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SFA-Net: A Selective Features Absorption Network for Object Detection in Rainy Weather Conditions

IEEE Transactions on Neural Networks and Learning Systems 2023年第8期34卷 5122-5132页

作者： Huang, Shih-Chia Hoang, Quoc-Viet Le, Trung-Hieu National Taipei University of Technology Department of Electronic Engineering Taipei10608 Taiwan National Taipei University of Technology International Graduate Program in Electrical Engineering and Computer Science Taipei10608 Taiwan Hung Yen University of Technology and Education Faculty of Information Technology Hungyen 17000 Viet Nam

In recent years, object detection approaches using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with rainy images due to lack of visibility. Aiming to bridge this gap, in this article, we present a novel selective features absorption network (SFA-Net) to improve the performance of object detection not only in rainy weather conditions but also in favorable weather conditions. SFA-Net accomplishes this objective by utilizing three subnetworks, where the feature selection subnetwork is concatenated with the object detection subnetwork through the feature absorption subnetwork to form a unified model. To promote further advancement in object detection impaired by rain, we propose a large-scale rainy image dataset, named srRain, which contains both synthetic rainy images and real-world rainy images for training and testing purposes. srRain is comprised of 25 900 rainy images depicting diverse driving scenarios in the presence of rain with a total of 181 164 instances interpreting five common object categories. Experimental results display that our SFA-Net reaches the highest mean average precision (mAP) of 77.53% on a normal image set, 62.52% on a synthetic rainy image set, 37.34% on a collected natural rainy image set, and 32.86% on a published real rainy image set, surpassing current state-of-the-art object detectors and the combination of image deraining and object detection models while retaining a high speed. © 2012 IEEE.

关键词： Feature extraction

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Graph Coordinates and Conventional Neural Networks - An Alternative for Graph Neural Networks

Graph Coordinates and Conventional Neural Networks - An Alte...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Qin, Zheyi Paffenroth, Randy Jayasumana, Anura P. Colorado State University Electrical and Computer Engineering Fort Collins United States Worcester Polytechnic Institute Department of Data Science Program WorcesterMA United States

ISBN: (纸本)9798350324457

Graph-based data present unique challenges and opportunities for machine learning. Graph Neural Networks (GNNs), and especially those algorithms that capture graph topology through message passing for neighborhood aggregation, have been a leading solution. However, these networks often require substantial computational resources and may not optimally leverage the information contained in the graph's topology, particularly for large-scale or complex *** propose Topology Coordinate Neural Network (TCNN) and Directional Virtual Coordinate Neural Network (DVCNN) as novel and efficient alternatives to message passing GNNs, that directly leverage the graph's topology, sidestepping the computational challenges presented by competing algorithms. Our proposed methods can be viewed as a reprise of classic techniques for graph embedding for neural network feature engineering, but they are novel in that our embedding techniques leverage ideas in Graph Coordinates (GC) that are lacking in current *** results, benchmarked against the Open Graph Benchmark Leaderboard, demonstrate that TCNN and DVCNN achieve competitive or superior performance to message passing GNNs. For similar levels of accuracy and ROC-AUC, TCNN and DVCNN need far fewer trainable parameters than contenders of the OGBN Leaderboard. The proposed TCNN architecture requires fewer parameters than any neural network method currently listed in the OGBN Leaderboard for both OGBN-Proteins and OGBN-Products datasets. Conversely, our methods achieve higher performance for a similar number of trainable parameters. These results hold across diverse datasets and edge features, underscoring the robustness and generalizability of our methods. By providing an efficient and effective alternative to message passing GNNs, our work expands the toolbox of techniques for graph-based machine learning. A significantly lower number of tunable parameters for a given evaluation metric makes TCNN and DVCNN especiall

关键词： graph analytics graph coordinate graph embedding green AI network embedding

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A Novel Via-Based Magnetic Coupling Solution to Improving Illumination of Artificial Magnetic Conductor by Antenna-on-Chip

A Novel Via-Based Magnetic Coupling Solution to Improving Il...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Yiyang Yu Atif Shamim Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

Antenna-on-Chip (AoC) is one of the most promising solutions in upcoming 6G era. However, AoC suffers from low gain usually due to the highly conductive silicon substrate in mainstream complementary-metal-oxide-semiconductor (CMOS) processes. Artificial magnetic conductors (AMC) embedded within the stack-up of standard CMOS processes have been widely used to enhance the gain by isolating the AoC from the Si substrate and providing constructive reflection. Nonetheless, the ultra-thin stack-up of standard CMOS processes causes that only the AMC unit cells nearby the AoC can be illuminated well while the outermost part is illuminated poorly, which prevents the AMC from its optimal reflection performance. To mitigate the issue, this paper proposes a novel via-based magnetic coupling enhancement structures (H-CES- V) to improve the AMC illumination by coupling the energy from well-illuminated unit cells to outermost unit cells magnetically. Compared to conventional AMC, the gain can be improved by 1.5 dBi with the proposed structure. Finally, the proposed AMC-backed AoC with H-CES- V shows a boresight gain of 7 dBi (12 dBi better than a standalone AoC without AMC), and a radiation efficiency of 59 % at 94 GHz.

关键词： Couplings Lighting Conductors CMOS process Silicon Gain Antennas Substrates Magnetic circuits Standards

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Using textile capacitive sensors to train synchronized movement of hands

Using textile capacitive sensors to train synchronized movem...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Chen, Shih-Hung Wu, Ze-We Liao, Kuo-Cheng Chen, Chi-Chun Ming Young Biomedical Corp. Miaoli Taiwan National Chin-Yi University of Technology Program Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

This study introduced a capacitive sensing interactive game platform aimed at promoting emotional stability, which we have named the 'Sunrise and Sunset' game. This game primarily consists of two pieces of regular textile fabric enveloping conductive silver fabric. A microcontroller was employed to extract the sensed capacitive values, and a game named 'Sunrise and Sunset' is designed to complement the slow raising and lowering of both hands. The development of this gaming platform has the potential to offer a novel method of emotional management, particularly in high-stress living environments. It can serve as an effective relaxation tool, aiding individuals in emotional balance, anxiety reduction, and stress alleviation. Simultaneously, this platform can contribute to the promotion of mental well-being, providing an engaging and beneficial means for people to manage their emotions and moods. © 2024 IEEE.

关键词： capacitive sensing emotional stability game relaxation tool silver fabric

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Impact of Multimedia Sensor Placement to Car Licence Number Detection 2022

Impact of Multimedia Sensor Placement to Car Licence Number ...

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11th International Conference on Software and computer Applications, ICSCA 2022

作者： Amelia, Afritha Zarlis, Muhammad Suherman, Suherman Efendi, Syahril Graduate Program of Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Electrical Engineering Faculty of Engineering University of Sumatera Utara Indonesia

ISBN: (纸本)9781450385770

A vehicle has a license plate and can be identified by the license number attached to the vehicle plate. For detection and recognition, multimedia sensors can be used so that it requires a vehicle tracking application that has a vehicle monitoring function and has implications for various fields. One of them is a multimedia sensor that requires an optimal design and method in the form of the number of multimedia sensors to be used, the placement of the multimedia sensor positions and solutions in the event of a system failure. To achieve multimedia sensor performance, research on multimedia sensors is carried out using a camera type with Phase Detection Auto Focus (PDAF) technology which is similar to a pair of right and left eyes to see an object. The objects detected were 2 cars, where the car passed the camera sensor at a speed of 10-15 km/hour 20 times. Changes in the distance of the vehicle to the camera affect the disparity value and the object's accuracy value, namely and the object's Accuracy value of the minimum disparity value of 6.20×106 of 16.88×109. © 2022 ACM.

关键词： Disparity Vehicle plate Phase Detection Auto Focus (PDAF) Tracking application Object accuracy

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Application of 3D Printing and Design in Healthcare: A Focus on Undergraduate Research to Attract Students to Bioengineering and Related Disciplines 54

Application of 3D Printing and Design in Healthcare: A Focus...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Zelada-Quiroz, Cindy M. Reyes-Santiago, Brian L. Ortiz-Rivera, Eduardo I. University of Puerto Rico at Mayagüez Bio-Engineering Graduate Program Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Computer Science and Engineering Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Electrical and Computer Engineering Mayagüez Puerto Rico

ISBN: (纸本)9798350351507

This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D

关键词： Students

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Ultra-Thin CMOS-Compatible Artificial Magnetic Conductor for Millimeter-Wave Antenna-on-Chip

Ultra-Thin CMOS-Compatible Artificial Magnetic Conductor for...

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Antennas and Propagation & USNC/URSI National Radio science Meeting

作者： Yiyang Yu Atif Shamim Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal KSA

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

Antenna-on-chip (AoC) is one of the promising solutions in the 6G era. However, it suffers from poor radiation due to the lossy Si substrate. Placing an artificial magnetic conductor (AMC) under the AoC cannot only isolate the AoC from the lossy Si substrate but also provide in-phase reflection. Nonetheless, the ultra-thin stack-up of the mainstream semiconductor technology makes the realization of AMC challenging at the millimeter-wave spectrum. To make the AMC electrically thicker, this paper presents four kinds of thickness reduction techniques (TRT): slot, notch, metallic post, and embedded guiding structure. With TRTs, an ultra-thin AMC ( $15\ \mu \mathrm{m}$ thickness) is realized. With the proposed AMC, the AoC demonstrated a gain of 3.2 dB at 72 GHz. Compared to the standalone antenna, the AMC enhances the gain by 7 dB.

关键词： 6G mobile communication Conferences Millimeter wave technology Conductors Silicon Reflection Gain

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Cuckoo Search-Optimized Deep CNN for Enhanced Cyber Security in IoT Networks

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computers, Materials & Continua 2024年第12期81卷 4109-4124页

作者： Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413TaiwanChina Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057MaharashtraIndia Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Business Administration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Research and Innovation Insights2TechinfoJaipur302001India Department of Computer Science Faculty of ScienceNorthern Border UniversityArar91431Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)Hong Kong518031China

Phishing attacks seriously threaten information privacy and security within the Internet of Things(IoT)*** phishing attack detection solutions have been developed for IoT;however,many of these are either not optimally efficient or lack the lightweight characteristics needed for practical *** paper proposes and optimizes a lightweight deep-learning model for phishing attack *** model employs a two-fold optimization approach:first,it utilizes the analysis of the variance(ANOVA)F-test to select the optimal features for phishing detection,and second,it applies the Cuckoo Search algorithm to tune the hyperparameters(learning rate and dropout rate)of the deep learning ***,our model is trained in only five epochs,making it more lightweight than other deep learning(DL)and machine learning(ML)*** proposed model achieved a phishing detection accuracy of 91%,with a precision of 92%for the’normal’class and 91%for the‘attack’***,the model’s recall and F1-score are 91%for both *** also compared our approach with traditional DL/ML models and past literature,demonstrating that our model is more *** study enhances the security of sensitive information and IoT devices by offering a novel and effective approach to phishing detection.

关键词： Deep learning phishing Cuckoo Search cable news network(CNN) IoT ANOVA F-test

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A robust multi-objective optimization algorithm for accurate parameter estimation for solar cell models

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Soft Computing 2024年第19期28卷 11265-11277页

作者： Singla, Manish Kumar Gupta, Jyoti Alsharif, Mohammed H. Kim, Mun-Kyeom Aljaidi, Mohammad Safaraliev, Murodbek Department of Interdisciplinary Courses in Engineering Chitkara University Institute of Engineering & ampTechnology Chitkara University Punjab India Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Engineering and Technology K. R. Mangalam University Gurgaon Haryana122003 India Department of Electrical Engineering College of Electronics and Information Engineering Sejong University 209 Neungdong-Ro Gwangjin-Gu Seoul05006 Korea Republic of School of Energy System Engineering Chung-Ang University 84 Heukseok-Ro Dongjak-Gu Seoul06974 Korea Republic of Department of Computer Science Zarqa University Zarqa13110 Jordan Department of Automated Electrical Systems Ural Federal University Yekaterinburg620002 Russia

The accuracy of solar cell models is crucial for enhancing the performance of solar photovoltaic (PV) systems. However, existing solar cell models lack precise parameters, and the manufacturer's datasheet does not provide the required information for reliable modeling. Consequently, accurate parameter estimation becomes necessary. This paper presents a simple multi-objective optimization algorithm (Hybrid Particle Swarm Optimization and Rat Search Algorithm (PSORSA)) designed to estimate cell parameters based on this observation. Unlike other optimization algorithms addressing this issue, the proposed algorithm aims to overcome challenges related to local minima and premature convergence, which often lead to suboptimal results. The paper focuses on assessing the reliability of the proposed algorithm by comparing its performance with other well-known optimization algorithms. The proposed optimizing algorithm is tested on the CEC 2019 benchmark function. Experimental results (RMSE), including statistical analysis, validate the algorithm's effectiveness by comparing them with other algorithms. At the end, non-parametric test is performed to justify the outcomes, vouching for the better performance of the proposed algorithm. The findings demonstrate that the proposed algorithms are particularly well-suited for estimating solar PV models. With its simple structure and high accuracy, the proposed algorithm exhibits great potential for various applications in the field of solar energy. Moreover, its computational efficiency and ease of implementation further contribute to its practicality. © The Author(s) 2024.

关键词： Solar cells

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Super-Resolution Displacement Spectroscopic Sensing over a Surface“Rainbow”

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engineering 2022年第10期17卷 75-81页

作者： Lyu Zhou Nan Zhang Chang Chieh Hsu Matthew Singer Xie Zeng Yizheng Li Haomin Song Josep Jornet Yun Wu Qiaoqiang Gan Department of Electrical Engineering The State University of New York at BuffaloBuffaloNY 14260USA Department of Biomedical Engineering The State University of New York at BuffaloBuffaloNY 14260USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA 02115USA Material Science Engineering Program King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia

Subwavelength manipulation of light waves with high precision can enable new and exciting applications in spectroscopy,sensing,and medical *** these applications,miniaturized spectrometers are desirable to enable the on-chip analysis of spectral *** particular,for imaging-based spectroscopic sensing mechanisms,the key challenge is to determine the spatial-shift information accurately(i.e.,the spatial displacement introduced by wavelength shift or biological or chemical surface binding),which is similar to the challenge presented by super-resolution ***,we report a unique"rainbow"trapping metasurface for on-chip spectrometers and *** with super-resolution image processing,the low-setting 4×optical microscope system resolves a displacement of the resonant position within 35 nm on the plasmonic rainbow trapping metasurface with a tiny area as small as0.002 *** unique feature of the spatial manipulation of efficiently coupled rainbow plasmonic resonances reveals a new platform for miniaturized on-chip spectroscopic analysis with a spectral resolution of 0.032 nm in wavelength *** this low-setting 4×microscope imaging system,we demonstrate a biosensing resolution of 1.92×109exosomes per milliliter for A549-derived exosomes and distinguish between patient samples and healthy controls using exosomal epidermal growth factor receptor(EGFR)expression values,thereby demonstrating a new on-chip sensing system for personalized accurate bio/chemical sensing applications.

关键词： Rainbow trapping Metasurface Surface plasmon polaritons Super-resolution displacement On-chip biosensing

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