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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Meghanathan, Natarajan Department of Electrical and Computer Engineering and Computer Science Jackson State University 1400 Lynch Street JacksonMS39217 United States

ISBN: (纸本)9783031535512

We perform factor analysis on the raw data of the four major neighborhood and shortest paths-based centrality metrics (Degree, Eigenvector, Betweenness and Closeness) and propose a novel quantitative measure called the CoreIntermediate-Peripheral (CIP) Index to capture the extent with which a node could play the role of a core node (nodes at the center of a network with larger values for any centrality metric) vis-a-vis a peripheral node (nodes that exist at the periphery of a network with lower values for any centrality metric). We conduct factor analysis (varimax-based rotation of the Eigenvectors) on the transpose matrix of the raw centrality metrics dataset, with the node ids as features, under the hypothesis that there are two factors (core and peripheral) that drive the values incurred by the nodes with respect to the centrality metrics. We test our approach on a diverse suite of 12 complex real-world networks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Factor analysis

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A Load Insensitive Model Predictive Control for a Three-phase Inverter with L-C Filter

A Load Insensitive Model Predictive Control for a Three-phas...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Zeng, Jianwu Kim, Taesic Winstead, Vincent Minnesota State University Department of Electrical and Computer Engineering and Technology MankatoMN56001 United States University of Missouri Department of Electrical Engineering and Computer Science ColumbiaMO65201 United States

ISBN: (纸本)9798350376067

The traditional model predictive control (MPC) for power inverters is designed upon a certain operating point and is solved with quadratic programming (QP). The performance may deteriorate under variations of converter parameters or the load. This paper proposes a load-insensitive MPC (LI-MPC) for a three-phase inverter. The load current is first estimated from the current and voltage measured from the L-C filter, then the optimization problem is online solved with the gradient descent (GD) method, which makes the solution insensitive to the parameter's variation in the power converter. Experiment results show that the LI-MPC not only has a lower and more stable total harmonic distortion value than the QP-MPC, but has a small voltage tracking error as well. Therefore, the proposed LI-MPC can achieve better power quality than the traditional MPC. © 2024 IEEE.

关键词： Predictive control systems

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Generative AI Co-Pilot for Rapid Prototyping of IEC 61499 Control Applications 29

Generative AI Co-Pilot for Rapid Prototyping of IEC 61499 Co...

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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Ovsiannikova, Polina Liakh, Tatiana Jhunjhunwala, Pranay Vyatkin, Valeriy Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleå Tekniska Universitet Department of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9798350361230

This work develops a concept of a natural language co-pilot for the creation of IEC 61499 applications to accelerate initial testing and development. The co-pilot addresses the challenge of generating the correct function blocks that can be opened in popular IEC 61499 IDEs. In our case study, we focus on the generation of the centralised controller that operates particular equipment to perform a defined process. In addition, we have developed a scheme for how the co-pilot will be integrated into the FBME IDE as an AI assistant in the next steps. In the discussion, we provide valuable information for future co-pilot developers on the possible problems they might face in this area and how to overcome them. © 2024 IEEE.

关键词： Rapid prototyping

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An Explicit Discontinuous Galerkin Time-Domain Scheme to Simulate Kerr Nonlinearity

An Explicit Discontinuous Galerkin Time-Domain Scheme to Sim...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Sun, Ruitao Dong, Ming Chen, Liang Bagci, Hakan Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9781665442282

A discontinuous Galerkin time-domain (DGTD) method is formulated and implemented to analyze transient electromagnetic field interactions in a medium with Kerr nonlinearity. The (nonlinear) Maxwell equations in conservative form are discretized using a DG scheme that employs the Harten-Lax-van Leer numerical flux to facilitate the information exchange between discretization elements. A slope limiter is introduced into the DGTD method to prevent generation of non-physical oscillations in the solution and maintain the stability of the explicit time marching. Numerical examples, which demonstrate the applicability and the accuracy of the proposed method, are presented. © 2023 IEEE.

关键词： Numerical methods

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Successful Applications and Future Challenges of Machine Learning for Power Systems

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IEEE ELECTRIFICATION MAGAZINE 2022年第4期10卷 90-+页

作者： Li, Fangxing Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

Machine learning (ML), or artificial intelligence (AI), is one of the emerging technologies for implementing the next-generation smart grid. In recent years, significant efforts have been devoted to exploring the potentials of ML and AI for solving complex power system problems. The IEEE WG on Machine Learning for Power Systems has recently organized several events in this heatedly studied area. These events include the following:

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Weibull probability distribution based on four years wind speed data using nine numerical methods

Weibull probability distribution based on four years wind sp...

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International Conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Badawi, Ahmed Ali, Hassan Ismail, Nasser A. Zyoud, Alhareth Yusoff, Siti Hajar Al-Rimawi, Ashraf Ghanem, Wasel College of Engineering Technology University of Doha for Science and Technology Doha Qatar Department of Electrical and Computer Engineering Birzeit University Birzeit Ramallah Palestine Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9781032803722

Wind energy potential can be estimated in a specific area using the Probability density function (PDF). PDF is used for the mean wind speed data on daily basis. This paper represents the analysis of the climatology of the mean wind speed data for Askalan city on the Mediterranean coastal plain of Palestine. A selection of the PDF had been implemented using nine numerical analysis methods to represent the cumulative distribution function and Weibull probability distribution. The two main parameters of the Weibull shape factor are k = 1.7848 and the scale factor parameter c = 4.3642 ms-1. The study assessment finds out the characteristics of wind energy conversion and results confirm that it can produce energy using small-scale wind turbines. Matlab software was used to implement the numerical methods and extract the wind characteristics. © 2025 The Author(s).

关键词： Windmill

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BIOMECHANICAL SIMULATION OF LATERAL ASYMMETRY IN TONGUE BRACING

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Canadian Acoustics - Acoustique Canadienne 2023年第3期51卷 196-197页

作者： Azreen, Jasia Mayer, Connor Liu, Yadong Shamei, Arian Stavness, Ian Gick, Bryan Department of Electrical and Computer Engineering University of British Columbia Canada Department of Language Science University of California Irvine United States Department of Linguistics University of British Columbia Canada Department of Computer Science University of Saskatchewan Canada

Tongue bracing occurs when the lateral edges of the tongue maintain contact with the palate or upper molars. Bracing is pervasive in speech: previous EPG data analysis shows lateral contact to be maintained for 97.5% of the total observation duration [Gick et al. (2017) JSLHR 60, 494]. This research has also indicated the presence of lateral bias or asymmetry in the tongue: a consistent tendency to release contact more on one side than the other, both in unilateral release and in sequential loss of contact during a bilateral release. However, in these cases of asymmetry, it remains unclear which side of the tongue should be considered dominant. The present study explores the question of dominance in lateral tongue bracing through biomechanical simulation of tongue muscle activation. Certain muscles have been identified as bracing agonists (GGP, GGM, MH, VERT, SL) and antagonists (GGA, STY, HG, TRANS, IL) [Liu et al. (2022) Phonetica 79, 523]. Agonists increase the likelihood of bilateral bracing and tend to raise or widen the tongue while antagonists decrease the likelihood of bilateral bracing and tend to lower or narrow the tongue. The current simulations explore whether a unilateral bracing outcome can be produced by asymmetric activation of agonists, antagonists or a combination thereof. Preliminary results from our simulation study show that reducing agonist activation or increasing antagonist activation on one side while keeping activations constant on the other side results in lower tongue-palate contact on the opposite side, due to the hydrostatic properties of the tongue, though the reduction is much greater in the former case. These results suggest that unilateral bracing may be instantiated primarily by contra-lateral muscle activation/deactivation from the side on which bracing contact is maintained, providing a starting point for further exploration of lateral tongue dominance. © 2023, Canadian Acoustical Association. All rights reserved.

关键词： Chemical activation

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Implementation of GUI-based SOME/IP and SOME/IP-SD communication

Implementation of GUI-based SOME/IP and SOME/IP-SD communica...

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2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023

作者： Oh, Sung Bhin Kim, Jong Hun Lee, Si Woo Park, Jae Bum Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Sungkyunkwan University Department of Electrical and Computer Science and Engineering Suwon Korea Republic of

ISBN: (纸本)9798350344318

This research paper introduces a graphical user interface (GUI)-based communication program designed for scalable service-oriented middleware over IP (SOME/IP) packet communication. The program establishes an environment for generating, transmitting, and monitoring both SOME/IP and SOME/IP service discovery (SOME/IP-SD) packets. This paper offers a concise overview of the GUI-oriented SOME/IP communication program, accompanied by an analysis of both transmitted and received packets using Wireshark. Additionally, potential avenues for future research are also discussed. © 2023 IEEE.

关键词： Graphical user interfaces

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Learning Multiagent Options for Tabular Reinforcement Learning using Factor Graphs

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1141-1153页

作者： Chen, Jiayu Chen, Jingdi Lan, Tian Aggarwal, Vaneet Purdue University School of Industrial Engineering West LafayetteIN47907 United States George Washington University Department of Electrical and Computer Engineering WashingtonDC20052 United States Purdue University School of Industrial Engineering The School of Electrical and Computer Engineering West LafayetteIN47907 United States King Abdullah University of Science and Technology Department of Computer Science Thuwal23955 Saudi Arabia

Covering option discovery has been developed to improve the exploration of reinforcement learning in single-agent scenarios, where only sparse reward signals are available. It aims to connect the most distant states identified through the Fiedler vector of the state transition graph. However, the approach cannot be directly extended to multiagent scenarios, since the joint state space grows exponentially with the number of agents, thus prohibiting efficient option computation. Existing research adopting options in multiagent scenarios still relies on single-agent algorithms and fails to directly discover joint options that can improve the connectivity of the joint state space. In this article, we propose a new algorithm to directly compute multiagent options with collaborative exploratory behaviors while still enjoying the ease of decomposition. Our key idea is to approximate the joint state space as the Kronecker product of individual agents' state spaces, based on which we can directly estimate the Fiedler vector of the joint state space using the Laplacian spectrum of individual agents' transition graphs. This decomposition enables us to efficiently construct multiagent joint options by encouraging agents to connect the subgoal joint states, which are corresponding to the minimum or maximum of the estimated joint Fiedler vector. Evaluation on multiagent collaborative tasks shows that our algorithm can successfully identify multiagent options and significantly outperforms prior works using single-agent options or no options, in terms of both faster exploration and higher cumulative rewards. © 2020 IEEE.

关键词： Reinforcement learning

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An Efficient Lane Following Navigation Strategy With Fusion Attention for Autonomous Drones in Urban Areas

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IEEE Transactions on Vehicular Technology 2023年第3期73卷 3094-3105页

作者： Lee, Chao-Yang Khanum, Abida Wang, Neng-Chung Karuparthi, Bala Syam Kumar Yang, Chu-Sing the Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliou64002 Taiwan the Computer Science and Communication Engineering National Cheng Kung University Tainan701 Taiwan the Department of Computer Science and Information Engineering National United University Miao-Li36003 Taiwan the Department of Aeronautical Engineering National Formosa University Huwei632 Taiwan the Department of Electrical Engineering National Cheng Kung University Tainan701 Taiwan

—Drones are a vital part of our daily lives because of their flexible flying nature and low operation and maintenance costs. Navigation is the most important aspect in the autonomous drone era. With that being said, recent studies have tackled the greatly challenging task of obtaining the most feasible and safest path. In this work, we focus on safe and reliable unmanned aerial vehicle navigation in densely populated city environments to efficiently follow the lane. We present herein a deep learning method through which a drone can autonomously navigate by following a lane in a dynamic urban environment. This drone perceives the environment by using two cameras facing front and down. A convolutional neural network (CNN) is used to capture the high-level feature representation through the attention and residual mechanism of the drone’s raw visual inputs. The CNN concurrent pipelines used for three raw visual inputs can output high-level features and follow the concurrent feature fusion into the self-head attention mechanism that encapsulates both dynamic and static information to predict yaw and linear velocity. These predictions are modulated into the final control commands to obtain smooth and continuous inputs that are delivered to the drone. The experimental evaluation results show that the proposed method can learn the drone’s navigation strategy for a lane following a guidance system. The high performance of the trained navigation policy is observed in the simulations with different scenarios. In conclusion, our proposed approach outperforms both existing and current state-of-the-art ImageNet models. © 2023 IEEE.

关键词： Cameras

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