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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Sayrafian, Kamran Cloteaux, Brian Marbukh, Vladimir Emiyah, Christian National Institute of Standards and Technology Information Technology Laboratory GaithersburgMD United States Morgan State University Department of Electrical and Computer Engineering BaltimoreMD United States

ISBN: (纸本)9781665431620

A commonly used methodology to estimate the proximity of two individuals in an automatic exposure notification system uses the signal strength of the Bluetooth signal from their mobile phones. However, there is an underlying error in Bluetooth-based proximity detection that can result in wrong exposure decisions. A wrong decision in the exposure determination leads to two types of errors: false negatives and false positives. A false negative occurs when an exposed individual is incorrectly identified as not exposed. Similarly, a false positive occurs when a non-exposed individual is mistakenly identified as exposed. Both errors have costly implications and can ultimately determine the effectiveness of Bluetooth-based automatic exposure notification in containment of pandemics such as COVID-19. In this paper, we present a platform that allows for the analysis of the system performance under various parameters. This platform enables us to gain a better understanding on how the underlying technology error propagates through the contact tracing system. Preliminary results show the considerable impact of the Bluetooth-based proximity estimation error on false exposure determination. Alternatively, using this platform, analysis can be performed to determine the acceptable accuracy level of a proximity detection mechanism in order to have a more effective contact tracing solution. © 2022 IEEE.

关键词： Bluetooth

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Operational Reliability Evaluation of Urban Multi-Energy systems With Equivalent Energy Storage

Operational Reliability Evaluation of Urban Multi-Energy Sys...

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作者： Wang, Sheng Hui, Hongxun Ding, Yi Ye, Chengjin Zheng, Menglian University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering 999078 China State Grid Suzhou City and Energy Research Institute Co. Ltd. Suzhou215163 China Zhejiang University College of Electrical Engineering Hangzhou310027 China Zhejiang University College of Energy Engineering Hangzhou310027 China

With the coordination of multiple energies at the city level, the complexity of the urban energy system is ever-increasing. Securing the reliable operation of the urban multi-energy system (UMES) has become a challenging task. This article focuses on the operational reliability evaluation of the UMES considering the incorporation of equivalent energy storages. First, a novel concept of dynamic energy hub is proposed, as a unified tool to characterize the dynamic relationships of the operating conditions of diverse components in the UMES. Then, the temperature-controlled load (TCL) is modeled as the equivalent energy storage considering the thermal dynamics. Its operational reliabilities, as well as multiple other components, are modeled using the reliability equivalent technique to reduce the dimension of uncertainties. Moreover, a contingency management scheme of the UMES is developed in an optimal control framework considering the comfort costs of equivalent energy storages. To deal with the time-dependency of the optimal control problem, a simplified Benders decomposition procedure is devised and embedded in the Time-sequential Monte Carlo simulation to improve the computation efficiency of the reliability evaluation. Finally, a practical case of a UMES in southern China is used to validate the proposed technique. © 1972-2012 IEEE.

关键词： Reliability

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Optical-Based Relative Electric Field Measurement in Dielectric Microwave Resonators 5

Optical-Based Relative Electric Field Measurement in Dielect...

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5th IEEE Research and Applications of Photonics in Defense Conference, RAPID 2022

作者： Dev, Sukrith Anthony, Nathan Trendafilov, Simeon Allen, Monica Allen, Jeffery Munitions Directorate Eglin Air Force Base Air Force Research Laboratory United States University of Central Florida Department of Electrical and Computer Engineering Orlando United States

ISBN: (数字)9781665402231

ISBN: (纸本)9781665402231

Here we present the experimental relative electric field magnitude mapping of a high permittivity cylindrical dielectric microwave resonator mode using an external superstrate optically induced conductance (OIC) technique. The fundamental TE01δ mode is mapped and compared to finite element method simulated fields with excellent agreement. © 2022 IEEE.

关键词： Electric fields

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Prioritization of Smart Meters Based on Data Monitoring for Enhanced Grid Resilience

SSRN

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SSRN 2024年

作者： Farooq, Asma Shahid, Kamal Olsen, Rasmus Løvenstein Department of Electronic Systems Aalborg University Aalborg9220 Denmark Institute of Electrical Electronics and Computer Engineering University of the Punjab Punjab Lahore54590 Pakistan

Smart meter data enables real-time insights into energy consumption, grid performance, and load management, improving grid reliability, energy efficiency, and the integration of renewable resources. Effective communication between smart meters and the control center plays a pivotal role in enhancing grid resilience. Advance metering infrastructure (AMI) exhibits several limitations, such as communication delays, metering technology, data storage, and processing capabilities, that impede its ability to deliver real-time data with extreme precision and small time granularity. Thus, the accuracy and timeliness of data collection and analysis may be compromised, which could impact the efficiency of energy management and grid operations. This paper presents a novel method for scheduling smart meter data access that is based on the real-time assessment and analysis of the data. A quality metric known as mismatch probability is used to evaluate meter data and schedule the meters using the Hungarian algorithm. The proposed method has been tested on real data from a Danish grid. Results show enhanced information quality in the context of real-time monitoring in comparison to scheduling algorithms chosen heuristically. © 2024, The Authors. All rights reserved.

关键词： Smart meters

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50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-EDFA

50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-E...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical Communications, IPOC 2024

作者： Huang, Shuailuo Zhu, Baolong Qiao, Gang Gao, Yuyang Zuo, Mingqing Shen, Shikui Wang, Zelin He, Yongqi Chen, Zhangyuan Li, Juhao Chen, Zhangyuan Li, Juhao China Unicom Research Institute Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Fundamental Network Technology China Mobile Research Institute Beijing China Pengcheng National Laboratory Shenzhen China

ISBN: (纸本)9798350379266

关键词： Pulse amplitude modulation

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Hypercomplex Generative Adversarial Networks for Lightweight Semantic Labeling 3rd

Hypercomplex Generative Adversarial Networks for Lightweigh...

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3rd International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022

作者： Sfikas, Giorgos Retsinas, George Gatos, Basilis Nikou, Christophoros Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research "Demokritos" Athens Greece School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Surveying and Geoinformatics Engineering University of West Attica Athens Greece Department of Computer Science and Engineering University of Ioannina Ioannina Greece

ISBN: (纸本)9783031090363

Following recent advances on parameterized hypercomplex multiplication [21], we explore the usefulness of hypercomplex convolutions and deconvolutions in a document labeling task. We show that the proposed Hypercomplex Generative Adversarial Networks achieve excellent results while requiring significantly less independent parameters than real-valued models. © 2022, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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NARCE: A Mamba-Based Neural Algorithmic Reasoner Framework for Online Complex Event Detection

arXiv

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arXiv 2025年

作者： Han, Liying Dong, Gaofeng Ouyang, Xiaomin Kaplan, Lance Cerutti, Federico Srivastava, Mani Department of Electrical and Computer Engineering University of California Los Angeles United States Department of Computer Science and Engineering Hong Kong University of Science and Technology China US Army DEVCOM Army Research Laboratory United States Department of Information Engineering University of Brescia Italy Amazon United States

Current machine learning models excel in short-span perception tasks but struggle to derive high-level insights from long-term observation, a capability central to understanding complex events (CEs). CEs, defined as sequences of short-term atomic events (AEs) governed by spatiotemporal rules, are challenging to detect online due to the need to extract meaningful patterns from long and noisy sensor data while ignoring irrelevant events. We hypothesize that state-based methods are well-suited for CE detection, as they capture event progression through state transitions without requiring long-term memory. Baseline experiments validate this, demonstrating that the state-space model Mamba outperforms existing architectures. However, Mamba’s reliance on extensive labeled data, which are difficult to obtain, motivates our second hypothesis: decoupling CE rule learning from noisy sensor data can reduce data requirements. To address this, we propose NARCE, a framework that combines Neural Algorithmic Reasoning (NAR) to split the task into two components: (i) learning CE rules independently of sensor data using synthetic concept traces generated by LLMs and (ii) mapping sensor inputs to these rules via an adapter. Our results show that NARCE outperforms baselines in accuracy, generalization to unseen and longer sensor data, and data efficiency, significantly reducing annotation costs while advancing robust CE detection. © 2025, CC BY.

关键词： Labeled data

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Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication

arXiv

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arXiv 2023年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. The Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA02215 United States Hong Kong The Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus The Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland The Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used;the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples. © 2023, CC BY.

关键词： Directed graphs

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Adjustable Current Limiting Function with a Monolithically Integrated SiC Circuit Breaker Device

Adjustable Current Limiting Function with a Monolithically I...

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作者： Takamori, Taro Wada, Keiji Boettcher, Norman Erlbacher, Tobias Saito, Wataru Nishizawa, Shin-Ichi Tokyo Metropolitan University Department of Electrical Engineering and Computer Science Tokyo192-0397 Japan Fraunhofer Institute for Integrated Systems and Device Technology IISB Erlangen91058 Germany Kyushu University Research Institute for Applied Mechanics Fukuoka816-8580 Japan

This article proposes a current limiting function for a self-sensing and self-triggering monolithically integrated SiC circuit breaker device. The proposed function provides the device not only with a fast-response current breaking operation but also with the current limiting operation, including supplying a constant current to the load and preventing the detection of inrush currents. This function is suitable for replacing mechanical conductors in initial charging circuits within rectifiers and safety equipment in case of overcurrent phenomena. The proposed method achieves certain constant currents through a simple variation of the gate-drive circuit with the adjustable parameters of an additional MOSFET. The mechanism of the current limiting function is verified using TCAD simulations based on certain conditions. Consequently, experimental results verified that the circuit breaker device with the current limiting function reduces the inrush current by up to 76.9% using a 500 VDC distribution circuit system. © 1972-2012 IEEE.

关键词： Silicon carbide

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A TMA-Seq2seq Network for Multi-Factor Time Series Sea Surface Temperature Prediction

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computers, Materials & Continua 2022年第10期73卷 51-67页

作者： Qi He Wenlong Li Zengzhou Hao Guohua Liu Dongmei Huang Wei Song Huifang Xu Fayez Alqahtani Jeong-Uk Kim Department of Information Technology Shanghai Ocean UniversityShanghai201306China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou310012China College of Computer Dong Hua UniversityShanghai200051China College of Information Technology Shanghai Jian Qiao UniversityShanghai201306China Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh 12372Saudi Arabia Department of Electrical Engineering Sangmyung UniversitySouth KoreaKorea

Sea surface temperature (SST) is closely related to global climatechange, ocean ecosystem, and ocean disaster. Accurate prediction of SST isan urgent and challenging task. With a vast amount of ocean monitoring dataare continually collected, data-driven methods for SST time-series predictionshow promising results. However, they are limited by neglecting complexinteractions between SST and other ocean environmental factors, such as airtemperature and wind speed. This paper uses multi-factor time series SSTdata to propose a sequence-to-sequence network with two-module attention(TMA-Seq2seq) for long-term time series SST prediction. Specifically, TMASeq2seq is an LSTM-based encoder-decoder architecture facilitated by factorand temporal-attention modules and the input of multi-factor time series. Ittakes six-factor time series as the input, namely air temperature, air pressure,wind speed, wind direction, SST, and SST anomaly (SSTA). A factor attentionmodule is first designed to adaptively learn the effect of different factors onSST, followed by an encoder to extract factor-attention weighted features asfeature representations. And then, a temporal attention module is designedto adaptively select the hidden states of the encoder across all time steps tolearn more robust temporal relationships. The decoder follows the temporalattention module to decode the feature vector concatenated from the weightedfeatures and original input feature. Finally, we use a fully-connect layer tomap the feature into prediction results. With the two attention modules, ourmodel effectively improves the prediction accuracy of SST since it can notonly extract relevant factor features but also boost the long-term *** experiments on the datasets of China Coastal Sites (CCS) demonstrate that our proposed model outperforms other methods, reaching 98.29%in prediction accuracy (PACC) and 0.34 in root mean square error (RMSE).Moreover, SST prediction experiments in China’s East, South,

关键词： Sea surface temperature multi-factor attention long short-term memory

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