into the environment through various means, such as being used in firefighting foams and similar products or when they get deposited in landfills. In addition to some levels of adsorption to a solid phase, PFAS have a propensity to adhere to the water-air interface, due to surfactant-like nature. This adsorption to air-water interfaces can complicate PFAS transportation through the vadose zone. The persistent properties and potential health risks linked to PFAS provide formidable complexity. Due to the widespread contamination of the environment caused by PFAS, scientists and environmental agencies are intensively studying the fate and flow of these chemicals within the soil environment. In this paper, two numerical models - groundwater seepage and PFAS transport - are developed to examine the impact of air-water interface adsorption on the transport of PFAS within soil's unsaturated (vadose) and saturated (groundwater) environments. For unsaturated soil and the coupled groundwater seepage and PFAS transport models, the degree of saturation is fed into the PFAS transport model from the seepage model;the results are shown through 2D snapshots at certain times that show the spatial distribution of PFAS concentration over time for the two inlet-outlet-combination scenarios. Highlighting the significant impact of air-water interface adsorption (caused by varying degrees of water saturation) on PFAS transport within the groundwater system, the coupled model emphasizes the essential importance of taking site-specific conditions and hydrogeological parameters into account when assessing the risks of PFAS contamination and devising

关键词： Seepage

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Comprehensive Averaged Model of DCM-Operated Boost Converter Fed by PV Source 4

Comprehensive Averaged Model of DCM-Operated Boost Converter...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Fairouz, Fatima A Elgendy, Mohammed A Muhammed, Musbahu Newcastle University School of Engineering Newcastle Upon Tyne United Kingdom Renewable Energy Program Kuwait Institute for Scientific Research Industrial Shuwaikh Kuwait Teesside University School of Computing Engineering & Digital Technologies Middlesbrough United Kingdom

ISBN: (纸本)9798350306262

The average model of DC-DC converters is commonly used to analyze the control stability and dynamics of switched-mode converters. Although the average model of the boost converter (BC) in the continuous conduction mode (CCM) and the discontinuous conduction modes (DCM) is well-covered in the literature, the modelling and control of the DCM-operated BC with the maximum power point tracking (MPPT) has not been paid much attention. In this paper, a comprehensive state-space averaged model of DCM-operated BC fed by photovoltaic (PV) source is derived. Higher-order, lower-order, reduced-order, and full-order models are considered. MATLAB simulation is used to verify the derived models. The converter dynamics were analyzed based on the bode-plot and the step-response for each model. Results show that the lower-full-order model is considered the most suitable choice for modelling the DCM-operated boost converter. © 2024 IEEE.

关键词： Boost converter

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A Power-Efficient VLSI Multiplier Design Employing Radix-2m Squarer Unit and Adder Compressor

A Power-Efficient VLSI Multiplier Design Employing Radix-2m ...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Leonardo Antonietti Morgana Da Rosa Rodrigo Lopes Eduardo Da Costa Rafael Soares Graduate Program on Computing - Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

Multipliers are pivotal in numerous applications, including digital signal processing, image processing, and video processing. Nonetheless, their operation substantially increases power consumption for these applications. Therefore, applying strategies that can reduce power in this arithmetic operator is paramount. This paper presents a novel approach to optimize arithmetic units, focusing on multiplier units, through the integration of the Radix- $2^{m}$ squarer unit (RSU) and 4–2 adder/subtractor compressor (AC). Compared to the state-of-the-art, the proposed multiplier unit, termed MRSU (multiplier unit RSU-based), offers significant area-and energy-savings. The synthesis results show remarkable improvements in the MRSU Dadda 4–2 architecture, which achieves 14.35× more energy-savings for 8 bits, 4.87× for 16 bits, and 2.22× for 32 bits compared to the multiplier unit automatically selected by the logic-synthesis tool. Furthermore, compared to the Booth multiplier with the Dadda compression tree, MRSU Dadda 4–2 exhibits 1.67× more energy-savings for 8 bits, 1.93× for 16 bits, and 1.95× for 32 bits.

关键词： Image coding Power demand Focusing Digital signal processing Computer architecture Very large scale integration Energy efficiency Electronic circuits Adders Arithmetic

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