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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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Quantum Calculus-Based Two-Dimensional Least Mean Square Algorithm

Quantum Calculus-Based Two-Dimensional Least Mean Square Alg...

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Asilomar Conference on Signals, systems & computers

作者： Muhammad Moinuddin Azzedine Zerguine Ubaid M. Al-Saggaf Muhammad Arif Electrical and Computer Engineering Department and the Centre of Excellence in Intelligent Engineering Systems King Abdulaziz University Jeddah Saudi Arabia Electrical Engineering Department and the Interdisciplinary Research Center for Communication Systems and Sensing KFUPM Dhahran Saudi Arabia Institute of Networked and Embedded Systems University of Klagenfurt and the Ubiquitous Sensing Systems Lab University of Klagenfurt-Silicon Austria Labs Klagenfurt Austria

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Recent work of the one-dimensional q-LMS algorithm give insight that the Quantum Calculus based gradient called the q-gradient is capable of improving the convergence behavior in contrast to the standard LMS algorithm. The reason for this is the fact that the q-derivative takes larger steps in minimizing a cost function as it evaluates the secant in contrast to the tangent of the cost function. Motivated by this, we propose a two-dimensional version of the q-LMS algorithm. More precisely, we employ Quantum Calculus based q-gradient in steepest descent optimization of mean-square-error (MSE) cost function in 2D adaptive filtering scenario to obtain two-dimensional q-LMS (2D q-LMS) algorithm. A thorough analytical investigation of the proposed 2D q-LMS algorithm in both mean and mean-square sense is provided. Both the transient and steady-state convergence behaviours are examined. Consequently, excess MSE (EMSE) learning curve and its steady-state expression are evaluated in closed form. Simulation results are presented for the application of noise cancelation in images to show the superiority of the proposed 2D q-LMS algorithm.

关键词： Filtering Two-dimensional displays Simulation Cost function Calculus Steady-state Performance analysis Transient analysis Standards Convergence

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MovieChat+: Question-aware Sparse Memory for Long Video Question Answering

arXiv

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arXiv 2024年

作者： Song, Enxin Chai, Wenhao Ye, Tian Hwang, Jenq-Neng Li, Xi Wang, Gaoang Zhejiang University-University of Illinois at Urbana-Champaign Institute Zhejiang University China The Department of Electrical and Computer Engineering The University of Washington United States Robotics and Autonomous Systems Thrust Hong Kong University of Science and Technology Guangzhou China The College of Computer Science and Technology Zhejiang University China

Recently, integrating video foundation models and large language models to build a video understanding system can overcome the limitations of specific pre-defined vision tasks. Yet, existing methods either employ complex spatial-temporal modules or rely heavily on additional perception models to extract temporal features for video understanding, and they only perform well on short videos. For long videos, the computational complexity and memory costs associated with long-term temporal connections are significantly increased, posing additional challenges. Taking advantage of the Atkinson-Shiffrin memory model, with tokens in Transformers being employed as the carriers of memory in combination with our specially designed memory mechanism, we propose MovieChat to overcome these challenges. We lift pre-trained multi-modal large language models for understanding long videos without incorporating additional trainable temporal modules, employing a zero-shot approach. Additionally, in our new version, MovieChat+, we design an enhanced vision-question matching-based memory consolidation mechanism to more significantly anchor the predictions of the visual language models in the relevant visual content. MovieChat achieves state-of-the-art performance in long video understanding, along with the released MovieChat-1K benchmark with 1K long video, 2K temporal grounding labels, and 14K manual annotations for validation of the effectiveness of our method. The code along with the dataset can be accessed via the following link. © 2024, CC BY.

关键词： Zero-shot learning

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Probabilistic Planning with Prioritized Preferences over Temporal Logic Objectives

arXiv

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arXiv 2023年

作者： Li, Lening Rahmani, Hazhar Fu, Jie The Department of Robotics Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Electrical and Computer Engineering University of Florida GainesvilleFL32605 United States

This paper studies temporal planning in probabilistic environments, modeled as labeled Markov decision processes (MDPs), with user preferences over multiple temporal goals. Existing works reflect such preferences as a prioritized list of goals. This paper introduces a new specification language, termed prioritized qualitative choice linear temporal logic on finite traces, which augments linear temporal logic on finite traces with prioritized conjunction and ordered disjunction from prioritized qualitative choice logic. This language allows for succinctly specifying temporal objectives with corresponding preferences accomplishing each temporal task. The finite traces that describe the system's behaviors are ranked based on their dissatisfaction scores with respect to the formula. We propose a systematic translation from the new language to a weighted deterministic finite automaton. Utilizing this computational model, we formulate and solve a problem of computing an optimal policy that minimizes the expected score of dissatisfaction given user preferences. We demonstrate the efficacy and applicability of the logic and the algorithm on several case studies with detailed analyses for each. Copyright © 2023, The Authors. All rights reserved.

关键词： Specification languages

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Efficient Coordination and Synchronization of Multi-Robot systems Under Recurring Linear Temporal Logic

arXiv

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arXiv 2025年

作者： Peron, Davide Fernandez-Ayala, Victor Nan Vlahakis, Eleftherios E. Dimarogonas, Dimos V. Department of Information Engineering University of Padova Padova35122 Italy Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden

We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem efficiently, we propose a bottom-up approach combining offline plan synthesis with online coordination, dynamically adjusting plans via real-time communication. To address action delays, we introduce a synchronization mechanism ensuring coordinated task execution, leading to a multi-agent coordination and synchronization framework that is adaptable to a wide range of multi-robot applications. The software package is developed in Python and ROS2 for broad deployment. We validate our findings through lab experiments involving nine robots showing enhanced adaptability compared to previous methods. Additionally, we conduct simulations with up to ninety agents to demonstrate the reduced computational complexity and the scalability features of our work. © 2025, CC BY.

关键词： Multipurpose robots

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Demystifying Device-Specific Compatibility Issues in Android Apps

Demystifying Device-Specific Compatibility Issues in Android...

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International Conference on Software Maintenance (ICSM)

作者： Junfeng Chen Kevin Li Yifei Chen Lili Wei Yepang Liu Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Department of Electrical and Computer Engineering McGill University Montreal Canada

ISBN: (数字)9798350395686

ISBN: (纸本)9798350395693

The Android ecosystem is profoundly fragmented due to the frequent updates of the Android system and the prevalent customizations by mobile device manufacturers. Previous research primarily focused on identifying and repairing evolution-induced API compatibility issues, with limited consideration of device-specific compatibillty issues (DSC issues). To fill this gap, we conduct an empirical study of 197 DSC issues collected from 94 open-source repositories on GitHub. We introduce a new perspective for comprehending these issues by categorizing them into two principal groups, Functionality Breaks, and OEM Features, based on their manifestations and root causes. The functionality break issues disrupt standard Android system behaviors, lead to crashes or unexpected behaviors on specific devices, and require developers to implement workarounds to preserve the original functionality. The OEM feature issues involve the introduction of device-specific functionalities or features beyond the basic Android system. The different nature of functionality break issues and OEM feature issues lead to unique challenges in addressing them. For example, our examination of issue fixing practices highlights significant differences in addressing the two categories of DSC issues. Common solutions for functionality break issues involve calling additional APIs, substituting problematic ones, or using specific parameters, while resolving OEM feature issues often relies on Android inter-component communication methods and reflection, with additional unconventional strategies. Such observations highlight the distinctive challenges in addressing DSC issues in Android apps and will facilitate the future development of testing and analysis tools targeting these issues. Our study demonstrates that Functionality break and OEM feature issues have different characteristics, and future research may need to investigate them separately.

关键词： Software maintenance Source coding Ecosystems Reflection Mobile handsets computer crashes Object recognition Standards Testing Software development management

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Do algorithms and barriers for sparse principal component analysis extend to other structured settings?

arXiv

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arXiv 2023年

作者： Wang, Guanyi Lou, Mengqi Pananjady, Ashwin Department of Industrial Systems Engineering and Management National University of Singapore Singapore Schools of Industrial and Systems Engineering United States Electrical and Computer Engineering Georgia Institute of Technology United States

We study a principal component analysis problem under the spiked Wishart model in which the structure in the signal is captured by a class of union-of-subspace models. This general class includes vanilla sparse PCA as well as its variants with graph sparsity. With the goal of studying these problems under a unified statistical and computational lens, we establish fundamental limits that depend on the geometry of the problem instance, and show that a natural projected power method exhibits local convergence to the statistically near-optimal neighborhood of the solution. We complement these results with end-to-end analyses of two important special cases given by path and tree sparsity in a general basis, showing initialization methods and matching evidence of computational hardness. Overall, our results indicate that several of the phenomena observed for vanilla sparse PCA extend in a natural fashion to its structured counterparts. Copyright © 2023, The Authors. All rights reserved.

关键词： Principal component analysis

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Analytical Model for Device Currents in 5-Level Active Neutral Point Clamped Converter

Analytical Model for Device Currents in 5-Level Active Neutr...

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International Conference on electrical systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： Daniel Zakzewski Rakesh Resalayyan Apurv Kumar Yadav Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory The Institute for Systems Research University of Maryland College Park United States Department of Electrical Engineering Indian Institute of Technology Roorkee Uttrakhand India

This paper presents a closed form analytical model for semiconductor and capacitor currents in a 5-Level Active Neutral Point Clamped Converter (5L-ANPC) topology. This model enables device selection, performance prediction, and design optimization of the topology. Models for the switch and FC currents are derived based on the topology's switching states. A model for input capacitor current is derived by analyzing the interaction of three phase legs of the topology. The model is verified using conventional time-domain switching simulation of the topology.

关键词： Semiconductor device modeling Analytical models Capacitors Transportation Stars Switches Predictive models

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FIXED-BUDGET DIFFERENTIALLY PRIVATE BEST ARM IDENTIFICATION

arXiv

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arXiv 2024年

作者： Chen, Zhirui Karthik, P.N. Chee, Yeow Meng Tan, Vincent Y.F. The Department of Industrial Systems Engineering and Management National University of Singapore Singapore The Institute of Data Science National University of Singapore Singapore The Department of Mathematics The Department of Electrical and Computer Engineering National University of Singapore Singapore

We study best arm identification (BAI) in linear bandits in the fixed-budget regime under differential privacy constraints, when the arm rewards are supported on the unit interval. Given a finite budget T and a privacy parameter Ε > 0, the goal is to minimise the error probability in finding the arm with the largest mean after T sampling rounds, subject to the constraint that the policy of the decision maker satisfies a certain Ε-differential privacy (Ε-DP) constraint. We construct a policy satisfying the Ε-DP constraint (called DP-BAI) by proposing the principle of maximum absolute determinants, and derive an upper bound on its error probability. Furthermore, we derive a minimax lower bound on the error probability, and demonstrate that the lower and the upper bounds decay exponentially in T, with exponents in the two bounds matching order-wise in (a) the sub-optimality gaps of the arms, (b) Ε, and (c) the problem complexity that is expressible as the sum of two terms, one characterising the complexity of standard fixed-budget BAI (without privacy constraints), and the other accounting for the Ε-DP constraint. Additionally, we present some auxiliary results that contribute to the derivation of the lower bound on the error probability. These results, we posit, may be of independent interest and could prove instrumental in proving lower bounds on error probabilities in several other bandit problems. Whereas prior works provide results for BAI in the fixed-budget regime without privacy constraints or in the fixed-confidence regime with privacy constraints, our work fills the gap in the literature by providing the results for BAI in the fixed-budget regime under the Ε-DP constraint. Copyright © 2024, The Authors. All rights reserved.

关键词： Decision making

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Efficient Model Training in Decentralized systems with Federated Learning 2

Efficient Model Training in Decentralized Systems with Feder...

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2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Rao, M.S. Srinivasa Saraswathy, S. Neela, V. Arun, M.R. Gupta, Sandeep Taqui, Syed Noeman Vignana Jyothi Institute of Engineering & Technology Vnr Department of Mechanical Engineering Telangana Hyderabad India Sri Sairam Engineering College Department of Computer Science and Business Systems Chennai India School of Computing and Information Technology Reva University Karnataka Bengaluru India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Department of Electrical Engineering Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Vlsi Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350369960

In the fast-changing field of machine learning, data privacy and model training efficiency are crucial. Federated Learning (FL) is a breakthrough method for training models on several decentralized devices or servers without centralizing raw data. This study examines Federated Learning's challenges in optimizing model training in dispersed systems. The first stage is to examine the Federated Learning (FL) framework and its merits, particularly in protecting data privacy and reducing server dependence. The next section will discuss communication overhead, stragglers, and non-IID (independent and identically distributed) data issues in a decentralized training model. We developed novel optimization methodologies and adaptive algorithms to improve Federated Learning (FL) efficiency. This includes updating asynchronous models, adaptability-based communication frequency, and non-IID data management. We also present a resilient aggregation method that mitigates Byzantine failures in participating nodes. We demonstrate that our methods improve convergence rate, communication costs, and model performance trained with Federated Learning (FL) by conducting a series of comprehensive experiments and analyzing real-world case studies. We show that these enhancements do not compromise data privacy, preserving Federated Learning (FL) principles. In conclusion, this study advances Federated Learning in decentralized systems. In an age of data sensitivity, this approach could help implement efficient, scalable, and privacy-preserving machine-learning methods. © 2023 IEEE.

关键词： Byzantine Failures Communication Efficiency Data Privacy Decentralized systems Federated Learning Model Training Non-IID Data

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