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IEEE General Meeting Power& Energy Society

作者： Mary Peterson Sarangan Rajendran Al Tamimi Charles Yokley Nirasha Bataduvaarachchi Demy Alexander Olivia O’Reilly Adithya Melagoda Arun-Kaarthick Manoharan Visvakumar Aravinthan Electrical & Computer Engineering Wichita State University Wichita KS USA Transmission Planning & Policy Sunflower Electric Power Corporation Wichita KS USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Increasing investment in renewable resources is raising important questions about how to equitably share the costs and benefits of such investments. It is essential for utilities and communities to evaluate how their renewables investments impact customers, including energy cost changes and grid adequacy support. For shared solar investments, this work develops an equity index that incorporates energy cost increases and resulting grid support during scarcity scenarios. A solar investment is modeled for two Midwestern manufacturing towns at different income levels. Using the developed metric, it is determined that energy cost increases from a solar investment may inequitably impact lower-income households, but that the investment results in improved grid support.

关键词： Measurement Renewable energy sources Costs Manufacturing Solar system Indexes Investment

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Intelligent Participation of Electric Vehicles in Demand Response Programs

Intelligent Participation of Electric Vehicles in Demand Res...

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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Cindy P. Guzmán Alexios Lekidis Panagiotis Pediaditis Pedro MS Carvalho Hugo Morais INESC-ID Instituto Superior Técnico-IST Universidade de Lisboa Lisboa Portugal Public Power Corporation S.A. Athens Greece School of Electrical and Computer Engineering National Technical University of Athens

Demand Response (DR) has been proposed and implemented in recent years to enable the participation of active consumers in energy management. However, existing programs do not consider the characteristics and opportunities introduced by electric vehicles (EVs). EVs have more flexibility than traditional loads and can be used as battery energy storage systems if the vehicle-to-grid capability is available. The main contribution of this paper is the analysis of the EV user's point of view concerning different DR programs (implicit and explicit) as well as the EVs management considering different strategies. One of the most interesting strategies that have been proposed and tested is opportunity cost optimization, where the expected prices of the next days are considered. Some of the results show that DR programs with less cost are interesting for the users since also minimise the EV charging during the DR time operation. On the other hand, realtime pricing program is not interesting for the users since its performance is highly dependent on the market price.

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Research on the Application Risk of computer Network Security Technology

Research on the Application Risk of Computer Network Securit...

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Networking, Informatics and Computing (ICNETIC), International Conference on

作者： Bingqian Guo Wei Zhao Peicheng Chen Changsheng Zhang Zhaodong Sun Wenbin Feng SWJTU-Leeds Joint School Southwest Jiaotong University Chengdu China School of Public Administration Huazhong Agricultural University Wulanchabu China School of Energy and Power Engineering Xi'an Jiaotong University Xi'an China School of Petroleum Engineering and Environmental Engineering Yan’an University Yan’an China School of Physics and Physical Engineering Qufu Normal University Qufu China School of Electrical and Computer Engineering Nanfang College of Guangzhou Guangzhou China

In the new era, computer network security issues have attracted more and more attention. How to use the latest technology to strengthen the network operating environment and prevent data information leakage has become the focus of network security management. This paper studies the computer network security technology in the era of big data. First, it is proposed that network data has the characteristics of high security factor, fast computing efficiency, and resource sharing. Secondly, it analyzes the security risks of computer networks to clarify the existing virus intrusion risks and network security. Vulnerabilities and operating system risks are different types. Finally, it focuses on the realization path of computer network security technology, and introduces the application points of firewall technology, data encryption technology and PKI technology.

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PAL: Prompting Analytic Learning with Missing Modality for Multi-Modal Class-Incremental Learning

arXiv

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arXiv 2025年

作者： Yue, Xianghu Chen, Yiming Zhang, Xueyi Gao, Xiaoxue Feng, Mengling Lao, Mingrui Zhuang, Huiping Li, Haizhou Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China Institute for Infocomm Research A*STAR 138632 Singapore Saw Swee Hock School of Public Health National University of Singapore 117583 Singapore Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangdong Guangzhou510006 China Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen518172 China Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore

Multi-modal class-incremental learning (MMCIL) seeks to leverage multi-modal data, such as audio-visual and image-text pairs, thereby enabling models to learn continuously across a sequence of tasks while mitigating forgetting. While existing studies primarily focus on the integration and utilization of multi-modal information for MMCIL, a critical challenge remains: the issue of missing modalities during incremental learning phases. This oversight can exacerbate severe forgetting and significantly impair model performance. To bridge this gap, we propose PAL, a novel exemplar-free framework tailored to MMCIL under missing-modality scenarios. Concretely, we devise modality-specific prompts to compensate for missing information, facilitating the model to maintain a holistic representation of the data. On this foundation, we reformulate the MMCIL problem into a Recursive Least-Squares task, delivering an analytical linear solution. Building upon these, PAL not only alleviates the inherent under-fitting limitation in analytic learning but also preserves the holistic representation of missing-modality data, achieving superior performance with less forgetting across various multi-modal incremental scenarios. Extensive experiments demonstrate that PAL significantly outperforms competitive methods across various datasets, including UPMC-Food101 and N24News, showcasing its robustness towards modality absence and its anti-forgetting ability to maintain high incremental accuracy. © 2025, CC BY.

关键词： Contrastive Learning

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Socially Cognizant Robotics for a Technology Enhanced Society

arXiv

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arXiv 2023年

作者： Dana, Kristin J. Andrews, Clinton Bekris, Kostas Feldman, Jacob Stone, Matthew Hemmer, Pernille Mazzeo, Aaron Salzman, Hal Yi, Jingang Rutgers University United States Electrical and Computer Engineering Dept Rutgers University United States Bloustein School of Planning and Policy Rutgers University United States Computer Science Dept Rutgers University United States Psychology Dept Rutgers University United States

Emerging applications of robotics, and concerns about their impact, require the research community to put human-centric objectives front-and-center. To meet this challenge, we advocate an interdisciplinary approach, socially cognizant robotics, which synthesizes technical and social science methods. We argue that this approach follows from the need to empower stakeholder participation (from synchronous human feedback to asynchronous societal assessment) in shaping AI-driven robot behavior at all levels, and leads to a range of novel research perspectives and problems both for improving robots’ interactions with individuals and impacts on society. Drawing on these arguments, we develop best practices for socially cognizant robot design that balance traditional technology-based metrics (e.g. efficiency, precision and accuracy) with critically important, albeit challenging to measure, human and society-based metrics. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine design

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Value of Information in Der Roll-Out

SSRN

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SSRN 2022年

作者： Khan, Hafiz Anwar Ullah Unel, Burcin Dvorkin, Yury Department of Electrical and Computer Engineering NYU Tandon School of Engineering New York University NY United States Institute for Policy Integrity NYU School of Law New York University NY United States

Integration of Distributed Energy Resources (DERs) in power systems exacerbates the existing information problems between power utilities and regulators. DER policies oblivious to the trilemma of information asymmetry between power utilities, DER aggregators, and regulators result in distorted price signals to DER investors, economically inefficient DER policies, and socially suboptimal DER roll-out. Therefore, in this paper, we propose a Stackelberg game approach for modeling and analyzing information asymmetry in distribution network information and consumer data between the DER aggregators and the power utilities. The proposed framework is based on hierarchical Single Leader Single Follower (SLSF) games, reformulated as Mathematical Programs with Equilibrium Constraints (MPECs), and solved using the Scholtes’s relaxation technique. Our results, based on the 7-bus Manhattan power network, show that unless the DER aggregators have perfect information about the distribution network characteristics, the welfare along with the realized installed capacity of DERs in the system decreases. Hence, policy interventions to alleviate the rampant information problems are imperative to ensure an optimal DER roll-out. © 2022, The Authors. All rights reserved.

关键词： Energy resources

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Towards Deep Attention in Graph Neural Networks: Problems and Remedies

arXiv

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arXiv 2023年

作者： Lee, Soo Yong Bu, Fanchen Yoo, Jaemin Shin, Kijung Kim Jaechul Graduate School of Artificial Intelligence KAIST Daejeon Korea Republic of School of Electrical Engineering KAIST Daejeon Korea Republic of Heinz College of Information Systems and Public Policy Carnegie Mellon University PittsburghPA United States

Graph neural networks (GNNs) learn the representation of graph-structured data, and their expressiveness can be further enhanced by inferring node relations for propagation. Attention-based GNNs infer neighbor importance to manipulate the weight of its propagation. Despite their popularity, the discussion on deep graph attention and its unique challenges has been limited. In this work, we investigate some problematic phenomena related to deep graph attention, including vulnerability to over-smoothed features and smooth cumulative attention. Through theoretical and empirical analyses, we show that various attention-based GNNs suffer from these problems. Motivated by our findings, we propose AERO-GNN, a novel GNN architecture designed for deep graph attention. AERO-GNN provably mitigates the proposed problems of deep graph attention, which is further empirically demonstrated with (a) its adaptive and less smooth attention functions and (b) higher performance at deep layers (up to 64). On 9 out of 12 node classification benchmarks, AERO-GNN outperforms the baseline GNNs, highlighting the advantages of deep graph attention. Our code is available at https://***/syleeheal/AERO-GNN. © 2023, CC BY-NC-SA.

关键词： Graph neural networks

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Sponge City As A Civil engineering Solution To Climate Change That Improves Urban Flood Resilience 10

Sponge City As A Civil Engineering Solution To Climate Chang...

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10th E-Health and Bioengineering Conference, EHB 2022

作者： Shao, Yu-Tong Ma, Kevin Sheng-Kai Department of Bioenvironmental Systems Engineering National Taiwan University Taipei Taiwan Center for Global Health Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan

ISBN: (纸本)9781665485579

Climate change and urbanization drive the demand for water management to make cities more water resilient. Climate change brings heavy precipitation and causes urban flooding, with conventional construction of cities no longer suitable given the rising risk of flooding. Characterized by constructing cities as large sponges that absorb and treat water, the idea of sponge cities is a solution to stormwater control and drainage water management, which can be achieved by creating water absorbing areas, increasing permeable surface, and integrating stormwater and drainage systems. To assess flood resilience, evaluation indicators have been introduced to measure the effectiveness of sponge cities. A case study was also provided in this review to demonstrate how the concept of sponge cities was put into practice. © 2022 IEEE.

关键词： Climate change

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Research on the Evaluation and Transformation of Resources in Closed Mines and the GIS Comprehensive Management System of Smart Mines

SSRN

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SSRN 2024年

作者： Feng, Xiaotong Dong, Jihong Wang, Lei Liu, Feng Genc, Bekir Celik, Turgay Ji, Li School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou221116 China China Coal Society Beijing100013 China School of Mining Engineering University of the Witwatersrand Johannesburg2050 South Africa School of Electrical and Information Engineering University of the Witwatersrand Johannesburg2000 South Africa School of Public Policy and Management China University of Mining and Technology Xuzhou221116 China

With the development of socio-economy and coal resources, some mines have reached the end of their life. Addressing resource waste and environmental problems caused by closed mines and utilizing their resources to promote the transformation of resource-exhausted mining areas has become a significant global concern in the energy and environment field. Main research contents of this paper: (1) Analyzed the academic concerns and research hotspots of closed mines both domestically and internationally, summarized the main unresolved issues in the field and explored the theoretical framework on closed mines. (2) The air-sky-earth multi-source collaborative data were used to identify the resource characteristics and to classify the above/belowground resource types of the closed mine. Provided calculation methods for aboveground buildings, underground tunnels, and shaft spaces, as well as an estimation method for the residual coal resources in the underground mines. (3) Comparing the transformation and utilization methods of closed mines at home and abroad, a technical system of transformation paths for closed mines was given based on constraints, transformation suitability level, resource conditions, etc., and the most suitable transformation paths for 15 pairs of closed mines in the Weihe River Basin were formulated according to the steps of determining the paths for resource transformation. (4) A comprehensive GIS database platform for mine closure resources was constructed from three aspects: system architecture design, scenario design, and functional design. The study aims to provide new ideas for the transformation and sustainable development of closed mine enterprises. © 2024, The Authors. All rights reserved.

关键词： Mining

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Device-Type Profiling for Network Access Control Systems using Clustering-Based Multivariate Gaussian Outlier Score 5

Device-Type Profiling for Network Access Control Systems usi...

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5th International Conference on Future Networks and Distributed Systems: The Premier Conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Muhammad, Musa Daniel Ani, Uchenna Abdullahi, Aminu Aliyu Radanliev, Petar Faculty of Engineering Environment and Computing Coventry University Scarborough United Kingdom Petras National Centre of Excellence for IoT Systems Cyber Security Department of Science Technology Engineering and Public Policy University College London United Kingdom Department of Computer Science Dutse Nigeria Oxford E-Research Centre Department of Engineering Sciences Oxford United Kingdom

ISBN: (纸本)9781450387347

Behaviour profiling is used in organisations to identify the working patterns of agents: humans or devices. It can be used to detect abnormal patterns of devices in an organisation's BYOD network to help control network access. Although BYOD offers great benefits of improving productivity and job satisfaction while reducing cost, it bears some security issues around access control with limitations in addressing insider threat scenarios. This means that motivated and determined attackers with valid access credentials can exploit the weaknesses to compromise the system. The limitation of mobile devices can mean that traditional network access control mechanism are ineffective in addressing insider threats, and can impact on device capacity and functionality. Thus, it is crucial to explore other ways of identifying insider threats from anomalous device behaviours. We propose a device-type profiling for threat detection which uses packet inter-arrival time patterns of devices for automatic identification of abnormal device-types. Experimental tests using clustering-based multivariate gaussian outlier score (CMGOS) to clearly distinguish and label normal and abnormal inter-arrival time patterns yielded promising results. This affirms the effectiveness of the proposed approach to support system administrators in monitoring and detecting insider threats for timely and effective access control response. © 2021 ACM.

关键词： Access control

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