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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Faris Alotibi David Tipper Department of Informatics and Networked Systems School of Computing and Information University of Pittsburgh Pittsburgh PA USA School of Computer Science and Engineering Taibah University Medina Saudi Arabia

ISBN: (纸本)9781665435413

The growth of wind power generation is accelerating worldwide. However, wind turbines need to be carefully controlled to maintain structural stability and optimal power generation. The state of the turbine and power generated is digitized and transmitted over communication networks for physical component monitoring, control, and data management. Motivated by creating power outages, financial loss, and physical wind turbine damage, attackers could craft and inject falsified network traffic to maliciously influence control actions. In this paper, we propose a physics-informed machine learning anomaly detection approach. The mechanism is utilized at each wind turbine, where generated power signals are validated based on laws of physics and incorporated into machine learning algorithm to detect anomalies. We show that the proposed combined physics and machine learning approach improves the accuracy of detecting falsification attacks compared with using machine learning alone.

关键词： Machine learning algorithms Machine learning Telecommunication traffic Wind farms Wind power generation Wind turbines Structural engineering

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Light-Weight RetinaNet for Object Detection on Edge Devices

Light-Weight RetinaNet for Object Detection on Edge Devices

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Yixing Li Akshay Dua Fengbo Ren School of Computing Informatics and Decision Systems Engineering Arizona State University

ISBN: (数字)9781728155036

ISBN: (纸本)9781728155043

This paper aims at reducing computation for Retinanet, an mAP-30-tier network, to facilitate its practical deployment on edge devices for providing IoT-based object detection services. We first validate RetinaNet has the best FLOP-mAP trade-off among all mAP-30-tier network. Then, we propose a light-weight RetinaNet structure with effective computation- accuracy trade-off by only reducing FLOPs in computationally intensive layers. Compared with the most common way of trading off computation with accuracy-input image scaling, the proposed solution shows a consistently better FLOPs-mAP trade-off curve. Light-weight RetinaNet achieves a 0.3% mAP improvement at 1.8x FLOPs reduction point over the original RetinaNet, and gains 1.8x more energy-efficiency on an Intel Arria 10 FPGA accelerator in the context of edge computing. The proposed method potentially can help a wide range of the object detection applications to move closer to a preferred corner for a better runtime and accuracy, while enjoys more energy-efficient inference at the edge.

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Distributed Charging Coordination for Electric Trucks under Limited Facilities and Travel Uncertainties

arXiv

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arXiv 2024年

作者： Bai, Ting Li, Yuchao Malikopoulos, Andreas A. Johansson, Karl Henrik Mårtensson, Jonas Integrated Transport Research Lab The Division of Decision and Control Systems The Digital Futures KTH Royal Institute of Technology StockholmSE-10044 Sweden School of Computing and Augmented Intelligence Arizona State University TempeAZ-85281 United States School of Civil and Environmental Engineering Cornell University IthacaNY-14853 United States

In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks’ nontrivial charging times and the stations’ limited charging facilities. Our goal is to reduce the trucks’ waiting times at the stations while minimizing individual trucks’ operational costs. We propose a distributed coordination framework that relies on computation and communication between the stations and the trucks, and handles uncertainties in travel times and energy consumption. Within the framework, the stations assign a limited number of charging ports to trucks according to the first-come, first-served rule. In addition, each station constructs a waiting time forecast model based on its historical data and provides its estimated waiting times to trucks upon request. When approaching a station, a truck sends its arrival time and estimated arrival-time windows to the nearby station and the distant stations, respectively. The truck then receives the estimated waiting times from these stations in response, and updates its charging plan accordingly while accounting for travel uncertainties. We performed simulation studies for 1, 000 trucks traversing the Swedish road network for 40 days, using realistic traffic data with travel uncertainties. The results show that our method reduces the average waiting time of the trucks by 46.1% compared to offline charging plans computed by the trucks without coordination and update, and by 33.8% compared to the coordination scheme assuming zero waiting times at distant stations. Copyright © 2024, The Authors. All rights reserved.

关键词： Trucks

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Managing technological vulnerability of urban dwellers: Analysis, trends, and solutions

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2020年第1期1卷 48-59页

作者： Robertson, Lindsay J. Munoz, Albert Michael, Katina SCIT University of Wollongong WollongongNSW2522 Australia Faculty of Business University of Wollongong WollongongNSW2522 Australia School for the Future of Innovation in Society School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85287 United States

Urban dwellers are increasingly dependent on technological systems to supply goods and services essential for their way of life. Such dependence incurs vulnerability in situations when these goods and services are not available. The systems supplying these essentials are known to have many loci of failure. We consider the exposure of a technological system in terms of the number and type of loci of failure and present this as a metric of urban dweller vulnerability. Such a metric captures the vulnerability to the nonavailability of the specific goods or services provided by a particular technological system. By selecting from goods and services commonly required, this article identifies a representative range of essential goods and services provided to urban-dwelling individuals by technological systems, and examines the nature and extent of exposure associated with each system. Based upon the descriptions of these technological systems, this article classifies the contributors to each technological system’s exposure into a small number of categories. The analysis allows the inference of generalized approaches for reducing each category of exposure, and hence vulnerability. Thus, a theory of exposure can be used to inform engineering management approaches applicable to end-user vulnerability reduction, and to identify the feasibility of less exposed technological systems. © 2020 IEEE. All right reserved.

关键词： Risk assessment

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Modulated Predictive Current Control of Back-to-Back NPC Converter in PMSG Wind Energy System with Reduced Computational Burden

Modulated Predictive Current Control of Back-to-Back NPC Con...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Ai Zhang Venkata Yaramasu Jose Rodriguez Zhenbin Zhang School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff USA Faculty of Engineering Universidad San Sebastian Santiago Chile School of Electrical engineering Shandong University Shandong China

This paper proposes a novel modulated predictive current control with a reduced computational burden for a three-phase back-to-back connected neutral-point clamped (NPC) converter in a permanent magnet synchronous generator (PMSG) based wind energy system. An algorithm has been developed to determine the optimal sector number based on measured generator- and grid-side voltages and currents. The eight voltage vectors in the optimal sector are then used to determine the optimal triangular region (among 6) that produces the minimum cost function value for NPC rectifier and inverter. The three voltage vectors in the optimal triangular region are selected and applied to the rectifier and inverter via seven segment switching scheme. The dwell times of medium voltage vectors in the switching sequence are adjusted dynamically to balance the DC capacitor voltages. The proposed approach produces constant switching frequency, minimal steady-state errors, and fast transient response. The developed control scheme is tested on a 3 MW, 3 kV PMSG wind energy system through MATLAB simulations.

关键词： Current control Transient response Wind energy Switching frequency Rectifiers Switches Cost function

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Deep Graph Learning for Anomalous Citation Detection

arXiv

引用

arXiv 2022年

作者： Liu, Jiaying Xia, Feng Feng, Xu Ren, Jing Liu, Huan School of Economics and Management Dalian University of Technology Dalian116024 China School of Engineering IT and Physical Sciences Federation University Australia BallaratVIC3353 Australia School of Software Dalian University of Technology Dalian116620 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States

Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid to scholarly data, i.e., anomaly detection in a citation network. Citation is considered as one of the most crucial metrics to evaluate the impact of scientific research, which may be gamed in multiple ways. Therefore, anomaly detection in citation networks is of significant importance to identify manipulation and inflation of citations. To address this open issue, we propose a novel deep graph learning model, namely GLAD (Graph Learning for Anomaly Detection), to identify anomalies in citation networks. GLAD incorporates text semantic mining to network representation learning by adding both node attributes and link attributes via graph neural networks. It exploits not only the relevance of citation contents but also hidden relationships between papers. Within the GLAD framework, we propose an algorithm called CPU (Citation PUrpose) to discover the purpose of citation based on citation texts. The performance of GLAD is validated through a simulated anomalous citation dataset. Experimental results demonstrate the effectiveness of GLAD on the anomalous citation detection task. Copyright © 2022, The Authors. All rights reserved.

关键词： Anomaly detection

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Digital Innovations Development: Causal factors and relations - A Case Study of Montenegro 28

Digital Innovations Development: Causal factors and relation...

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2024 28th International Conference on Information Technology, IT 2024

作者： Ognjanovic, Ivana Lakovic, Luka Sendelj, Ramo Bokor, Laszlo Kara, Peter A. Reich, Christoph Madan, Manav Roganovic, Milovan Zouilas, Emmanouil Mantas, John Erakovic, Jevto Radusinovic, Tanja Rakocevic, Nada University of Donja Gorica Faculty for Information Systems and Technologies Podgorica81000 Montenegro University of Donja Gorica Humanistic Studies Podgorica81000 Montenegro Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary Furtwangen University Institute of Data Science Cloud Computing and It Security Furtwangen78120 Germany Clinic for Neurology Clinical Centre of Montenegro Podgorica81000 Montenegro National and Kapodistrian University of Athens Faculty of Nursing School of Health Sciences Goudi11527 Greece Chamber of Economy of Montenegro Podgorica81000 Montenegro

ISBN: (纸本)9798350369618

In order for economies to expand and develop globally, innovation is essential. A popular statistic for evaluating innovation between countries is the Global Innovation Index (GII), which provides a thorough analysis of the state of innovation worldwide. In this context, this paper aims to contribute to the literature by examining the multi-factoral effects of the innovation ecosystem on innovation development (internal causal effects), and the impact of global trends and crises on the innovation ecosystem (external causal effects) in Montenegro. The resources provided in this paper offer valuable insights into the innovation landscape in Montenegro and the Western Balkans, as well as the impact of globalization, global trends, and crises on innovation in the region. The paper also discusses the function of innovation hubs such as the DigNest project, in promoting cooperation between academic institutions, government agencies and corporations, and supporting the exchange of knowledge and fresh concepts. © 2024 IEEE.

关键词： Ecosystems

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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Flexible GPU-Based Implementation of Number Theoretic Transform for Homomorphic Encryption

Flexible GPU-Based Implementation of Number Theoretic Transf...

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International SoC Design Conference, ISOCC

作者： Phap Duong-Ngoc Thang Xuan Pham Hanho Lee Tuy Tan Nguyen Dept. of Information and Communication Engineering Inha University Incheon Korea School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff USA

ISBN: (纸本)9781665459723

This paper proposes a flexible implementation of Number Theoretic Transform (NTT) on GPU platforms. The proposed method introduces an adjustable number (i.e., $NTT_{core}$ ) of butterfly units that are simultaneously implemented in each NTT computational stage. The NTT implementation of a large polynomial was experimented on an NVIDIA GeForce RTX 3070 GPU card and showed at least 21× acceleration compared with that on the CPU. The proposed approach is worthy to parallelize NTT computations of multiple polynomials in expensive homomorphic functions with high circuit depth.

关键词： Instruction sets Graphics processing units Transforms Cryptography Homomorphic encryption

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Influence Maximization: Divide and Conquer

arXiv

引用

arXiv 2022年

作者： Patwardhan, Siddharth Radicchi, Filippo Fortunato, Santo Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Bloomington United States

The problem of influence maximization, i.e., finding the set of nodes having maximal influence on a network, is of great importance for several applications. In the past two decades, many heuristic metrics to spot influencers have been proposed. Here, we introduce a framework to boost the performance of any such metric. The framework consists in dividing the network into sectors of influence, and then selecting the most influential nodes within these sectors. We explore three different methodologies to find sectors in a network: graph partitioning, graph hyperbolic embedding, and community structure. The framework is validated with a systematic analysis of real and synthetic networks. We show that the gain in performance generated by dividing a network into sectors before selecting the influential spreaders increases as the modularity and heterogeneity of the network increase. Also, we show that the division of the network into sectors can be efficiently performed in a time that scales linearly with the network size, thus making the framework applicable to large-scale influence maximization problems. © 2022, CC BY-NC-ND.

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