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IEEE Conference on Decision and Control

作者： Dimitrios Kotsinis Charalampos P. Bechlioulis Department of Electrical and Computer Engineering Athena Research Center Robotics Institute Maroussi Greece University of Patras Greece

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we propose a sub-optimal approach for the multi-agent navigation problem in simply-connected workspaces. We design a decentralized control law exhibiting the following three properties: (1) navigation of each agent with the optimal policy towards its destination, (2) avoidance of collision with other nearby agents and the workspace boundary, and (3) knowledge about the current position and not the destination of nearby agents. Moreover, we refer to the sub-optimal approach because the computational complexity and time needed to calculate the global optimal solution become unrealistic as the number of agents increases. In our case, each agent has a predetermined optimal policy calculated by a novel off-policy iterative method, to go towards its destination and it deviates from it in order to avoid collisions. The purpose of the simulation study is to examine how much the sub-optimal greedy trajectory of each agent deviates from the optimal one.

关键词： Navigation Decentralized control Vectors Trajectory Iterative methods Computational complexity Game theory Multi-agent systems

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Machine Vision Observation, Artificial Intelligence Pattern Recognition, Protective Circuit Design, Characterization of Multiple Materials, and Nano-Structural Analysis for Investigating InGaN Green Light Emitting Diode Degradation in a Salty Water Vapor Environment

Machine Vision Observation, Artificial Intelligence Pattern ...

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2024 IEEE International Reliability Physics Symposium, IRPS 2024

作者： Chen, Cheng-Shan Yang, Chun-Yen Yang, Shao-Jui Wang, Deng-Yi Kuo, Yaw-Wen Hsiao, Wei-Han Chou, Hsin-Hung Lin, Chia-Feng Li, Yung-Hui Wu, Yewchung Sermon Chen, Hsiang Han, Jung National Yang Ming Chiao Tung University Department of Materials Science and Engineering Hsinchu30010 Taiwan National Chi Nan University Department of Electrical Engineering Nantou54561 Taiwan National Chi Nan University Department of Applied Materials and Optoelectronic Engineering Nantou54561 Taiwan Chang Gung University Department of Electrical Engineering Taoyuan33302 Taiwan National Chi Nan University Department of Computer Science & Information Engineering Nantou54561 Taiwan National Chung Hsing University Department of Materials Science and Engineering Taichung40227 Taiwan Hon Hai Research Institute AI Research Center Taipei11494 Taiwan Yale University Department of Electrical Engineering New HavenCT06511 United States

ISBN: (纸本)9798350369762

This study delves into the degradation of GaN-based LEDs in saline environments, a relatively underexplored area of research. LEDs are known for their longevity, but face challenges under extreme conditions. Utilizing artificial intelligence, machine vision, and material analysis, this study detects early signs of LED degradation[1], [2]. The results highlight the impact of saline exposure on LED performance, with some LEDs continuing to function for up to 30 minutes before failure. Advanced circuits ensure uninterrupted operation. Encompassing electrical engineering, computer science, and materials science, this study provides a comprehensive approach to LED fault detection and protection. © 2024 IEEE.

关键词： III-V semiconductors

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Real-Time Tunable Gas Sensing Platform Based on SnO_(2) Nanoparticles Activated by Blue Micro-Light-Emitting Diodes

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Nano-Micro Letters 2024年第12期16卷 103-119页

作者： Gi Baek Nam Jung-El Ryu Tae Hoon Eom Seung Ju Kim Jun Min Suh Seungmin Lee Sungkyun Choi Cheon Woo Moon Seon Ju Park Soo Min Lee Byungsoo Kim Sung Hyuk Park Jin Wook Yang Sangjin Min Sohyeon Park Sung Hwan Cho Hyuk Jin Kim Sang Eon Jun Tae Hyung Lee Yeong Jae Kim Jae Young Kim Young Joon Hong Jong-In Shim Hyung-Gi Byun Yongjo Park Inkyu Park Sang-Wan Ryu Ho Won Jang Department of Materials Science and Engineering Seoul National UniversitySeoul 08826Republic of Korea Research Laboratory of Electronics Department of Mechanical EngineeringMassachusetts Institute of TechnologyCambridgeMA 02139USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos AngelesCA 90089USA Department of Display Materials Engineering Soonchunhyang UniversityAsan 31538Republic of Korea Department of Photonics and Nanoelectronics BK21 FOUR ERICA-ACE CenterHanyang University ERICAAnsan 15588Republic of Korea Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok 25913Republic of Korea Advance Institute of Convergence Technology Seoul National UniversitySuwon 16229Republic of Korea Department of Mechanical Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea Department of Physics Chonnam National UniversityGwangju 500-757Republic of Korea

Micro-light-emitting diodes(μLEDs)have gained significant interest as an activation source for gas sensors owing to their advantages,including room temperature operation and low power ***,despite these benefits,challenges still exist such as a limited range of detectable gases and slow *** this study,we present a blueμLED-integrated light-activated gas sensor array based on SnO_(2)nanoparticles(NPs)that exhibit excellent sensitivity,tunable selectivity,and rapid detection with micro-watt level power *** optimal power forμLED is observed at the highest gas response,supported by finite-difference time-domain ***,we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO_(2)*** noble metals induce catalytic interaction with reducing gases,clearly distinguishing NH3,H2,and ***-time gas monitoring based on a fully hardwareimplemented light-activated sensing array was demonstrated,opening up new avenues for advancements in light-activated electronic nose technologies.

关键词： Micro-LED Gas sensor array Low power consumption Metal decoration Real-time detection

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Urban Water Consumption Forecasting Using Deep Learning and Correlated District Metered Areas

arXiv

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arXiv 2024年

作者： Malialis, Kleanthis Mavri, Nefeli Vrachimis, Stelios G. Kyriakou, Marios S. Eliades, Demetrios G. Polycarpou, Marios M. KIOS Research Innovation Center of Excellence Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

Accurate water consumption forecasting is a crucial tool for water utilities and policymakers, as it helps ensure a reliable supply, optimize operations, and support infrastructure planning. Urban Water Distribution Networks (WDNs) are divided into District Metered Areas (DMAs), where water flow is monitored to efficiently manage resources. This work focuses on short-term forecasting of DMA consumption using deep learning and aims to address two key challenging issues. First, forecasting based solely on a DMA's historical data may lack broader context and provide limited insights. Second, DMAs may experience sensor malfunctions providing incorrect data, or some DMAs may not be monitored at all due to computational costs, complicating accurate forecasting. We propose a novel method that first identifies DMAs with correlated consumption patterns and then uses these patterns, along with the DMA's local data, as input to a deep learning model for forecasting. In a real-world study with data from five DMAs, we show that: i) the deep learning model outperforms a classical statistical model;ii) accurate forecasting can be carried out using only correlated DMAs' consumption patterns;and iii) even when a DMA's local data is available, including correlated DMAs' data improves accuracy. © 2024, CC BY-NC-SA.

关键词： Water distribution systems

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Maintaining Fuse in the Presence of Distributed Generation Sources in the Distribution Network to Improve Protection System 17

Maintaining Fuse in the Presence of Distributed Generation S...

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17th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2023

作者： Taleb, Mahdi Fani, Bahador Shahgholian, Ghazanfar Mosavi, Amir Fathollahi, Arman Islamic Azad University Najafabad Branch Department of Electrical Engineering Najafabad Iran Islamic Azad University Smart Microgrid Research Center Najafabad Branch Najafabad Iran Obuda University John von Neumann Faculty of Informatics Budapest Hungary Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark

ISBN: (纸本)9798350321104

The need to reduce greenhouse gas emissions and the high price of fossil fuels have made renewable resources attractive in energy-based economies around the world. Renewable energy sources will make up a significant part of the modern energy system in the future because they have promising potential. Many countries are already working to increase their capacity for renewable energy. The placement of renewable resources in power systems has gained significant attention due to their potential to provide power to distribution feeders or near consumers. However, the integration of these resources can have adverse effects on the distribution network, which necessitates their placement to be carefully considered. In this study, a novel method of coordinating protection devices based on the current control of distributed production sources using their current-voltage diagram during fault conditions is suggested. The proposed method aims to address the coordination and regulation problems encountered when integrating scattered resources into the network. To evaluate the effectiveness of our approach, we compare the impact of the presence of renewable sources at various points on the network during flooding. We conduct simulations using the ETAP software and present the obtained results. The proposed protection coordination method effectively mitigates the challenges of integrating renewable resources into the distribution network, providing a promising solution to support the transition towards a more sustainable energy future. © 2023 IEEE.

关键词： Renewable energy resources

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Age of Information Based User Scheduling and Data Assignment in Multi-User Mobile Edge Computing Networks:An Online Algorithm

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China Communications 2024年第5期21卷 153-165页

作者： Ge Yiyang Xiong Ke Dong Rui Lu Yang Fan Pingyi Qu Gang School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education Beijing 100044China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing 100044China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering College ParkMarylandUSA

This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading *** weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization problem is formulated by jointly optimizing the user scheduling and data *** to the non-analytic expression of the WSA *** optimization variables and the unknowability of future network information,the problem cannot be solved with known solution ***,an online Joint Partial Offloading and User Scheduling Optimization(JPOUSO)algorithm is proposed by transforming the original problem into a single-slot data assignment subproblem and a single-slot user scheduling sub-problem and solving the two sub-problems *** analyze the computational complexity of the presented JPO-USO algorithm,which is of O(N),with N being the number of *** results show that the proposed JPO-USO algorithm is able to achieve better AoI performance compared with various baseline *** is shown that both the user’s data assignment and the user’s AoI should be jointly taken into account to decrease the system WSA when scheduling users.

关键词： age of information(aoi) mobile edge computing(mec) user scheduling

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Study and Simulation of Wind Farms Based on Squirrel Cage Induction Generator in electrical Distribution System 17

Study and Simulation of Wind Farms Based on Squirrel Cage In...

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17th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2023

作者： Zanjani, Sayed Mohammad Ali Moazzami, Majid Honarvar, Mohammad Amin Mosavi, Amir Fathollahi, Arman Islamic Azad University Smart Microgrid Research Center Najafabad Branch Najafabad Iran Islamic Azad University Najafabad Branch Department of Electrical Engineering Najafabad Iran Obuda University John von Neumann Faculty of Informatics Budapest Hungary Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark

ISBN: (纸本)9798350321104

Wind power sources are evolving and becoming more prevalent in energy systems, which has implications for a variety of operational metrics, including stability and frequency regulation. To guarantee the stability and reliability of the modern power system, it is crucial that grid-connected wind turbines operate consistently and reliably. It is still challenging to accurately and reliably characterize these generators and their components to analyze sequestered operational possibilities like short-circuit faults, soft-starting, and generator switching. To comprehensively understand the stability interactions within distribution grids or localized networks, an accurate simulation is essential. The current study investigates the impact of a static synchronous compensator (STATCOM) on a distribution system that incorporates an induction generator wind farm. Specifically, we analyze and simulate the effect of STATCOM on a 25 kV distribution system, which delivers the power generated by a 9 MW wind farm to the grid via a 25 kV line. The outcomes demonstrate that STATCOM plays a pivotal role in regulating the voltage changes at the common connection point between the distribution system and the wind farm during both normal and faulty conditions. In addition to improving the stability and efficiency of the distribution network, STATCOM can also provide active power during short-circuit fault conditions. Based on the outcomes, the effectiveness of the proposed approach is highly dependent on the wind energy system's parameters. Due to the inherent parameter uncertainty, non-stationarity, and nonlinearity in the wind power system, the use of a parameter prediction approach based on artificial intelligence (AI) is recommended for future research. © 2023 IEEE.

关键词： Static synchronous compensators

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Power Budget Calculation and Sensitivity Enhancement for N×25 Gbps TDM-PON Configuration 3

Power Budget Calculation and Sensitivity Enhancement for N×...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Feituri, Ahmed B Abdullah, M.F.L. Swedan, Abdulhameed Almabrok Suliman, Hager A Universiti Tun Hussen Onn Malaysia Faculty of Electrical and Electronic Engineering Batu Pahat Malaysia The Electronic and Communication Research Center Applied Research and Development Authority Tripoli Libya University of Misurata Department of Computer Science Misurata Libya

ISBN: (纸本)9798350319897

Passive Optical Network (PON) standards relied on Time Division Multiplexing (TDM) and Wavelength Division Multiplexing (WDM) methods to maximize data rate. The latest 25GS-PON specifications were declared by Multi-Source Agreement (MSA) group in 2022. The current work stacks two and four 25-Gb/s TDM-PON downstream (DS) channels. The simulation, evaluation, and outcomes are completed using various versions of *** software. O-band wavelength plan as well as Continuous-Wave (CW) laser with Non-Return-to-Zero/On-Off-Keying (NRZ-OOK) format support the system to mitigate Chromatic Dispersion (CD) and upgrade the system capacity. The power budget of 31.1 dB is suitable for Optical Distribution Network (ODN) standards, and the standard value of receiver sensitivity (-24.1 dBm) is achieved. The transmitted power of 1, 4, and 7 dBm are needed for 32, 64, and 128 users/λ, respectively. The transmission is successful for 512 subscribers and 20 km optical reach without the use of amplifiers, Forward Error Correction (FEC), and compensation techniques. The effect of four-wave mixing (FWM) is solved by the wavelength space of 0.8 nm as well as the slight increase in transmitted power from 7 to 7.8 dBm. The open and clear eye diagrams prove the quality of received signals. The simplicity of structure is high because of utilizing basic components and Intensity Modulation/Direct Detection (IM/DD) strategy without amplification and equalization. FEC and compensation techniques are recommended for future work. © 2023 IEEE.

关键词： Passive optical networks

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Incremental Learning with Concept Drift Detection and Prototype-based Embeddings for Graph Stream Classification

arXiv

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arXiv 2024年

作者： Malialis, Kleanthis Li, Jin Panayiotou, Christos G. Polycarpou, Marios M. KIOS Research Innovation Center of Excellence Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

Data stream mining aims at extracting meaningful knowledge from continually evolving data streams, addressing the challenges posed by nonstationary environments, particularly, concept drift which refers to a change in the underlying data distribution over time. Graph structures offer a powerful modelling tool to represent complex systems, such as, critical infrastructure systems and social networks. Learning from graph streams becomes a necessity to understand the dynamics of graph structures and to facilitate informed decision-making. This work introduces a novel method for graph stream classification which operates under the general setting where a data generating process produces graphs with varying nodes and edges over time. The method uses incremental learning for continual model adaptation, selecting representative graphs (prototypes) for each class, and creating graph embeddings. Additionally, it incorporates a loss-based concept drift detection mechanism to recalculate graph prototypes when drift is detected. © 2024, CC BY-SA.

关键词： Decision making

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An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships

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Science China Earth Sciences 2023年第11期66卷 2563-2578页

作者： Yunqiang ZHU Kai SUN Shu WANG Chenghu ZHOU Feng LU Hairong LV Qinjun QIU Xinbing WANG Yanmin QI State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Department of Automation Tsinghua UniversityBeijing 100084China School of Computer Science China University of GeosciencesWuhan 430074China Department of Electronic Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Computer Science University of Nottingham Ningbo ChinaNingbo 315100China

Geoscience knowledge graph(GKG)can organize various geoscience knowledge into a machine understandable and computable semantic network and is an effective way to organize geoscience knowledge and provide knowledge-related *** a result,it has gained significant attention and become a frontier in *** knowledge is derived from many disciplines and has complex spatiotemporal features and relationships of multiple scales,granularities,and ***,establishing a GKG representation model conforming to the characteristics of geoscience knowledge is the basis and premise for the construction and application of ***,existing knowledge graph representation models leverage fixed tuples that are limited in fully representing complex spatiotemporal features and *** address this issue,this paper first systematically analyzes the categorization and spatiotemporal features and relationships of geoscience *** this basis,an adaptive representation model for GKG is proposed by considering the complex spatiotemporal features and *** the constraint of a unified spatiotemporal ontology,this model adopts different tuples to adaptively represent different types of geoscience knowledge according to their spatiotemporal *** model can efficiently represent geoscience knowledge,thereby avoiding the isolation of the spatiotemporal feature representation and improving the accuracy and efficiency of geoscience knowledge *** can further enable the alignment,transformation,computation,and reasoning of spatiotemporal information through a spatiotemporal ontology.

关键词： Geoscience Knowledge graph Representation model Spatiotemporal features Spatiotemporal relationships

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