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International Conference on Internet of Things 2024, ICIoT 2024

作者： Li, Yeqin Chieng, David Kwong, Chiew Foong Lee, Boon Giin Zhang, Yunfan Wang, Yin Lin, Ting-Jung Next-Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering University of Nottingham Ningbo China Ningbo China School of Computer Science University of Nottingham Ningbo China Ningbo China Department of Electrical and Computer Engineering Duke University United States HealthyPhoton Technology Co. Ltd. Ningbo315042 China

A data-driven approach has been developed to classify indoor activities using only commonly available passive environmental sensors, such as CO2, temperature, humidity, and passive infrared (PIR). An integrated IoT system comprising of sensor nodes, edge node and an intelligent server is designed and developed to provide real-time activity classification. Spectral Clustering and bidirectional long short-term memory (BiLSTM) are employed to achieve automatic labeling and room state prediction. The results show that the overall classification accuracy ranges from 88% to 96% for five target states across three distinct environments using CO2 and PIR values as input variables. Additionally, incorporating more input variables has been evaluated to access the ability of real-time classification of proposed model. An innovative monitoring mode can provide a different approach for detecting activities and occupancy in the future. © The Institution of engineering & Technology 2024.

关键词： Sensor nodes

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Real-Time Testing of Microgrid Control Algorithms: Development of Experimental Setup 29

Real-Time Testing of Microgrid Control Algorithms: Developme...

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29th International Conference on Information Technology, IT 2025

作者： Forcan, Miodrag Dobrić, Goran Abed, Amir Žarković, Mileta Ikić, Marko Forcan, Jovana Barragán-Villarejo, Manuel Maza-Ortega, José María De Paula Garcia-López, Francisco University of East Sarajevo Faculty of Electrical Engineering East Sarajevo71123 Bosnia and Herzegovina University of Belgrade School of Electrical Engineering Belgrade11120 Serbia University of East Sarajevo Faculty of Philosophy Department of Computer Science and Systems East Sarajevo71420 Bosnia and Herzegovina University of Sevilla Department of Electrical Engineering Seville41004 Spain

ISBN: (纸本)9798331517649

This paper provides an overview of microgrid control strategies, examining differences between centralized and decentralized approaches, and focusing on classical hierarchical control schemes as well as the structure of three-layer microgrid control systems. It also explores Hardware-in-the-Loop modeling, a crucial approach for microgrid simulation, with particular emphasis on devices supporting microgrid modeling. The paper primarily focuses on the design and implementation requirements of an experimental setup for real-time testing of microgrid control algorithms. The setup incorporates Hardware-in-the-Loop device, a power amplifier, a power converter, a battery energy storage system, and a digital controller. It is specifically designed to handle both power and information (control) signals, facilitating a comprehensive approach to evaluating and validating microgrid control strategies in real-world conditions. A detailed analysis of the setup elements and their interactions is also provided. © 2025 IEEE.

关键词： Hardware-in-the-loop simulation

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Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

Understanding the Impact of Unobservable Variables on the Pe...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Juarez Garcia, Ezequiel Stephens, Chad L. Napoli, Nicholas J. Laboratory Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Crew Systems & Aviation Operations Branch and System-Wide Safety Project NASA Langley Research Center HamptonVA23681 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separ ability of class distributions. Such challenges result in unrepresentative training data, complex skewedor warped decision boundaries, and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions with in the feature space through partitioning. This enables the optimization of local models with inthe regions to overcome the impact of un observ ability and complex decision boundaries indifferent feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of un observability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobserv ability in predictive mo

关键词： Information fusion

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Learning good state and action representations for Markov decision process via tensor decomposition

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 5157-5209页

作者： Chengzhuo Ni Yaqi Duan Munther Dahleh Mengdi Wang Anru R. Zhang Department of Electrical & Computer Engineering Princeton University Laboratory for Information & Decision Systems Massachusetts Institute of Technology Electrical Engineering & Computer Science Department Massachusetts Institute of Technology Department of Biostatistics & Bioinformatics Duke University

The transition kernel of a continuous-state-action Markov decision process (MDP) admits a natural tensor structure. This paper proposes a tensor-inspired unsupervised learning method to identify meaningful low-dimensional state and action representations from empirical trajectories. The method exploits the MDP's tensor structure by kernelization, importance sampling and low-Tucker-rank approximation. This method can be further used to cluster states and actions respectively and find the best discrete MDP abstraction. We provide sharp statistical error bounds for tensor concentration and the preservation of diffusion distance after embedding. We further prove that the learned state/action abstractions provide accurate approximations to latent block structures if they exist, enabling function approximation in downstream tasks such as policy evaluation.

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Ferrite Shielding for Eddy Current Suppression on Inductors and Transformers Using Ribbon-Based Magnetic Cores

Ferrite Shielding for Eddy Current Suppression on Inductors ...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Gao, Zihan Wang, Fred The University of Tennessee Knoxville Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN United States The University of Tennessee Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350376067

Ribbon-based magnetic cores, such as nanocrystalline and amorphous cores, have been widely used in inductors and transformers in high power converters. However, unwanted eddy current can be found on the surfaces of the core laminations due to fringing effect and leakage magnetic field. In this paper, a ferrite shielding structure is proposed to create bypass loops for lamination layers to avoid the stray field crossing the lamination layers. The mechanism of the proposed shielding is demonstrated. Simulations and tests have proved the effectiveness for the gapped inductor, as well as core and shell-type transformers. © 2024 IEEE.

关键词： Magnetic leakage

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Capacity Development Through Intensive Training of Higher Education Teachers for Implementation of PLC Curricula in South-East Asia 21

Capacity Development Through Intensive Training of Higher Ed...

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21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024

作者： Bencheva, Nina Zahariev, Plamen Hristov, Georgi Banjerdpongchai, David Kostadinov, Nikolay University of Ruse 'Angel Kanchev' Telecommunications Department Ruse Bulgaria Chulalongkorn University Department of Electrical Engineering Bangkok Thailand University of Ruse 'Angel Kanchev' Computer Systems and Technology Department Ruse Bulgaria

ISBN: (纸本)9798331516635

The ASEAN Factori 4.0 project seeks to contribute to the enhancement of education in industrial automation at six Asian universities in Thailand, Laos, and Cambodia. The paper outlines the steps of teacher-intensive training and evaluates the results, including an analysis of the methodology employed. The training was divided into two parts, each lasting two weeks. Its objective was to prepare teachers and equip them with practical skills to train students in Programmable Logic Controllers (PLCs) and their applications in industrial automation. During the first part (Training 1), Asian teachers underwent training at three EU universities: Claude Bernard University Lyon 1, University of Ruse, and Grenoble Alpes University. The second part (Training 2) took place at the Centres of Excellence established in the six Asian universities: Chulalongkorn University, Mae Fah Luang University, Royal University of Phnom Penh, Institute of Technology of Cambodia, National University of Laos, and Savannakhet University. Pre- and Post-surveys were conducted after each training session to assess the participants' knowledge and gather feedback. The Pre-test aimed to evaluate the trainees' level of PLC knowledge, while the Post-test questionnaires collected feedback and assessed the courses' effectiveness. Two Post-tests were designed: one completed after each lab session to adjust training sessions and teaching materials based on the feedback, and another one assessing overall trainee satisfaction. The paper presents an analysis of the results of all surveys and conclusions with regard to the results and the effectiveness of the training are drawn. © 2024 IEEE.

关键词： Teaching

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Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

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computers, Materials & Continua 2022年第6期71卷 6275-6291页

作者： Riad Alharbey Ameen Banjar Yahia Said Mohamed Atri Abdulrahman Alshdadi Mohamed Abid Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Electrical Engineering Department College of EngineeringNorthern Border UniversityArarSaudi Arabia Laboratory of Electronics and Microelectronics(LR99ES30) Faculty of Sciences of MonastirUniversity of MonastirTunisia College of Computer Sciences King Khalid UniversityAbhaSaudi Arabia CES Laboratory ENISUniversity of SfaxTunisia

Hajj and Umrah are two main religious duties for *** help faithfuls to perform their religious duties comfortably in overcrowded areas,a crowd management system is a must to control the entering and exiting for each *** the number of people is very high,an intelligent crowd management system can be developed to reduce human effort and accelerate the management *** this work,we propose a crowd management process based on detecting,tracking,and counting human faces using Artificial Intelligence *** detection and counting will be performed to calculate the number of existing visitors and face detection and tracking will be used to identify all the humans for security *** proposed crowd management system is composed form three main parts which are:(1)detecting human faces,(2)assigning each detected face with a numerical identifier,(3)storing the identity of each face in a database for further identification and *** main contribution of this work focuses on the detection and tracking model which is based on an improved object detection *** improved Yolo v4 was used for face detection and *** has been very effective in detecting small objects in highresolution *** novelty contained in thismethod was the integration of the adaptive attention mechanism to improve the performance of the model for the desired *** wise attention mechanism was applied to the output layers while both channel wise and spatial attention was integrated in the building *** main idea from the adaptive attention mechanisms is to make themodel focus more on the target and ignore false positive *** demonstrated the efficiency of the proposed method through expensive experimentation on a publicly available *** wider faces dataset was used for the train and the evaluation of the proposed detection and tracking *** proposed model has achieved good results with 91.2%of mAP and a processing speed

关键词： Crowdmanagement Hajj and Umrah face detection object tracking convolutional neural networks(CNN) adaptive attention mechanisms

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Supremal and Robust Control against Actuator Jamming Attacks in Cyber-Physical systems

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期9卷 1-13页

作者： Duo, Wenli Wang, Shouguang Zhou, MengChu You, Dan Wisniewski, Remigiusz Bazydlo, Grzegorz Albeshri, Aiiad Institute of Systems Engineering Macau University of Science and Technology Macau China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Department of Computer Science King Abdulaziz University Jeddah Saudi Arabia

Cyber-physical systems, such as unmanned aerial vehicles and connected and autonomous vehicles, are vulnerable to cyber attacks, which can cause significant damage to society. This paper examines the attack issue in cyber-physical systems within the framework of discrete event systems. Specifically, we consider a scenario where a malicious intruder injects a jamming signal into an actuator channel. It disrupts the transmission of control commands and prevents an actuator from receiving them. This is termed an actuator jamming attack. In the paper, we first analyze the closed-loop system behavior under such an attack. An attack structure is constructed to illustrate how an intruder exploits a jamming attack to drive a system into unsafe states. Then, we study the supervisory control problem for a system exposed to such an attack. The problem is reduced to a basic supervisory control one in discrete event systems by introducing the concept of dynamically controllable language. A solution to this problem is explored, where we establish an existence condition for a supremal and robust supervisor that is capable of defending against actuator jamming attacks, and design an algorithm to derive it. Finally, the effectiveness of our method is illustrated by an intelligent automated guided vehicle system. IEEE

关键词： Discrete event simulation

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Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 75-89页

作者： Aijuan Song Guohua Wu Witold Pedrycz Ling Wang School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland Department of Automation Tsinghua UniversityBeijing 100084China

Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple *** algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one ***,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used *** contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve *** VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation *** enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the *** test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,*** results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared ***,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.

关键词： Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)

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A 1.65 to 1.84 GHz Filtering SPDT Switch With Fully Tunable Insertion Phase Using NRN and Mixed Electromagnetic Coupling Techniques

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IEEE Transactions on Circuits and systems II: Express Briefs 2023年第9期70卷 3353-3357页

作者： Wei, Zhihua Chi, Pei-Ling Xu, Ruimin Yang, Tao School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu300 Taiwan Research Center of Advanced RF Chips and Systems Nanhu Laboratory Jiaxing Zhejiang314000 China

This brief presents a novel filtering single-pole-double-throw (SPDT) switch with continuously tunable center frequency and insertion phase. It is comprised of six varactor-loaded microstrip resonators and three tunable non-resonating nodes (NRNs) at source and loads. The controllable mixed electromagnetic couplings are introduced on the two main paths of each channel of the switch. At ON-state, the designed filtering switch can generate a 4th-order bandpass filtering performance with high selectivity, and the insertion phase can be continuously tuned with a full 360° tuning range by changing the reactances of NRNs and switching the dominated modes of the mixed couplings. At OFF-state, the mixed electromagnetic couplings are set to zero, and hence high isolation can be realized. To validate the proposed technique, a circuit prototype is designed and fabricated. The measured results suggest that the designed filtering SPDT switch can operate with a tunable center frequency ranging from 1.65 GHz to 1.84 GHz, and its insertion phase at ON-state channel can be continuously tuned from -180° to 180°. During the whole tuning process, the measured in-band isolation for OFF-state channel keeps better than 40 dB. © 2023 IEEE.

关键词： Bandpass filters

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