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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Liang, Hengyue Liang, Buyun Cui, Ying Mitchell, Tim Sun, Ju University of Minnesota Electrical & Computer Engineering Minneapolis United States University of Minnesota Computer Science & Engineering Minneapolis United States University of Minnesota Industrial & Systems Engineering Minneapolis United States City University of New York Queens College New York City United States

ISBN: (纸本)9781728163277

Empirical evaluation of the adversarial robustness of deep learning models involves solving non-trivial constrained optimization problems. Popular numerical algorithms to solve these constrained problems rely predominantly on projected gradient descent (PGD) and mostly handle adversarial perturbations modeled by the 1, 2, and ∞ metrics. In this paper, we introduce a novel algorithmic framework that blends a general-purpose constrained-optimization solver PyGRANSO, With Constraint-Folding (PWCF), to add reliability and generality to robustness evaluation. PWCF 1) finds good-quality solutions without the need of delicate hyperparameter tuning and 2) can handle more general perturbation types, e.g., modeled by general p (where p > 0) and perceptual (nonp) distances, which are inaccessible to existing PGD-based algorithms. © 2023 IEEE.

关键词： adversarial attack adversarial robustness constrained optimization deep neural networks perceptual distance robustness evaluation

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Collection: The Aegean Ro-Boat Race 2023

IEEE Data Descriptions

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IEEE Data Descriptions 2024年 1卷 87-94页

作者： Alexandros Troupiotis-Kapeliaris Nikolaos Sapountzis Giannis Spiliopoulos Thomas Kogias Piyabhum Chaysri Bernardo AntÓnio Correia Gabriel Miguel Filipe Santos Silva Elias Xidias Konstantinos Blekas João Tasso de Figueiredo Borges de Sousa Dimitris Zissis Department of Product and Systems Engineering University of the Aegean Syros Greece Department of Computer Science and Engineering University of Ioannina Ioannina Greece Department of Electrical and Computer Engineering of the Faculty of Engineering University of Porto Porto Portugal

In this article, we introduce a publicly available real-world dataset collected during the Aegean Ro-Boat Race 2023, which took place at the University of the Aegean in Syros, Greece. The Aegean Ro-Boat Race represents an international competition at the university level, challenging teams to innovate and develop autonomous marine robotic systems capable of performing in unknown dynamic maritime environments under real-world conditions. The 2023 competition featured three primary mission tasks, each designed to test different aspects of the robotic systems: 1) high-speed performance for evaluating the speed and agility of the autonomous vessels; 2) collision avoidance for assessing the systems’ ability to detect and avoid obstacles in real-time; and 3) endurance for testing the operational longevity and efficiency of the robotic systems over extended periods. In total, seven teams registered for the competition, with five of them being from Greece and two from the countries of Portugal and Latvia. Due to several technical difficulties, three vessels were able to complete all races, and data were recorded during their entire participation. The spatiotemporal data for the “Aegean Ro-Boat Race” was gathered through an onboard data logging system that continuously monitored various sensors, including global positioning system (GPS), for all vessels during the entire competition. The dataset includes positional reports from the vessels during all three races (totaling over 6500 records), the positions of the external track and obstacle buoys, together with a file regarding the weather conditions during the race day. IEEE SOCIETY/COUNCIL computer Society (CS), Aerospace and Electronic systems Society (AESS), Signal Processing Society (SPS), Oceanic engineering Society (OES), Intelligent Transportation systems Society (ITSS) DATA TYPE/LOCATION CSV; Syros, Greece DATA DOI/PID 10.5281/zenodo.13318421

关键词： Robots Collision avoidance Boats Navigation Trajectory Testing Spatiotemporal phenomena Drones Technological innovation Sea measurements

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MINIMUM-RANK POSITIVE SEMIDEFINITE MATRIX COMPLETION WITH CHORDAL PATTERNS AND APPLICATIONS TO SEMIDEFINITE RELAXATIONS

Applied Set-Valued Analysis and Optimization

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Applied Set-Valued Analysis and Optimization 2023年第2期5卷 265-283页

作者： Jiang, Xin Sun, Yifan Andersen, Martin S. Vandenberghe, Lieven Department of Industrial and Systems Engineering Lehigh University BethlehemPA18015-1582 United States Department of Computer Science Stony Brook University Stony BrookNY11794-2424 United States Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States

We present an algorithm for computing the minimum-rank positive semidefinite completion of a sparse matrix with a chordal sparsity pattern. This problem is tractable, in contrast to the minimumrank positive semidefinite completion problem for general sparsity patterns. We also present a similar algorithm for the Euclidean distance matrix completion with minimum embedding dimension. The two algorithms use efficient recursions over a clique tree associated with the chordal sparsity pattern. As an application, we use the minimum-rank completion method as a rounding technique to convert the solution of a sparse semidefinite optimization problem with non-unique solutions to an optimal solution of lower rank. In experiments with semidefinite relaxations of optimal power flow problems, the minimum-rank completion often results in solutions of lower rank than the solutions computed by interior-point solvers. ©2023 Applied Set-Valued Analysis and Optimization.

关键词： Electric load flow

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Digitalization of Building electrical systems Towards Energy Efficiency: Planning and Design Insights

Digitalization of Building Electrical Systems Towards Energy...

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Renewable Energies and Smart Technologies (REST), International Conference on

作者： Edon Hajdini Agnesë Avdiu Mimoza Ibrani Department of Power Systems Faculty of Electrical and Computer Engineering (Alumni) Prishtina Republic of Kosovo Department of Telecommunications Faculty of Electrical and Computer Engineering Prishtina Republic of Kosovo

ISBN: (数字)9798350358902

ISBN: (纸本)9798350358919

The digitalization of building electrical systems is considered a transformative step towards enhancing energy efficiency. In this paper are presented the design and analysis in-sights of power digitalization in electrical systems for commercial buildings using EcoStruxure Power Design software, allowing for the simulation of electrical loads and providing the right circuit breakers and cable sections of feeders based on the planned load. To comprehensively analyze and harness the benefits of digitalization, we initially developed a conventional electrical system. Through this conventional scheme, shortcomings, and devised strategies are identified to enhance energy efficiency, preventive maintenance, proactive maintenance, as well as monitoring and remote commanding after implementation. To conduct the comparative analysis, we present a design of a digital electrical system where implementation within the project is structured across two layers: connected products and edge control. This integrated approach optimizes the operational efficiency and performance of the electrical system while leveraging the capabilities afforded by digitalization. A comparative analysis of the conventional electrical system and the digital electrical system is presented, highlighting the importance and advantages of digitalization.

关键词： Renewable energy sources Buildings Reliability engineering Energy efficiency Software Maintenance Software reliability

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Exploring CST Simulation Techniques for TEM Mode and Unit Cell Analysis to Determine Refractive Index 12

Exploring CST Simulation Techniques for TEM Mode and Unit Ce...

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12th International electrical engineering Congress, iEECON 2024

作者： Malathong, Kritthanit Konpang, Jessada Kongjareansuk, Sayree Akkaraekthalin, Prayoot Chudpooti, Nonchanutt Thitimahatthanakusol, Phatsakul Rajamangala University Of Technology Krungthep Faculty Of Engineering Department Of Electrical And Telecommunication Engineering 2 Nanglingee Rd. Sathorn Thungmahamek Bangkok10120 Thailand Rajamangala University Of Technology Krungthep Faculty Of Engineering Department Of Electrical And Telecommunication Engineering Bangkok Sathorn10120 Thailand King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering 1518 Pracharat 1 Road Bangsue Bangkok10800 Thailand King Mongkut's University Of Technology North Bangkok Faculty Of Applied Science Department Of Industrial Physics And Medical Instrumentation Bangkok10800 Thailand Rajamangala University Of Technology Isan Faculty Of Engineering And Technology Department Of Telecommunication Engineering 744 Sura Narai Rd Nai-muang Mueang Nakhon Ratchasima Nakorn Ratchasima30000 Thailand

ISBN: (纸本)9798350383591

The study investigates the accuracy of CST simulations in TEM mode and unit cell simulations for determining the refractive index (n) of materials. The results in TEM mode align with the expected properties of air, affirming the correctness of settings. However, when using unit cell simulations, the materials properties template inaccurately calculates n values, deviating from reality. Further examination reveals that unit cell simulations emit waves of different modes (TE, TM, or CP) instead of TEM, leading to inconsistencies. A revised equation is introduced to address this discrepancy, yielding results closer to actual n values. The importance of parameters like D and m is emphasized, as variations significantly impact the n values obtained. The introduced equation provides more accurate n cal-culations in unit cell simulations than the default CST template. © 2024 IEEE.

关键词： Refractive index

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Detection of Magnetite Rust Using Circular Microstrip Patch Antenna-based Chipless RFID Sensor

Detection of Magnetite Rust Using Circular Microstrip Patch ...

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2023 International electrical engineering Congress, iEECON 2023

作者： Nongpromma, Sirisak Janin, Suwan Kaemarungsi, Kamol Boonpoonga, Akkarat Chudpooti, Nonchanutt Bannawat, Lakkhana King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Rajamangala University of Technology Lanna Lampang Faculty of Engineering Department of Engineering and Technology Lampang52000 Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand Rajamangala University of Technology Rattanakosin Faculty of Engineering Department of Computer Engineering Nakhon Pathom Thailand

ISBN: (纸本)9798350332360

In this paper, detection of the magnetite rust is presented by using a chipless RFID sensor based on a circular microstrip patch antenna (CMPA). The sensor is designed at the resonant frequency of 4.89 GHz by using a single-layer PCB with its dielectric constant of 4.3. Simulations were conducted to verify that the designed sensor can detect the magnetite rust through shifted resonant frequency. In simulations, the sensor was mounted on the iron with its magnetite rust. The width and depth of iron rust were varied in order to investigate the effect of iron rust on the resonant frequency. Simulation results have been shown that the proposed chipless RFID sensor and RCS' can be utilized to detect the effect of the iron rust. © 2023 IEEE.

关键词： Microstrip antennas

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Prediction of Internet Broadband Connectivity Classification in West Java Indonesia using Machine Learning

Prediction of Internet Broadband Connectivity Classification...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Kusuma Atmaja, Wahyu Haris Heryadi, Yaya Sonata, Ilvico Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department West Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Engineering Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect Internet connectivity in clusters of West Java, Indonesia. It also aims to evaluate the results of models that forecast how these internal factors will affect internet connectivity. According to the research findings, the FTTH Cluster has eight significant Internet predictor connectivity out of 18 elements. Activation delay and Administration Documentation of Activation with Connectivity were the two major parameters modeled out of the 18 components. Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree (DT) models were used to predict Internet Broadband Connectivity Classification based on the two most important variables. According to the study, ANN is the best model, with 99% accuracy and 99.6% precision when compared to SVM and DT. Furthermore, it exceeds previous studies that used the ANN model and achieved 97.92% accuracy. © 2023 IEEE.

关键词： Prediction models

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Tracking-Differentiator-Based Sliding-Mode Control for Tracking Control

Tracking-Differentiator-Based Sliding-Mode Control for Track...

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2023 China Automation Congress, CAC 2023

作者： Li, Wenfei Li, Boyuan Hua, Wei Huang, Chao Du, Haiping Xing, Haitao Research Center for Intelligent Transportation Zhejiang Lab Hangzhou China The Hong Kong Polytechnic University Department of Industrial & Systems Engineering Hong Kong School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong Australia

ISBN: (纸本)9798350303759

Tracking control has attracted significant attention because of its close link with industrial applications. Tracking control requires that a control algorithm can ensure that an actuator follows control commands, with a fast response anti-disturbance abilities and small chattering. A tracking-differentiator-based sliding-mode control approach for tracking control is proposed in this paper. A tracking differentiator has the ability to obtain the desired signal's differential signal, even when there is noise in the desired signal. A differential signal is often required in the design of sliding-mode controllers. When tracking differentiator is applied to a sliding-mode controller, the chattering of the control commands (caused by noise disturbance) can be reduced while the fast response of the sliding-mode controller can be maintained. The simulation results show that the proposed controller is effective. © 2023 IEEE.

关键词： Sliding mode control

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A Deep Learning Approach for Satellite and Debris Detection: YOLO in Action 26

A Deep Learning Approach for Satellite and Debris Detection:...

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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Ahamed, Md Younus Bin Syed, Md Asif Chatterjee, Paroma Bin Habib, Al Zadid Sultan West Virginia University Lane Department of Computer Science and Electrical Engineering MorgantownWV26506 United States West Virginia University Department of Industrial and Management Systems Engineering MorgantownWV26506 United States

ISBN: (纸本)9798350359015

Satellite detection refers to the identification and recognition of satellites in satellite images. This task is crucial for various applications, including space surveillance, satellite tracking, and space debris monitoring. Several studies have been conducted to develop methods and techniques for satellite detection. The intricacy and scale of satellite images make satellite detection incredibly challenging. The process of manual identification and classification necessitates a significant amount of time. Recently, Deep Learning (DL) has emerged as a highly promising approach in computer Vision (CV) tasks. This study evaluates the effectiveness of three widely employed DL-based object detection algorithms, specifically YOLOv4, YOLOv5, and YOLOv8, within the field of satellite detection. The algorithms have undergone training utilizing a dataset of satellite photos comprising both satellites and debris. The evaluation of the algorithm's performance involved the utilization of broadly accepted metrics, including Precision, Recall, Mean Average Precision (mAP), Box Loss, and Class Loss. The findings indicated that all three algorithms exhibited a high level of accuracy in detecting and precisely determining the location of objects inside satellite data. The performance of YOLOv5 and YOLOv8 surpassed that of YOLOv4 across various measures, with a notable advantage observed in detecting tiny objects. Overall, this study demonstrates the capabilities of DL algorithms in the context of satellite detection and classification techniques. © 2023 IEEE.

关键词： Debris Object Detection Satellite YOLOv4 YOLOv5 YOLOv8

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Operational strategies for a photovoltaic-thermal system integrated with an electric air-to-water heat pump 3

Operational strategies for a photovoltaic-thermal system int...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Russo, Giuseppe Olympios, Andreas V. Pandey, Chandan Buonomano, Annamaria Markides, Christos N. University of Naples Federico II Department of Industrial Engineering Naples80125 Italy Laboratory Sargent Centre for Process Systems Engineering Department of Chemical Engineering London United Kingdom University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (纸本)9798350375923

In this study, operational strategies are investigated for an air-based photovoltaic-thermal (PV-T) system integrated with a domestic air-to-water heat pump. The PV-T system is used to simultaneously generate electricity and heat ambient air, which serves as the heat source for the heat pump. By utilising a variable-speed fan to regulate airflow, the PV-T system outlet temperature is adjusted, and the focus is on how different outlet temperatures impact the PVT system electrical and thermal efficiency, heat pump performance, and overall electricity requirements for heating. The performance of the integrated system is assessed for a case study of a household application in north Italy. The optimal PV-T outlet temperature is found to be between 30 - 35 °C, resulting in only 5% less electricity production than an equivalent PV system with equal nominal electricity capacity, while reducing overall electricity required for heating by over 15% compared to PV-integrated heat pumps. © 2024 IEEE.

关键词： Photovoltaics

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