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Spatiotemporal pattern detection, generation, and computation with circuits

Neural Computing and Applications 2025年 1-17页

作者： Ivans, Robert C. Cantley, Kurtis D. Idaho National Laboratory 1955 Fremont Avenue Idaho FallsID83415 United States Department of Electrical and Computer Engineering Boise State University 1910 University Drive BoiseID83725 United States

Implementations of neurons, delays, and synapse circuits are presented with simulations. These neural elements are used to create two small spiking neural networks, the Rate-Window and Order-Biased clusters, which are capable of detecting simple two-spike spatiotemporal patterns. A simple pattern detecting network (SPDN) is created by combining the Rate-Window and Order-Biased clusters, where clusters are small spiking neural networks, and its simple pattern detection ability is demonstrated in simulation. The SPDN is used to implement a complex pattern detecting network (CPDN) and its complex pattern detection ability is demonstrated in simulation. Methods for generating arbitrary spatiotemporal patterns are presented. The CPDN and spatiotemporal pattern generation methods are then used to implement a novel spatiotemporal computing paradigm based on detecting and responding to spatiotemporal symbols. A simulation of a spatiotemporal half adder is presented to demonstrate the computing paradigm. © The Author(s) 2025.

关键词： Time delay

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Enhancing WRSN Sustainability through On-demand Directional Wireless Charging with Multiple Green-powered Mobile Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 18019-18030页

作者： Ma, Xiongbo Liu, Xilong Ansari, Nirwan Ding, Jun The School of Information Science and Engineering Yunnan University Yunnan Kunming650500 China The Advanced Networking Laboratory Helen & John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Current research on scheduling mobile charging vehicles (MCVs) generally focuses on periodic and omnidirectional charging of sensor nodes (SNs). However, this approach leads to significant energy wastage, especially when relying on fossil energy sources. In this work, we propose to schedule multiple green energy-powered MCVs equipped with directional antennas to efficiently charge SNs. We first develop an on-demand and directional charging model based on far-field wireless charging. Then, we formulate the SN survival maximization problem to efficiently prolong the lifetime of wireless rechargeable sensor networks (WRSNs). Given the NP-hard nature of this optimization problem, we develop the three-Step directIonal wireless charGiNg (SIGN) algorithm to efficiently solve this problem. SIGN strategically determines the MCVs’ anchor points (APs), traveling paths and wireless energy emitting directions. Finally, we conduct extensive simulation experiments to validate the superiority of our proposed algorithm in optimizing energy usage and prolonging network lifetime. © 2014 IEEE.

关键词： Wireless charging

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Service-Oriented Resource Allocation and Task Scheduling for Wi-Fi and Bluetooth Coexistence in Smart Home IoT Systems

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ACM Transactions on Internet of Things 2025年第2期6卷 1-24页

作者： Zhao, Di Niu, Tianxu Song, Bin Du, Xiaojiang Xidian University State Key Laboratory of Integrated Services Network Xi'an China Xidian University Hangzhou Institute of Technology Hangzhou China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken United States

In IoT-enabled smart home scenarios, heterogeneous communication devices such as Bluetooth (BT) and Wi-Fi are widely used in applications such as home automation, remote monitoring, and intelligent device interconnection. However, in such a multi-device coexistence environment, efficiently allocating limited time-frequency resources to mitigate communication interference and enhance system performance has become a critical challenge. To address these issues, this article proposes a comprehensive solution that integrates master selection, resource allocation, and task scheduling to optimize resource utilization and service quality in smart home IoT systems. For device management, we propose a hierarchical entropy weight method (HEWM), considering factors such as device parameters, sensing capabilities, communication performance, and device interoperability. This method ensures efficient and stable selection of the primary device, optimizing network topology and communication efficiency. For resource allocation, we introduce a proximal policy optimization (PPO) algorithm that dynamically adjusts time-frequency resource allocation based on the varying device usage, network load, and communication condition. This adaptive strategy reduces interference between devices and improves system throughput. For task scheduling, we develop a task urgency-based queueing (TUQ) mechanism that prioritizes tasks based on urgency. A task preemption mechanism ensures that high-urgency tasks are processed with minimal delay, enhancing scheduling efficiency and service responsiveness. Simulation results show that the proposed approach significantly outperforms traditional methods in smart home IoT scenarios, achieving higher primary device scores, a 3%-22% improvement in system throughput, and a 5%-36% reduction in task delay. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wi-Fi

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24.4 THz·V fT×BV figure-of-merit AlN/GaN/AlN MISHEMTs with thin AlN buffer layer

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Science China(Information Sciences) 2025年第3期68卷 403-404页

作者： Chaoqun ZHANG Hong ZHOU Sami ALGHAMDI Kun ZHANG Zhihong LIU Yue HAO Jingcheng ZHANG State Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology Xidian University Guangzhou Wide Bandgap Semiconductor Innovation Center Guangzhou Institute of TechnologyXidian University Electrical and Computer Engineering Department King Abdulaziz University

Gallium nitride-based high-electron-mobility-transistors(HEMTs) have gained widespread interest and become primary candidates for next-generation high-frequency and high-power RF electronics, due to their wide bandgap,high breakdown field, and strong polarization-induced high-density 2-dimensional electron gas(2DEG) at the heterojunction interface.

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Edge-Driven Industrial Computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

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A Relative-Error-Dependent TOD Protocol for Cyber-Physical Systems under an Event-Triggered Communication

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 318-328页

作者： Yang, Hongchenyu Peng, Chen Tian, Engang Shanghai University School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Power Station Automation Technology Shanghai200444 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China

To deal with different data magnitudes or measurement units of different system nodes, a novel relative-error-dependent try-once-discard (RED-TOD) communication protocol with event-triggered detectors is proposed to improve the accuracy and reliability of node selection for band-limited cyber-physical systems. With the combined effect of the absolute error and the relative error, a novel node activation condition is proposed to comprehensively reflect and fairly compare node transmission requirements. Under such a stricter scheduling rule, the node selection is more accurate as required and the available communication bandwidth is utilized with higher efficiency. Moreover, periodic sampling module and event-triggered detectors are placed before RED-TOD scheduling scheme to deal with redundancy and inaccurate transmissions of the existing variable sampling scheme. Taking the proposed scheduling scheme and non-small network-induced delay into account, an impulsive closed-loop system model is well established. Sufficient criteria for input-to-state stabilization are derived by employing the Lyapunov-Krasovskii functional approach. A searching algorithm is also presented to co-design optimized scheduler parameters and controller gains. Furthermore, to avoid continuous calculations, the next transmission instant and the dormant period of the event-triggered detector are predicted according to the present information carried by each node. Finally, an illustrative example is employed to demonstrate the effectiveness and superiority of the proposed scheduling method. © 2023 IEEE.

关键词： Feedback control

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Multimodal Pain Assessment Βased on Physiological Biosignals: The Impact of Demographic Factors on Perception and Sensitivity 11

Multimodal Pain Assessment Βased on Physiological Biosignal...

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11th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Pavlidou, Elisavet Tsiknakis, Manolis Department of Electrical and Computer Engineering Hellenic Mediterranean University Estavromenos Heraklion71410 Greece Computational BioMedicine Laboratory Institute of Computer Science Foundation for Research & Technology-Hellas Vassilika Vouton Heraklion70013 Greece

ISBN: (纸本)9789897587436

Pain is a multidimensional and highly personalized sensation that affects individuals’ physical and emotional state. Visual analog scales, numeric rate indicators, and various questionnaires, all relying on patient-reported outcome measurements, are considered the "gold" standard methods for assessing the severity of pain. Nevertheless, self-report tools require cognitive, linguistic, and social abilities, which may manifest variations in certain populations such as neonates, individuals with intellectual disabilities, and those affected by dementia. The purpose of this study is to automate the process through multimodal physiological-data-driven machine-learning models in order to gain deeper insights into pain sensation. We developed a pipeline using electrocardiogram (ECG), galvanic skin response (GSR), and electromyogram (EMG), along with demographic information from the BioVid dataset. The Pan & Tompkins algorithm was applied for ECG signal processing, while statistical analysis was used for feature extraction across all signals. Our study achieved 82.83% accuracy in the SVM classification task of baseline (BL) vs the highest level of pain (PA4) for females aged 20-35. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Sensory perception

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Bi-Directional MS Lesion Filling and Synthesis Using Denoising Diffusion Implicit Model-based Lesion Repainting

Bi-Directional MS Lesion Filling and Synthesis Using Denoisi...

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Medical Imaging 2025: Image Processing

作者： Zhang, Jinwei Zuo, Lianrui Liu, Yihao Remedios, Samuel Landman, Bennett A. Prince, Jerry L. Carass, Aaron Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States

ISBN: (纸本)9781510685901

Automatic magnetic resonance (MR) image processing pipelines are widely used to study people with multiple sclerosis (PwMS), encompassing tasks such as lesion segmentation and brain parcellation. However, the presence of lesion often complicates these analyses, particularly in brain parcellation. Lesion filling is commonly used to mitigate this issue, but existing lesion filling algorithms often fall short in accurately reconstructing realistic lesion-free images, which are vital for consistent downstream analysis. Additionally, the performance of lesion segmentation algorithms is often limited by insufficient data with lesion delineations as the training labels. In this paper, we propose a novel approach leveraging Denoising Diffusion Implicit Models (DDIMs) for both MS lesion filling and synthesis based on image inpainting. Our modified DDIM architecture, once trained, enables both MS lesion filing and synthesis of lesioned tissues. Specifically, it can generate lesion-free T1-weighted or FLAIR images from those containing lesions;Or it can add lesions to T1-weighted or FLAIR images of healthy subjects. The former is essential for downstream analyses that require lesion-free images, while the latter is valuable for augmenting training datasets for lesion segmentation tasks. We validate our approach through initial experiments in this paper and demonstrate promising results in both lesion filling and synthesis, paving the way for future work. © 2025 SPIE.

关键词： Image segmentation

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Empowering Internet of Underwater Things: An Integrated Simulator for Underwater Magneto-Coupled Wireless Sensor Networks

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IEEE Internet of Things Magazine 2025年第1期8卷 109-114页

作者： Songzuo, Liu Ullah, Irfan Muzzammil, Muhammad Ahmed, Niaz Wahid, Abdul Zhen, Shao Ministry of Industry and Information Technology Key Laboratory of Marine Information China College of Underwater Acoustic Engineering Harbin Engineering University China Sanya Nanhai Innovation and Development Base of Harbin Engineering University China FAST National University of Computer and Emerging Sciences Department of Electrical Engineering Islamabad Campus Pakistan

This research paper presents an integration of finite element method (FEM) based models into MATLAB for developing an end-to-end magneto-coupled (MC) communication system tailored for Internet of Underwater Things (IoUT)-based applications. Magneto-coupled communication has emerged as a promising solution for extreme environments like underwater where conventional wireless acoustic communication poses significant challenges. The article exploits the strengths of two software tools: MATLAB and COMSOL Multiphysics, to seamlessly integrate communication protocols with theoretical insights into magnetic channels. The article also demonstrates the development and evaluation of an end-to-end communication system with both simulation and experimental setup. We believe that this integrated approach is highly effective in achieving reliable communication performance in underwater scenarios, thereby advancing the capabilities of IoUT for various real-world applications. © 2025 IEEE.

关键词： MATLAB

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Resilient Operation of DC Standalone Microgrids: Experimental Validation of Hybrid RNN-PI Control for Pulse Load Management

Resilient Operation of DC Standalone Microgrids: Experimenta...

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2025 IEEE Green Technologies Conference, GreenTech 2025

作者： Aghmadi, Ahmed Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798331520182

Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems. This research describes a new hybrid control technique to improve DC microgrid operations' efficiency and resiliency, especially when handling critical loads. This research presents a hybrid closed-loop control technique that uses Recurrent Neural Networks (RNNs) and Proportional-Integral (PI) controllers to address the complex issues of dynamic load situations and transient disturbances. The RNN evaluates voltage errors to generate accurate reference currents, which the PI controllers then adjust to improve the performance of the bidirectional converter. Unlike standard PI-PI controls, our hybrid approach is particularly effective at regulating pulsed power loads (PPLs) and enhancing system response to transitory situations. The experimental results show that the RNN-PI control scheme significantly improves voltage regulation and transient responsiveness, exceeding conventional performance and resilience techniques. This approach provides a convincing solution for enhancing microgrid systems' stability and efficiency in various real-world applications. © 2025 IEEE.

关键词： Electric load distribution

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