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arXiv 2024年

作者： Turizo, Daniel Cifuentes, Diego Leykin, Anton Molzahn, Daniel K. School of Electrical and Computer Engineering Georgia Institute of Technology United States School of Industrial and Systems Engineering Georgia Institute of Technology United States School of Mathematics Georgia Institute of Technology United States

Optimal power flow (OPF) is a critical optimization problem for power systems to operate at points where cost or other operational objectives are optimized. Due to the non-convexity of the set of feasible OPF operating points, it is nontrivial to transition the power system from its current operating point to the optimal one without violating constraints. On top of that, practical considerations dictate that the transition should be achieved using a small number of small-magnitude control actions. To solve this problem, this paper proposes an algorithm for computing a transition path by framing it as a shortest path problem. This problem is formulated in terms of a discretized piece-wise linear path, where the number of pieces is fixed a priori in order to limit the number of control actions. This formulation yields a nonlinear optimization problem (NLP) with a sparse block tridiagonal structure, which we leverage by utilizing a specialized interior point method. An initial feasible path for our method is generated by solving a sequence of relaxations which are then tightened in a homotopy-like procedure. Numerical experiments illustrate the effectiveness of the algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Global optimization

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Cognition Difference-Based Dynamic Trust Network for Distributed Bayesian Data Fusion

Cognition Difference-Based Dynamic Trust Network for Distrib...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Yingke Li Ziqiao Zhang Junkai Wang Huibo Zhang Enlu Zhou Fumin Zhang school of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta GA USA

Distributed Data Fusion (DDF), as a prevalent technique that empowers scalable, flexible, and robust information fusing, has been employed in various multi-sensor networks operating in uncertain and dynamic environments. This paper proposes a cognition difference-based mechanism to construct a dynamic trust network for real-time DDF, where the cognition difference is defined as the statistical difference between the sensors' estimated probability distributions. Distinguished by the mutual correlation between trust and cognition difference, two principles of determining trust are investigated, and their performances are analyzed by conducting simulations in the scenarios of source seeking. Our simulation and experiment results show that the proposed approach is effective in providing comprehensive and robust performance in general and unstructured environments.

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Scalable and Independent Learning of Nash Equilibrium Policies in n-Player Stochastic Games with Unknown Independent Chains

arXiv

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arXiv 2023年

作者： Qin, Tiancheng Etesami, S. Rasoul The Department of Industrial and Systems Engineering Department of Electrical and Computer Engineering Coordinated Science Lab University of Illinois Urbana-Champaign UrbanaIL61801 United States

We study a subclass of n-player stochastic games, namely, stochastic games with independent chains and unknown transition matrices. In this class of games, players control their own internal Markov chains whose transitions do not depend on the states/actions of other players. However, players’ decisions are coupled through their payoff functions. We assume players can receive only realizations of their payoffs, and that the players can not observe the states and actions of other players, nor do they know the transition probability matrices of their own Markov chain. Relying on a compact dual formulation of the game based on occupancy measures and the technique of confidence set to maintain high-probability estimates of the unknown transition matrices, we propose a fully decentralized mirror descent algorithm to learn an ϵ-NE for this class of games. The proposed algorithm has the desired properties of independence, scalability, and convergence. Specifically, under no assumptions on the reward functions, we show the proposed algorithm converges in polynomial time in a weaker distance (namely, the averaged Nikaido-Isoda gap) to the set of ϵ-NE policies with arbitrarily high probability. Moreover, assuming the existence of a variationally stable Nash equilibrium policy, we show that the proposed algorithm converges asymptotically to the stable ϵ-NE policy with arbitrarily high probability. In addition to Markov potential games and linear-quadratic stochastic games, this work provides another subclass of n-player stochastic games that, under some mild assumptions, admit polynomial-time learning algorithms for finding their stationary ϵ-NE policies. Copyright © 2023, The Authors. All rights reserved.

关键词： Mirrors

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Real time enhancement of operator's ergonomics in physical human - robot collaboration scenarios using a multi-stereo camera system

Real time enhancement of operator's ergonomics in physical h...

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IEEE International Conference on industrial Technology (ICIT)

作者： Gerasimos Arvanitis Nikos Piperigkos Christos Anagnostopoulos Aris S. Lalos Konstantinos Moustakas Department of Electrical and Computer Engineering University of Patras Patra Greece Industrial Systems Institute ATHENA Research Center Patra Greece

In collaborative tasks where humans work alongside machines, the robot's movements and behaviour can have a significant impact on the operator's safety, health, and comfort. To address this issue, we present a multi-stereo camera system that continuously monitors the operator's posture while they work with the robot. This system uses a novel distributed fusion approach to assess the operator's posture in real-time and to help avoid uncomfortable or unsafe positions. The system adjusts the robot's movements and informs the operator of any incorrect or potentially harmful postures, reducing the risk of accidents, strain, and musculoskeletal disorders. The analysis is personalized, taking into account the unique anthropometric characteristics of each operator, to ensure optimal ergonomics. The results of our experiments show that the proposed approach leads to improved human body postures and offers a promising solution for enhancing the ergonomics of operators in collaborative tasks.

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Real time enhancement of operator’s ergonomics in physical human - robot collaboration scenarios using a multi-stereo camera system

arXiv

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arXiv 2023年

作者： Arvanitis, Gerasimos Piperigkos, Nikos Anagnostopoulos, Christos Lalos, Aris S. Moustakas, Konstantinos Department of Electrical and Computer Engineering University of Patras Patra Greece Industrial Systems Institute ATHENA Research Center Patra Greece

In collaborative tasks where humans work alongside machines, the robot’s movements and behaviour can have a significant impact on the operator’s safety, health, and comfort. To address this issue, we present a multi-stereo camera system that continuously monitors the operator’s posture while they work with the robot. This system uses a novel distributed fusion approach to assess the operator’s posture in real-time and to help avoid uncomfortable or unsafe positions. The system adjusts the robot’s movements and informs the operator of any incorrect or potentially harmful postures, reducing the risk of accidents, strain, and musculoskeletal disorders. The analysis is personalized, taking into account the unique anthropometric characteristics of each operator, to ensure optimal ergonomics. The results of our experiments show that the proposed approach leads to improved human body postures and offers a promising solution for enhancing the ergonomics of operators in collaborative tasks. © 2023, CC BY.

关键词： Ergonomics

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Distribution-Free Guarantees for systems with Decision-Dependent Noise

arXiv

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arXiv 2024年

作者： Zhang, Heling Ratliff, Lillian J. Dong, Roy The Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign ChampaignIL61801 United States The Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States The Department of Industrial and Enterprise Systems Engineering University of Illinois at Urbana-Champaign ChampaignIL61801 United States

In many real-world dynamicalsystems, obtaining precise models of system uncertainty remains a challenge. It may be difficult to estimate noise distributions or robustness bounds, especially when the distributions/robustness bounds vary with different control inputs in unknown ways. Addressing this challenge, this paper presents a novel iterative method tailored for systems with decision-dependent noise without prior knowledge of the distributions. Our approach finds the open-loop control law that minimizes the worst-case loss, given that the noise induced by this control lies in its (1 − p)-confidence set for a predetermined p. At each iteration, we use a quantile method inspired by conformal prediction to empirically estimate the confidence set shaped by the preceding control law. These derived confidence sets offer distribution-free guarantees on the system's noise, guiding a robust control formulation that targets worst-case loss minimization. Under specific regularity conditions, our method is shown to converge to a near-optimal open-loop control. While our focus is on open-loop controls, the adaptive, data-driven nature of our approach suggests its potential applicability across diverse scenarios and extensions. © 2024, CC BY.

关键词： Open loop control

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The Privacy Attitudes Questionnaire (PAQ) Turned 20: What’s Next for a Generalized Measure of Privacy Attitudes?

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2023年第1期67卷 705 - 709页

作者： Wayne C. W. Giang Alyssa Iglar Mark Chignell Reza Samavi Kopiha Nathan Department of Industrial and Systems Engineering University of Florida Gainesville FL USA Department of Mechanical and Industrial Engineering University of Toronto Toronto ON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON CanadaVector Institute Healthcare Insurance Reciprocal of Canada Toronto ON Canada

Attitudes and concerns related to privacy are not homogeneous, but instead differ based on the individual and context at hand. Understanding how these attitudes and concerns vary could inform product, service, and policy design. Questionnaires, such as the Privacy Attitudes Questionnaire (PAQ), can be used to evaluate and derive implications from people’s privacy orientations in numerous domains, including healthcare, social media, and e-commerce. Our objective is to refine the PAQ to reflect areas of privacy concern in today’s landscape. The panel will serve as a forum for conversation about areas of privacy concern, guided by our panelists’ expertise and questions about demographic and user considerations for the revised PAQ, a framework-inspired understanding of privacy, and privacy in healthcare. Insights and perspectives arising from the discussion panel will be considered for subsequent revisions of the PAQ.

关键词： privacy attitudes concerns questionnaire context healthcare

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Quantized Transformer Language Model Implementations on Edge Devices

Quantized Transformer Language Model Implementations on Edge...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Mohammad Wali Ur Rahman Murad Mehrab Abrar Hunter Gibbons Copening Salim Hariri Sicong Shao Pratik Satam Soheil Salehi Electrical and Computer Engineering University of Arizona Tucson AZ USA Computer Science University of Arizona Tucson AZ USA Systems and Industrial Engineering University of Arizona Tucson AZ USA Electrical Engineering and Computer Science University of North Dakota Grand Forks ND USA

Large-scale transformer-based models like the Bidi-rectional Encoder Representations from Transformers (BERT) are widely used for Natural Language Processing (NLP) applications, wherein these models are initially pre-trained with a large corpus with millions of parameters and then fine-tuned for a downstream NLP task. One of the major limitations of these large-scale models is that they cannot be deployed on resource- constrained devices due to their large model size and increased inference latency. In order to overcome these limitations, such large-scale models can be converted to an optimized FlatBuffer format, tailored for deployment on resource-constrained edge devices. Herein, we evaluate the performance of such FlatBuffer transformed MobileBERT models on three different edge devices, fine-tuned for Reputation analysis of English language tweets in the Rep Lab 2013 dataset. In addition, this study encompassed an evaluation of the deployed models, wherein their latency, performance, and resource efficiency were meticulously assessed. Our experiment results show that, compared to the original BERT large model, the converted and quantized MobileBERT models have 160x smaller footprints for a 4.1 % drop in accuracy while analyzing at least one tweet per second on edge devices. Furthermore, our study highlights the privacy-preserving aspect of TinyML systems as all data is processed locally within a serverless environment.

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Meaning of the Clusters on Dimensionality Reduction by Word Clustering 12

Meaning of the Clusters on Dimensionality Reduction by Word ...

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12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

作者： Deguchi, Toshinori Seo, Sinsuke Ishii, Naohiro Dept. of Electrical and Computer Engineering Gifu College Gifu Japan Interdisciplinary Technology Development Gifu College Gifu Japan Information Systems Architecture Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665497558

ISBN: (纸本)9781665497558

In text mining, Latent Semantic Analysis (LSA) is the popular method to reduce the dimension of document vectors. Since LSA produces a set of topics by statistical information, the meaning of each topic is not *** proposed a method to reduce the dimension by clustering the words in the documents. This method produces a set of clusters of words instead of topics. Using Word2vec to vectorize the words, the mean vector of the cluster is calculated, which shows the meaning of the *** this paper, we show the dimensionality reduction and the meaning of the generated clusters by word cloud, on document classification problem with a subset of BBC Dataset. © 2022 IEEE.

关键词： Classification (of information)

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Study of the Influence of Rolling Modes on the Operation of Interconnected Electric Drives of a Rolling Mill 4

Study of the Influence of Rolling Modes on the Operation of ...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Tytiuk, Valerii Busher, Victor Kalinin, Alexey Chornyi, Oleksii Druzhinin, Valeriy Halushko, Dmytro Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Dept. of Electrical Engineering and Electronics National University "Odessa Maritime Academy" Odessa Ukraine Department of Informative computer systems Abylkas Saginov Karaganda Technical University NPJSC Karaganda Kazakhstan Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Department of Power Engineering Karaganda Industrial University NPJSC Temirtau Kazakhstan Dept. of Electrical Engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

ISBN: (纸本)9798350395532

The paper is devoted to study of the influence of rolling modes on the performance of powerful interconnected electric drives of a hot rolling mill under the action of an electromagnetic coupling circuit between the electric drives of the roughing and finishing groups. The action of the electromagnetic coupling circuit manifests itself in the form of the influence of impact loads of synchronous electric drives on the angular velocity of direct current electric drives of the finishing group of the mill. The parameters of the electromagnetic coupling circuit are determined by the power supply scheme and equipment parameters. Values of impact loads applied to a synchronous motor depend on the rolling process parameters, in particular, the chemical composition of the rolled steel and the temperature of the ingot. The paper presents the results of calculating the rolling power for various rolling mode parameters. Using mathematical modeling in Simulink, numerical estimates of the influence of rolling modes on the magnitude of the voltage drop in the power supply unit and the drop in the angular velocity of the electric drive of the finishing group were obtained on the example of a wide-strip hot rolling mill 1700 of ArcelorMittal Temirtau JSC. © 2023 IEEE.

关键词： Hot rolling

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