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CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST)

作者： Hossein Rabbiun Jamal Mohammadi Mahmoud Shirazi Mehdi Kargahi Department of Computer Science and Information Technology Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (数字)9798331529284

ISBN: (纸本)9798331529291

This paper advances the schedulability analysis of the Adaptive Mixed-Criticality for Weakly Hard Real-Time Systems (AMC-WH) which allows a specified number of consecutive low-criticality (LO) jobs of tasks to be skipped when the system operates in the high-criticality (HI) mode. The current AMC-WH schedulability test, based on the skip-over model, in which low tasks are guaranteed to meet m − s out of m consecutive deadlines, where s is the number of allowed skips and m is the cycle length, only calculates the worst-case response times (WCRT) for low tasks under a fixed execution pattern post-mode switch. To address this limitation, we propose a new sufficient schedulability test for AMC-WH using the (m,k)-firm model, which allows various execution patterns for low tasks after a mode switch, enhancing the flexibility and applicability. Additionally, we develop an exact schedulability test for AMC-WH based on response time analysis (RTA). This test modifies the existing exact tests for the AMC algorithm, incorporating updates to state-space exploration and pruning rules to account for low task execution after a mode switch. Simulation results validate the effectiveness of our tests, demonstrating enhanced schedulability analysis and optimized resource allocation.

关键词： Adaptation models Adaptive systems Scheduling algorithms Simulation Switches Cyber-physical systems Real-time systems Time factors Resource management Testing

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Information-Exchange-Reduced Distributed FixedTime Secondary Control for DC Microgrid with Enhanced Stability

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IEEE Transactions on Industry Applications 2025年

作者： Chai, Junwei Xu, Zhao Wang, Minghao Lyu, Xue The Hong Kong Polytechnic University Department of Electrical and Electronics Engineering Hong Kong The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Shenzhen Research Institute Research Institute of Smart Energy Hong Kong Department of Electrical and Computer Engineering Zhuhai China University of Macau Advanced Research Institute Hengqin Zhuhai China

DC microgrids are a feasible grid system to host multiple distributed generators (DGs). In terms of the control and coordination of hosted DGs, the enhanced stability and fast dynamics of DC microgrids are required. To achieve these objectives, this paper proposes a comprehensive strategy that meticulously accounts for the impacts of transmission line impedances and constant power loads (CPLs). The strategy is architected with a dual-layer control approach: a stability enhancement controller is embedded within the primary control layer, while a novel distributed fixed-time controller is deployed in the secondary control layer, ensuring a robust and fast system performance. Specifically, for the primary control layer, the maximum tolerable CPL is firstly calculated using the reduced-order model and the impedance ratio criterion, contributing to more accurate and less conservative results. Additionally, a stability enhancement controller is designed to reshape the system's equivalent output impedance, improving both steady-state and transient stability of the DC microgrid and enabling the accommodation of larger CPLs. For the secondary control layer, a novel fixed-time secondary control scheme is put forward to achieve a concurrent DC bus voltage regulation and current sharing among DGs within a fixed time. Importantly, this method requires the transmission of only one variable to neighboring DGs, significantly decreasing communication traffic compared to the existing latest methods. The stability of the proposed scheme is theoretically proved through Lyapunov-based analysis. Case study results are presented to demonstrate the efficacy of the proposed strategy. © 1972-2012 IEEE.

关键词： Publishing

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Demonstration of IoT Sensors Powered by Ambient RF Energy Harvesting

Demonstration of IoT Sensors Powered by Ambient RF Energy Ha...

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International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT

作者： Chi-Yuk Chiu Charles Ng Ross Murch Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong Department of Electronic and Computer Engineering Institute for Advanced Study The Hong Kong University of Science and Technology Kowloon Hong Kong

ISBN: (数字)9798350314755

ISBN: (纸本)9798350314762

Ambient radio frequency (RF) powered Internet of Things (IoT) is a promising batteryless system for collecting environmental information for data exchange among devices. Ambient RF energy harvesting technology is most suitable for use in places that are hidden from light sources and are in difficult to reach places for battery replacement. In this paper, a demonstration of IoT sensors powered by ambient RF energy harvesting is presented. The system we have developed provides all key components from antenna, rectifier, power management unit (PMU), microcontroller unit (MCU) to sensing unit. In addition a novel 3-port antenna element for the systems is also described. The experimental results confirm that ambient RF signals can be regarded as an alternative to power supply in the next generation of wireless communications.

关键词： Radio frequency Wireless communication Power supplies RF signals Rectifiers Sensors Energy harvesting

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A Digital Twin-Based Intelligent Network Architecture for Underwater Acoustic Sensor Networks

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IEEE Transactions on Mobile Computing 2025年

作者： Song, Shanshan Huangfu, Bingwen Guo, Jiani Liu, Jun Cui, Junhong Shen, Xuemin Beihang University School of Electronic and Information Engineering Beijing100191 China Jilin University College of Computer Science and Technology Changchun130012 China UESTC Shenzhen Institute for Advanced Study Shenzhen China University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Underwater acoustic sensor networks (UASNs) drive toward strong environmental adaptability, intelligence, and multifunctionality. However, due to unique UASN characteristics, such as long propagation delay, dynamic channel quality, and high attenuation, existing studies present untimeliness, inefficiency, and inflexibility in real practice. Digital twin (DT) technology is promising for UASNs to break the above bottlenecks by providing high-fidelity status prediction and exploring optimal schemes. In this article, we propose a Digital Twin-based Network Architecture (DTNA), enhancing UASNs' environmental adaptability, intelligence, and multifunctionality. By extracting real UASN information from local (node) and global (network) levels, we first design a layered architecture to improve the DT replica fidelity and UASN control flexibility. In local DT, we develop a resource allocation paradigm (RAPD), which rapidly perceives performance variations and iteratively optimizes allocation schemes to improve real-time environmental adaptability of resource allocation algorithms. In global DT, we aggregate decentralized local DT data and propose a collaborative Multi-agent reinforcement learning framework (CMFD) and a task-oriented network slicing (TNSD). CMFD patches scarce real data and provides extensive DT data to accelerate AI model training. TNSD unifies heterogeneous tasks' demand extraction and efficiently provides comprehensive network status, improving the flexibility of multi-task scheduling algorithms. Finally, practical and simulation experiments verify the high fidelity of DT. Compared with the original UASN architecture, experiment results demonstrate that DTNA can: (i) improve the timeliness and robustness of resource allocation;(ii) greatly reduce the training time of AI algorithms;(iii) more rapidly obtain network status for multi-task scheduling at a low cost. © 2002-2012 IEEE.

关键词： Resource allocation

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Self-assembled microtubular electrodes for on-chip low-voltage electrophoretic manipulation of charged particles and macromolecules

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Microsystems & Nanoengineering 2022年第1期8卷 341-352页

作者： Apratim Khandelwal Nagendra Athreya Michael Q.Tu Lukas L.Janavicius Zhendong Yang Olgica Milenkovic Jean-Pierre Leburton Charles M.Schroeder Xiuling Li Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignUrbanaIL 61801USA Nick Holonyak Micro and Nanotechnology Laboratory University of Illinois Urbana-ChampaignUrbanaIL 61801USA Department of Chemical Engineering University of Illinois Urbana-ChampaignUrbanaIL 61801USA Beckman Institute for Advanced Science and Technology University of Illinois Urbana-ChampaignUrbanaIL 61801USA Department of Electrical and Computer Engineering Microelectronics Research CenterUniversity of TexasAustinTX 78758USA Coordinated Science Laboratory University of Illinois Urbana-ChampaignUrbanaIL 61801USA

On-chip manipulation of charged particles using electrophoresis or electroosmosis is widely used for many applications,including optofluidic sensing,bioanalysis and macromolecular data *** hereby demonstrate a technique for the capture,localization,and release of charged particles and DNA molecules in an aqueous solution using tubular structures enabled by a strain-induced self-rolled-up nanomembrane(S-RuM)***-in 3D electrodes that are embedded in cylindrical S-RuM structures and biased by a constant DC voltage are used to provide a uniform electrical field inside the microtubular *** charged-particle manipulation is achieved at a bias voltage of<2-4 V,which is~3 orders of magnitude lower than the required potential in traditional DC electrophoretic ***,Poisson-Boltzmann multiphysics simulation validates the feasibility and advantage of our microtubular charge manipulation devices over planar and other 3D variations of microfluidic *** work lays the foundation for on-chip DNA manipulation for data storage applications.

关键词： electrodes cylindrical planar

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Optimal Design of Distributed Network Based on Power Quality to Minimize the Flicker of Wind Turbines

Optimal Design of Distributed Network Based on Power Quality...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Abolfazl Ghaffari Alireza Askarzadeh Roohollah Fadaeinedjad Gerry Moschopoulos Department of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran Department of Energy Management and Optimization Institute of Science and High Technology and Environmental Sciences Graduate University of Advanced Technology Kerman Iran Department of Electrical and Computer Engineering Western University London Ontario Canada

The use of wind energy as an energy resource in distribution networks is increasing. A disadvantage to using wind energy, however, is the emission of flicker in an electrical distribution network (EDN), which may adversely affect power quality during system operation. An effective way to improve power quality is to include the allocation of wind turbines (WTs) in the planning phase. The location and size of WTs can significantly improve the network power quality and electrical performance in an EDN. This paper considers modeling for flicker emission by using a mixed integer non-linear programming (MINLP) model to determine the optimal location and size of WTs. The optimal design of the network associated with WTs generation profile patterns and the variation of load demand during the planning horizon 24-h is also determined. The proposed model is implemented in GAMS and tested on a standard IEEE 33-bus system.

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A Bayesian approach to online planning 24

A Bayesian approach to online planning

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Proceedings of the 41st International Conference on Machine Learning

作者： Nir Greshler David Ben Eli Carmel Rabinovitz Gabi Guetta Liran Gispan Guy Zohar Aviv Tamar General Motors Advanced Technical Center Israel Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa Israel

The combination of Monte Carlo tree search and neural networks has revolutionized online planning. As neural network approximations are often imperfect, we ask whether uncertainty estimates about the network outputs could be used to improve planning. We develop a Bayesian planning approach that facilitates such uncertainty quantification, inspired by classical ideas from the meta-reasoning literature. We propose a Thompson sampling based algorithm for searching the tree of possible actions, for which we prove the first (to our knowledge) finite time Bayesian regret bound, and propose an efficient implementation for a restricted family of posterior distributions. In addition we propose a variant of the Bayes-UCB method applied to trees. Empirically, we demonstrate that on the ProcGen Maze and Leaper environments, when the uncertainty estimates are accurate but the neural network output is inaccurate, our Bayesian approach searches the tree much more effectively. In addition, we investigate whether popular uncertainty estimation methods are accurate enough to yield significant gains in planning. Our code is available at: https://***/nirgreshler/bayesian-online-planning.

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人工智能在化学逆合成中的应用

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engineering 2023年第6期25卷 32-50,M0003页

作者： Yinjie Jiang Yemin Yu Ming Kong Yu Mei Luotian Yuan Zhengxing Huang Kun Kuang Zhihua Wang Huaxiu Yao James Zou Connor W.Coley Ying Wei College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Department of Computer Science City University of Hong KongHong Kong 999077China Shanghai Institute for Advanced Study Zhejiang UniversityShanghai 201203China Shanghai Artificial Intelligence Laboratory Shanghai 201203China Department of Computer Science Stanford UniversityStanfordCA 94305–2004USA Department of Chemical Engineering&Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of TechnologyCambridgeMA 02139USA

近年来,人们对通过人工智能(AI)技术解决化学逆合成预测问题产生了巨大的兴趣。与化学家和基于规则的专家系统进行的逆合成预测不同,AI驱动的逆合成预测自动从现成的实验数据集中学习化学知识,以预测反应和逆合成路径。这提供了解决许... 详细信息

近年来,人们对通过人工智能(AI)技术解决化学逆合成预测问题产生了巨大的兴趣。与化学家和基于规则的专家系统进行的逆合成预测不同,AI驱动的逆合成预测自动从现成的实验数据集中学习化学知识,以预测反应和逆合成路径。这提供了解决许多传统挑战的机会,包括专业知识过于繁杂、路线的长度过大和计算成本高。本文描述了当前AI驱动的逆合成预测的概况。我们首先讨论了化学逆合成的数学定义,并回顾了这个问题中的研究挑战。然后,我们回顾相关的AI技术和最新进度,以实现逆合成预测。此外,我们提供了逆合成系统不同部分的全面分类,并调查了AI方法如何重塑每个子模块。最后,我们讨论了未来有希望的研究领域。

关键词：逆合成计算成本数学定义化学知识 AI技术基于规则的专家系统专业知识子模块

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Graphene Bridge Heterostructure Devices for Negative Differential Transconductance Circuit Applications

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Nano-Micro Letters 2023年第2期15卷 161-171页

作者： Minjong Lee Tae Wook Kim Chang Yong Park Kimoon Lee Takashi Taniguchi Kenji Watanabe Min‑gu Kim Do Kyung Hwang Young Tack Lee Department of Electrical and Computer Engineering Inha UniversityIncheon 22212Republic of Korea Department of Materials Science and Engineering The University of Texas at DallasRichardsonTX 75080USA Center for Opto‑Electronic Materials and Devices Post‑Silicon Semiconductor InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Physics Kunsan National UniversityGunsan 54150Republic of Korea Advanced Materials Laboratory National Institute for Materials ScienceTsukuba 305‑0044Japan Department of Information and Communication Engineering Inha UniversityIncheon 22212Republic of Korea Division of Nanoscience and Technology KIST SchoolUniversity of Science and Technology(UST)Seoul 02792Republic of Korea Department of Electronic Engineering Inha UniversityIncheon 22212Republic of Korea

Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction *** this study,we demonstrate graphene(Gr)-bridge heterostructure devices consisting of laterally series-connected ambipolar semiconductor/Gr-bridge/n-type molybdenum disulfide as a channel material for field-effect transistors(FET).Unlike conventional FET operation,our Gr-bridge devices exhibit nonclassical transfer characteristics(humped transfer curve),thus possessing a negative differential *** phenomena are interpreted as the operating behavior in two series-connected FETs,and they result from the gate-tunable contact capacity of the Gr-bridge ***-value logic inverters and frequency tripler circuits are successfully demonstrated using ambipolar semiconductors with narrow-and wide-bandgap materials as more advanced circuit applications based on non-classical transfer ***,we believe that our innovative and straightforward device structure engineering will be a promising technique for future multi-functional circuit applications of 2D nanoelectronics.

关键词： Graphene bridge Heterostructure device Non-classical transfer characteristics Multi-value logic inverter Frequency tripler

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A Logical Design of Internet of Things Assisted Digital Health Record Monitoring System using Deep Learning Principles

A Logical Design of Internet of Things Assisted Digital Heal...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Gayathri, S. Vijayanandh Thirumoorthy, P. Valarmathy, A.S. Pandi, V. Samuthira Shobana, D. R.M.K. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Dhanalakshmi College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350308167

Intelligent systems for monitoring health have been made possible by the IoT and the mental/physical health of an individual may be monitored using such a system. Determinants of numerous diseases, both physical and mental include tension, worry and high blood pressure. Problems associated with aging including anxiety, depression, stress and pressure require specialized care in this context. The prompt identification of health issues by monitoring of nervousness tension, stress, and heart rate is a key to avoiding irreversible harm. This will improve health outcomes;lessen the burden on caregivers, and save money. Find innovative technological answers for continuous monitoring of stress, anxiety, and blood pressure through the use of covert embedded sensors as well as deep learning methods. As a result of the suggested smart health monitoring system, health monitoring services may now be provided quickly, cheaply, and reliably from remote places, whereas this was not previously achievable with conventional health care systems. The implementation of a blockchain-based framework has increased the safety and privacy of patients' private information and reduced the likelihood of it being misused. Using Deep Learning and related technologies to evaluate health data for numerous goals has aided in the achievement of both preventative healthcare and fatality control. This has allowed for the early diagnosis of chronic illnesses, which was previously impossible. The combination of computing resources in the cloud and electronic storage has been introduced in order to render operations cheaper and instantaneously. This research provides a comprehensive overview of the state of health monitoring technology, including the most up-to-date developments and the most pressing problems. © 2023 IEEE.

关键词： Deep Learning Health Record Monitoring Healthcare Internet of Things IoT Sensors

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