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Resilience Week (RWS)

作者： Mukesh Gautam Di Wu Mohammed Ben-Idris Electricity Infrastructure & Buildings Division Pacific Northwest National Laboratory Richland Washington USA Department of Electrical and Computer Engineering Michigan State University East Lansing Michigan USA

ISBN: (数字)9798350388985

ISBN: (纸本)9798350388992

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

关键词： Economics Renewable energy sources Technological innovation Reviews Scalability Security Stakeholders Resource management Energy storage Resilience

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Optimal Actuator Attacks on Autonomous Vehicles Using Reinforcement Learning

arXiv

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arXiv 2025年

作者： Wang, Pengyu Li, Jialu Shi, Ling Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

With the increasing prevalence of autonomous vehicles (AVs), their vulnerability to various types of attacks has grown, presenting significant security challenges. In this paper, we propose a reinforcement learning (RL)-based approach for designing optimal stealthy integrity attacks on AV actuators. We also analyze the limitations of state-of-the-art RL-based secure controllers developed to counter such attacks. Through extensive simulation experiments, we demonstrate the effectiveness and efficiency of our proposed method. Copyright © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Integrated self-referencing single shot digital holographic microscope and optical tweezer

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Light(Advanced Manufacturing) 2022年第3期3卷 205-218页

作者： Subhash Utadiya Sachin Joshi Nimit Patel Chetna Patel Mugdha Joglekar Vani Cahhniwal Timothy O’Connor Bahram Javidi Arun Anand Optics Laboratory Applied Physics DepartmentFaculty of Technology and EngineeringThe Maharaja Sayajirao University of BarodaVadodara 390001India Department of Electrical and Computer Engineering University of ConnecticutStorrsCT06269-4157USA Institute of Interdisciplinary Studies The Maharaja Sayajirao University of BarodaVadodaraIndia

Digital holographic microscopy is a single-shot technique for quantitative phase imaging of samples,yielding thickness profiles of phase *** provides sample features based on their morphology,leading to their classification and ***,observing samples,especially cells,in fluids using holographic microscopes is difficult without immobilizing the *** tweezers can be used for sample immobilization in *** present manuscript provides an overview of our ongoing work on the development of a compact,low-cost microscopy system for digital holographic imaging of optically trapped *** of digital holographic microscopy system with tweezers is realized by using the optical pickup unit extracted from DVD burners to trap microsamples,which are then holographically imaged using a highly compact self-referencing interferometer along with a low-cost,in-house developed quadrant photodiode,providing morphological and spectral information of trapped *** developed integrated module was tested using polystyrene microspheres as well as human *** investigated system offers a multitude of sample features,including physical and mechanical parameters and corner frequency information of the *** features were used for sample *** proposed technique has vast potential in opening up new avenues for low-cost,digital holographic imaging and analysis of immobilized samples in fluids and their classification.

关键词： Digital holographic microscopy Optical tweezers Red blood cells Quantitative phase imaging

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A Knowledge Acquisition Method for Consumer Electronics Based on Triadic Hesitant Fuzzy Concept

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IEEE Transactions on Consumer Electronics 2025年

作者： Xin, Xianwei Zhao, Ye Wang, Chenyang Xu, Jiucheng Taleb, Tarik Henan Normal University School of Computer and Information Engineering Xinxiang453007 China Key Laboratory of Computational Intelligence and Chinese Information Processing Ministry of Education Taiyuan237016 China Computer and Software Engineering School of College of Shenzhen University Guangdong Shenzhen518060 China Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province Henan Province 453007 China Ruhr University Bochum Faculty of Electrical Engineering and Information Technology Bochum44801 Germany

With the growing intelligence and personalization of consumer electronic products, extracting effective information has become a key challenge in Consumer Electronics (CE). Triadic Concept Analysis (TCA), an important extension of Formal Concept Analysis (FCA), is widely applied but often struggles to handle the hesitant fuzzy characteristics in real-world data. To address this gap, we propose a Triadic Hesitant Fuzzy Concept (THFC) model. First, we introduce the concept of a triadic hesitant fuzzy background, integrating the fuzzy and hesitant nature of data in the CE environment. We propose a knowledge acquisition method based on THFC, which constructs a multi-granularity knowledge space with a dynamic adjustment mechanism. This method captures subtle distinctions between different types of information and their hierarchical structures in the context of CE, offering significant support for knowledge discovery and decision-making in complex environments. Building on this, we design a variable-precision hybrid similarity measurement (VP-HSM) method to extract core, adjunct, and edge concepts, thus providing more precise and structured knowledge for data analysis and decision-making in CE. Experimental results on publicly available datasets show that the proposed method significantly improves classification accuracy and stability, effectively handling hesitant fuzzy data and improving the accuracy of concept extraction. © 1975-2011 IEEE.

关键词： Data accuracy

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Solar Irradiance Forecasting using Gaussian Process Regression Model

Solar Irradiance Forecasting using Gaussian Process Regressi...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Nesrine Omri Jannet Jamii Majdi Mansouri Mohamed Faouzi Mimouni The Laboratory of Automatic Electrical System and Environment (LAS2E) National Engineering School of Monastir Tunisia Electrical and Computer Engineering Department Texas A&M University at Qatar Electrical Engineering Department National Engineering School at Monastir (ENIM) Tunisia

Photovoltaic power generation presents a significant problem for power system security due to their stochastic nature. Thus, photovoltaic energy forecasting plays a key role in addressing the challenges of grid stability. Then, accurate PV energy forecasting improve the output power and therefore reduce the need for reserve energy to balance energy. Also, it improves dispatch and planning power. In this paper, we study a short term forecasting of PV power using a Gaussian Process Regression (GPR) model. The meteorological conditions such as temperature is used as input, while solar irradiance, is used as output for GPR *** data set are illustrated from data NOAA'S Surface Radiation (SURFRAD) Network at Bondville station, located in the USA. A comparative study with other machine learning techniques is developed in terms of calculation time (CT), RMSE, MAE, and R 2 .

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A Website Fingerprinting Attack Based on Parameter Prediction Model for Conceptual Drift

A Website Fingerprinting Attack Based on Parameter Predictio...

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Software System and Information Processing (ICSSIP), IEEE International Conference on

作者： Jian Cui Taizhong Xu Li Zhao Shuai Han College of Computer Science and Technology Harbin Engineering University Harbin China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China School of Electrical and Information Engineering Yunnan Minzu University Yunnan Key Laboratory of Unmanned Autonomous System Kunming China

ISBN: (数字)9798331506131

ISBN: (纸本)9798331506148

Website content updates and changes in the network environment can lead to concept drift, significantly impacting the performance of existing website fingerprinting methods. Recent research has focused on transfer learning-based approaches for concept drift adaptation to address this issue with limited samples. These methods involve pre-training a robust feature extractor and fine-tuning the classifier with a few samples. However, the effectiveness of these classifiers is highly dependent on the distributional gap between pre-training and fine-tuning datasets. As the divergence increases, more fine-tuning data is required to maintain classification performance. Consequently, existing methods struggle to achieve effective website identification tasks under severe concept drift with limited tuning data. To overcome these limitations, we propose a model parameter prediction approach, which adapts to new domains from data and model perspectives to enhance website identification performance. The proposed method predicts future model parameters to mitigate the effects of distributional changes, effectively adapting to evolving network environments. Experimental results demonstrate that our approach achieves significant improvements in accuracy, particularly under scenarios with limited tuning data and substantial concept drift.

关键词： Adaptation models Accuracy Concept drift Predictive models Fingerprint recognition Feature extraction Data models Robustness Long short term memory Tuning

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DDPS: Dynamic Differential Pricing-based Edge Offloading System with Energy Harvesting Devices

arXiv

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arXiv 2024年

作者： Xue, Hai Xia, Yun Xiong, Neal N. Zhang, Di Pei, Songwen School of Optical- Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States School of Electrical and Information Engineering Zhengzhou University the Henan International Joint Laboratory of Intelligent Health Information System the National Telemedicine Center National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China

Mobile edge computing (MEC) paves the way to alleviate the burden of energy and computation of mobile users (MUs) by offloading tasks to the network edge. To enhance the MEC server utilization by optimizing its resource allocation, a well-designed pricing strategy is indispensable. In this paper, we consider the edge offloading scenario with energy harvesting devices, and propose a dynamic differential pricing system (DDPS), which determines the price per unit time according to the usage of computing resources to improve the edge server utilization. Firstly, we propose an offloading decision algorithm to decide whether to conduct the offloading operation and how much data to be offloaded if conducted, the algorithm determines offloading operation by balancing the energy harvested with the energy consumed. Secondly, for the offloading case, we formulate the game between the MUs and the server as a Stackelberg game, and propose a differential pricing algorithm to determine the optimal computing resources required by MUs. Furthermore, the proposed algorithm also reallocates computing resources for delay-sensitive devices while server resources are surplus after the initial allocation, aiming to make full use of the server computing resources. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DDPS scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

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Distributed Uplink Rate Splitting Multiple Access (DU-RSMA): Principles and Performance Analysis

arXiv

引用

arXiv 2024年

作者： Tegos, Apostolos A. Xiao, Yue Tegos, Sotiris A. Karagiannidis, George K. Diamantoulakis, Panagiotis D. The Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece The Provincial Key Laboratory of Information Coding and Transmission Southwest Jiaotong University Chengdu610031 China

One of the main goals of the upcoming sixth-generation (6G) wireless networks is the ability to support higher network density, while ensuring a high quality of service for each user. In this paper, we introduce distributed uplink rate-splitting multiple access (DU-RSMA), define its basic principles, and provide insights into its advantages. Specifically, a system with two remote radio heads (RRHs) and two users is investigated. To improve the performance of the system, we consider that the RRHs can communicate through a feedback link, and thus they are able to decode the received messages either independently or with the assistance of the other RRH, since the decoded information can be shared through the feedback link. It should be noted that this scheme increases the achievable capacity region compared to the known multiple access schemes, which is also evaluated by a novel metric termed "fill factor". Both the case of adaptive transmission rates and the case of fixed transmission rates are investigated. To this end, the ergodic rate is investigated to cover the former case, while the outage probability is studied for the latter. Closed-form expressions are derived for both metrics. Finally, the analytical expressions are validated by simulation results, which explicitly show the impact of each parameter on the performance of the system, and prove that the proposed scheme outperforms the corresponding benchmarks. © 2024, CC BY.

关键词： Outages

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Open-World Semi-Supervised Learning for Node Classification

Open-World Semi-Supervised Learning for Node Classification

引用

International Conference on Data engineering

作者： Yanling Wang Jing Zhang Lingxi Zhang Lixin Liu Yuxiao Dong Cuiping Li Hong Chen Hongzhi Yin School of Information Renmin University of China Zhongguancun Laboratory Alibaba Group Department of Computer Science and Technology Tsinghua University School of Information Technology and Electrical Engineering The University of Queensland

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Open-world semi-supervised learning (Open-world SSL) for node classification, that classifies unlabeled nodes into seen classes or multiple novel classes, is a practical but under-explored problem in the graph community. As only seen classes have human labels, they are usually better learned than novel classes, and thus exhibit smaller intra-class variances within the embedding space (named as imbalance of intra-class variances between seen and novel classes). Based on empirical and theoretical analysis, we find the variance imbalance can negatively impact the model performance. Pre-trained feature encoders can alleviate this issue via producing compact representations for novel classes. However, creating general pre-trained encoders for various types of graph data has been proven to be challenging. As such, there is a demand for an effective method that does not rely on pre-trained graph encoders. In this paper, we propose an IMbalance-A ware method named OpenIMA for Open-world semi-supervised node classification, which trains the node classification model from scratch via contrastive learning with bias-reduced pseudo labels. Extensive experiments on seven popular graph benchmarks demonstrate the effectiveness of OpenIMA, and the source code has been available on GitHub 1 1 https://***/RUCKBReasoning/OpenIMA.

关键词： Analytical models Source coding Contrastive learning Semisupervised learning Benchmark testing Data engineering

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Wide field-of-view metalens: a tutorial

引用

Advanced Photonics 2023年第3期5卷 1-21页

作者： Fan Yang Mikhail YShalaginov Hung-I Lin Sensong An Anu Agarwal Hualiang Zhang Clara Rivero-Baleine Tian Gu Juejun Hu Massachusetts Institute of Technology Department of Materials Science and EngineeringCambridgeMassachusettsUnited States University of Massachusetts Lowell Department of Electrical and Computer EngineeringLowellMassachusettsUnited States Lockheed Martin Corporation OrlandoFloridaUnited States Massachusetts Institute of Technology Materials Research LaboratoryCambridgeMassachusettsUnited States

Wide field-of-view(FOV)optics are essential components in many optical systems,with applications spanning imaging,display,sensing,and beam *** refractive wide FOV optics often involve multiple stacked lenses,resulting in large size and weight as well as high *** lenses or metalenses promise a viable solution to realizing wide FOV optics without complex lens *** review the various architectures of wide FOV metalenses,elucidate their fundamental operating principles and design trade-offs,and quantitatively evaluate and contrast their imaging *** applications enabled by wide FOV metasurface optics are also discussed.

关键词： metasurface lens imaging field of view aberration

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