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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Li, Tao Hammar, Kim Stadler, Rolf Zhu, Quanyan New York University Department of Electrical and Computer Engineering United States Kth Royal Institute of Technology Division of Network and Systems Engineering Sweden

ISBN: (纸本)9798350316339

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyberphysical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actorcritic (FAC) architecture, where subjective forecasts are used to conjecture the opponents' strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL's faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks. © 2024 IEEE.

关键词： Cost functions

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A Market-Clearing-Based Sensitivity Model for Locational Marginal and Average Carbon Emission

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第4期2卷 579-582页

作者： Lu, Zelong Yan, Lei Wang, Jianxue Kang, Chongqing Shahidehpour, Mohammad Li, Zuyi Xi'an Jiaotong University School of Electrical Engineeng Xi'an710049 China Zhejiang University College of Electrical Engineering Hangzhou310027 China Tsinghua University State Key Lab of Power Systems Department of Electrical Engineering Beijing100084 China Illinois Institute of Technology Department of Electrical and Computer Engineering ChicagoIL60616 United States

This letter proposes a market-clearing-based locational marginal carbon emission (LMCE) metric to assess the marginal carbon emission effect of nodal load demand. Unlike the prevalent carbon emission flow (CEF) method that relies on a hypothetical power-flow tracking process, the proposed LMCE metric depends on a novel sensitivity analysis of market-clearing results, capable of revealing both energy-dependent and network-dependent impacts on emissions. Additionally, we introduce a locational average carbon emission (LACE) metric, derived from LMCE, to effectively measure the general emission effect. It offers insights into demand-side carbon emission effects, such as a negative LMCE and LACE indicating emission reduction even as load increases. It can also prevent excessive demand-side emission allocations. Overall, the proposed method provides a clear perspective for the ongoing decarbonization policies. © 2024 IEEE.

关键词： Sensitivity analysis

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Constraint Composite Graph-Based Weighted CSP Solvers: An Empirical Study 37

Constraint Composite Graph-Based Weighted CSP Solvers: An Em...

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37th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2024

作者： Rillo, Orazio Kumar, T.K. Satish Department of Computer Science Department of Physics and Astronomy Department of Industrial and Systems Engineering Information Sciences Institute University of Southern California United States

The Weighted Constraint Satisfaction Problem (WCSP) is a very expressive framework for optimization problems. The Constraint Composite Graph (CCG) is a graphical representation of a given (Boolean) WCSP that facilitates its reduction to a Minimum Weighted Vertex Cover (MWVC) problem by introducing intelligently chosen auxiliary variables. It also enables kernelization: a maxflow procedure used to fix the optimal values of a subset of the variables before initiating search. In this paper, we present some CCG-based WCSP solvers and compare their performance against toulbar2, a state-of-the-art WCSP solver, on a variety of benchmark instances. We also study the effectiveness of kernelization. Copyright © 2024 by the authors.

关键词： Constraint satisfaction problems

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A Survey of Cyber Attacks on Cyber Physical systems:Recent Advances and Challenges

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 784-800页

作者： Wenli Duo MengChu Zhou Abdullah Abusorrah Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China IEEE Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center and Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz University

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over *** plays a key role in modern industry since it connects physical and cyber *** order to meet ever-changing industrial requirements,its structures and functions are constantly ***,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and *** paper presents a survey of state-of-the-art results of cyber attacks on cyber physical ***,as typical system models are employed to study these systems,time-driven and event-driven systems are ***,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are *** particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and ***,both attack and defense strategies are discussed based on different system *** challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

关键词： Attack detection attack strategy cyber attack cyber physical system(CPS) secure control

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An Efficient Method to Estimate Admittance of Black-boxed Inverter-based Resources for Varying Operating Points

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CSEE Journal of Power and Energy systems 2024年第1期10卷 421-426页

作者： Weihua Zhou Bin Liu Nabil Mohammed Behrooz Bahrani Department of Electrical and Computer Systems Engineering Monash UniversityMelbourne 3800Australia Energy Centre Commonwealth Scientific and Industrial Research Organisation(CSIRO)Newcastle 2300Australia.He is now with the Network Planning DivisionTransgridSydney 2000Australia

Traditional analytical approaches for stability assessment of inverter-based resources(IBRs),often requiring detailed knowledge of IBR internals,become impractical due to IBRs’proprietary *** measurements,relying on electromagnetic transient simulation or laboratory settings,are not only time-intensive but also operationally inflexible,since various non-linear control loops make IBRs’admittance models operating-point ***,such admittance measurements must be performed repeatedly when operating point *** avoid time-consuming and cumbersome measurements,admittance estimation for arbitrary operating points is highly ***,existing admittance estimation algorithms usually face challenges in versatility,data demands,and *** this challenge,this letter presents a simple and efficient admittance estimation method for blackboxed IBRs,by utilizing a minimal set of seven operating points to solve a homogeneous linear equation *** studies demonstrate this proposed method ensures high accuracy across various types of *** accuracy is satisfying even when non-negligible measurement errors exist.

关键词： Admittance estimation black box inverterbased resource measurement error operating point

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Sentiment Analysis of Bangladeshi Digital Newspaper by Using Machine Learning and Natural Language Processing 6

Sentiment Analysis of Bangladeshi Digital Newspaper by Using...

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6th International Conference on electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Samin, Tasfia Mouri, Neshat Anjuman Haque, Farzana Islam, Md. Shariful North South University Department of Electrical & Computer Engineering Dhaka Bangladesh North South University Department of Mathematics & Physics Dhaka Bangladesh

ISBN: (纸本)9798350385779

The modern era has witnessed a heightened level of global news exposure in recent years. We all are updated with any news, be it the economic news of our country, the political news, national or international calamities, disease outbreaks, accidents, or homicides through various means of communication. Despite the advancements in news media, the enduring appeal and sustained demand for newspapers have not waned over time. A notable segment of the population still relies on the regular distribution of newspapers to their homes as a means of staying updated on domestic and global events. The profound influence of print media on the community and its perception of the nation is a matter of great significance. Within the realm of news, it is evident that the presence of positive and negative news yields distinct effects on individuals. This study focuses on conducting sentiment analysis of news articles featured on the front pages of prominent newspapers in Bangladesh. The polarity of news stories from five distinct newspapers was examined individually, as well as the collective polarity of the full dataset. The overall dataset consists of positive, negative, and neutral news, accounting for 54.305%, 42.434%, and 3.259% respectively. The classification has been done on a unique customized dataset containing the news for six consecutive months on the front pages of the leading five newspapers and the analysis was performed using six classification models: Logistic Regression, Multinomial Naive Bayes, Support Vector Machine (SVM), Support Vector Classifier (SVC), Random Forest, and K Nearest Neighbors. Overall, these models achieved accuracies of approximately 85.19%, 77.39%, 83.17%, 84.23%, 80.60%, and 58.78% respectively. © 2024 IEEE.

关键词： Sentiment analysis

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Photogrammetry for Digital Twinning Industry 4.0 (I4) systems 21

Photogrammetry for Digital Twinning Industry 4.0 (I4) System...

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2024 IEEE/ACS 21st International Conference on computer systems and Applications, AICCSA 2024

作者： Alhamadah, Ahmed Mamun, Muntasir Harms, Henry Redondo, Mathew Lin, Yu-Zheng Pacheco, Jesus Salehi, Soheil Satam, Pratik University of Arizona Department of Systems and Industrial Engineering United States University of Arizona Department of Electrical and Computer Engineering United States School of Industrial Engineering University of Sonora Mexico

ISBN: (纸本)9798331518240

The onset of Industry 4.0 is rapidly transforming the manufacturing world through the integration of cloud computing, machine learning (ML), artificial intelligence (AI), and universal network connectivity, resulting in performance optimization and increased productivity. Digital Twins (DT) are one such transformational technology that leverages software systems to replicate physical process behavior, and representing it in a digital environment. This paper aims to explore the use of photogrammetry (which is the process of reconstructing physical objects into virtual 3D models using photographs) and 3D Scanning techniques to create accurate visual representation of the 'Physical Process', to interact with the ML/AI based behavior models. To achieve this, we have used a readily available consumer device, the iPhone 15 Pro, which features stereo vision capabilities, to capture the depth of an Industry 4.0 system. By processing these images using 3D scanning tools, we created a raw 3D model for 3D modeling and rendering software for the creation of a DT model. The paper highlights the reliability of this method by measuring the error rate in between the ground truth (measurements done manually using a tape measure) and the final 3D model created using this method. The overall mean error is 4.97 % and the overall standard deviation error is 5.54% between the ground truth measurements and their photogrammetry counterparts. The results from this work indicate that photogrammetry using consumer-grade devices can be an efficient and cost-efficient approach to creating DTs for smart manufacturing, while the approaches flexibility allows for iterative improvements of the models over time. © 2024 IEEE.

关键词： Stereo vision

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Electric Bike Security and Protection System 2

Electric Bike Security and Protection System

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Maniraj, P. Murugan, A. Durai Gokul, R. Shalini, A.S. Kesavan, K. Kavin, P. M. Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Karur India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Electrical and Electronics Engineering Karur India

ISBN: (纸本)9798350349221

With the developing prevalence of electric bicycles (e-bicycles) as a feasible and proficient method of transportation, guaranteeing their security has turned into a foremost concern. Electric bicycles are important resources helpless against robbery and harm, to conquer this issue the venture proposes the improvement of an Electric Vehicle Burglary Location and Warning Framework utilizing IOT innovation. The framework integrates sensors to screen electric vehicles for unapproved access and utilizes Radio Recurrence ID innovation to improve security. After recognizing an unfair RFID section or any dubious movement, the framework sets off a caution to tell the proprietor and naturally locks the back tire, forestalling robbery. This framework could be an instrument for deflecting the robbery of electric vehicles and keeping proprietors from monetary misfortunes. In a period of developing IOT-based security arrangements, this framework offers an important expansion to safeguard electric vehicle and their venture. © 2024 IEEE.

关键词： Electric vehicles

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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A Nested Ensemble Method to Bilevel Machine Learning 48

A Nested Ensemble Method to Bilevel Machine Learning

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Chen, Lisha Abbas, Momin Chen, Tianyi Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering Department TroyNY United States

ISBN: (纸本)9781728163277

Modern machine learning problems, such as hyperparameter optimization, meta learning, and adversarial training, adopt a bilevel learning formulation. Such problems involve a nested relation between inner- and outer-level problems, which often have suboptimal solutions with poor generalization ability. To address this issue, this paper proposes an ensemble method tailored to bilevel learning. Our method finds a nested ensemble of inner and outer parameters that improve generalization. We instantiate our general results with meta learning. We show theoretically and empirically that the diversity and the smoother loss landscape of the proposed ensemble methods lead to improved generalization over the state-of-the-art method. © 2023 IEEE.

关键词： Machine learning

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