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42nd Chinese Control Conference, CCC 2023

作者： Chen, Xinzhe Chen, Luefeng Hu, Jie Yang, Qingfeng Wu, Min Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada

ISBN: (纸本)9789887581543

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Informatization

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Tensor Least Mean Fourth Algorithm

Tensor Least Mean Fourth Algorithm

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Asilomar Conference on Signals, systems & computers

作者： Muhammad Moinuddin Azzedine Zerguine Electrical & Computer Engineering Department Center of Excellence in Intelligent Engineering Systems (CEIES) King Abdulaziz University Jeddah Saudi Arabia Department of Electrical Engineering Center for Communication Systems and Sensing (IRC-CSS) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

The tensor Least Mean Square (LMS) algorithm is a recent contribution in the field of adaptive algorithms whose aim is to provide better estimation in the presence of a large number of unknown parameters. This algorithm is designed by employing separability of linear operators on the standard LMS and by minimizing the standard stochastic gradient-based optimization of the Mean-Square-Error (MSE) cost function. Since the MSE criterion is known to have a superior performance in Gaussian environments only, the performance of the Tensor LMS is expected to degrade in non-Gaussian environments; while, the classical Least Mean Fourth (LMF) algorithm is known to have superior performance in non-Gaussian environments. In this work, a Tensor LMF algorithm which is designed by minimizing the Mean-Fourth-Error (MFE) criterion using the tensor factorization. We also provide the convergence in the mean sense of the proposed developed tensor LMF algorithm and found its stability bounds that ensure the convergence of the proposed algorithm. We provide various simulation experiments in different non-Gaussian environments to show the superiority of the proposed Tensor LMF algorithm over the Tensor LMS algorithm. For this purpose, examples of rank one two-way are presented. Simulation results are provided to validate our theoretical claims.

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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Accelerating Memory and I/O Intensive Hpc Applications Using Hardware Compressions

SSRN

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SSRN 2024年

作者： AlSaleh, Saleh Elrabaa, Muhammad E.S. El-Maleh, Aiman Daud, Khaled Hroub, Ayman Mudawar, Muhamed Tonellot, Thierry Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Electrical and Computer Engineering Birzeit University Ramallah Birzeit Palestine Saudi ARAMCO Dhahran Saudi Arabia

Recently, compression of intermediate data has been proposed to accelerate of memory and I/O intensive high-performance computing (HPC) applications. Accelerator-based com- pression/decompression is proposed to hide the storage latency of large intermediate data generated/consumed by the application that cannot fit in the node’s memory. In this work, such a scheme has been evaluated using several compression frameworks (CPU, GPU, and FPGA-based). A novel FPGA-based compression/decompression scheme was developed that completely overlaps the movement of the application’s data with the application’s compute kernels on the CPU. This yields applications’ performance levels on-par with utilizing memory-only storage buffers. A simple lossy compression scheme was developed and implemented. This scheme achieved ∼5X compression ratio at 2−6 or ∼1.5% relative error, which is similar to the best in-class compression techniques (at the same point-wise relative error). Experimental results showed that the new FPGA-based compression achieves application’s performance levels very close to using a memory buffer for intermediate data with significant speedup over direct disk storage. Experiments also showed that compared to CPU- and GPU-based compression frameworks, it achieves better performance levels at a fraction of the power consumption. © 2024, The Authors. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas systems

arXiv

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arXiv 2024年

作者： Liu, Rong-Peng Song, Yue Liu, Junhong Wang, Xiaozhe Guo, Jinpeng Hou, Yunhe The Department of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The Department of Energy and Electrical Engineering Ho-Hai University Jiangsu Nanjing China

This letter proposes a hidden convexity-based method to address distributed optimal energy flow (OEF) problems for transmission-level integrated electricity-gas systems. First, we develop a node-wise decoupling method to decompose an OEF problem into multiple OEF subproblems. Then, we propose a hidden convexity-based method to equivalently reformulate nonconvex OEF subproblems as semi-definite programs. This method differs from any approximation and convexification methods that may incur infeasible solutions. Since all OEF subproblems are originally convex or equivalently convexified, we adopt an ADMM to solve the hidden convexity-based distributed OEF problem with convergence analysis. Test results validate the effectiveness of the proposed method, especially in handling a large number of agents. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming

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Deep-subwavelength engineering of stealthy hyperuniformity

arXiv

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arXiv 2024年

作者： Park, Jusung Park, Seungkyun Kim, Kyuho Kwak, Jeonghun Yu, Sunkyu Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Inter-university Semiconductor Research Center SOFT Foundry Institute Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of

Light behaviours in disordered materials have been of research interest primarily at length scales beyond or comparable to the wavelength of light, because order and disorder are often believed to be almost indistinguishable in the subwavelength regime according to effective medium theory (EMT). However, it was recently demonstrated that the breakdown of EMT occurs even at deep-subwavelength scales when interface phenomena, such as the Goos-Hänchen effect, dominate light flows. Here we develop the engineering of disordered multilayers at deep-subwavelength scales to achieve angle-selective manipulation of wave localization. To examine the disorder-dependent EMT breakdown, we classify the intermediate regime of microstructural phases between deep-subwavelength crystals and uncorrelated disorder through the concept of stealthy hyperuniformity (SHU). In this classification, we devise nontrivial order-to-disorder transitions by selectively tailoring the short-range and long-range order in SHU multilayers, achieving angle-selective control of wave localization. The result paves the way to the realization of deep-subwavelength disordered metamaterials, bridging the gap between the fields of disordered photonics and metamaterials. © 2024, CC BY.

关键词： Multilayers

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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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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

引用

IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters State estimation intelligent sensors

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computer vision for road imaging and pothole detection:a state-of-the-art review of systems and algorithms

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Transportation Safety and Environment 2022年第4期4卷 3-18页

作者： Nachuan Ma Jiahe Fan Wenshuo Wang JinWu Yu Jiang Lihua Xie Rui Fan Department of Control Science and Engineering Frontiers Science Center for Intelligent Autonomous Systemsand State Key Laboratory of Intelligent Autonomous SystemsTongji UniversityShanghai 201804P.R.China Department of Civil Engineering McGill UniversityMontréalQC H3A 0C3Canada Department of Electronics and Computer Engineering the Hong Kong University of Science and TechnologyHong Kong SAR 999077P.R.China CTO Office ClearMotion Inc.BillericaMA 01821USA School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore

computer vision algorithms have been utilized for 3-D road imaging and pothole detection for over two ***,there is a lack of systematic survey articles on state-of-the-art(SoTA)computer vision techniques,especially deep learningmodels,developed to tackle these *** article first introduces the sensing systems employed for 2-D and 3-D road data acquisition,including camera(s),laser scanners and Microsoft *** then comprehensively reviews the SoTA computer vision algorithms,including(1)classical 2-D image processing,(2)3-D point cloud modelling and segmentation and(3)machine/deep learning,developed for road pothole *** article also discusses the existing challenges and future development trends of computer vision-based road pothole detection approaches:classical 2-D image processing-based and 3-D point cloud modelling and segmentation-based approaches have already become history;and convolutional neural networks(CNNs)have demonstrated compelling road pothole detection results and are promising to break the bottleneck with future advances in self/un-supervised learning for multi-modal semantic *** believe that this survey can serve as practical guidance for developing the next-generation road condition assessment systems.

关键词： computer vision road imaging pothole detection deep learning image processing point cloud modelling convolutional neural networks

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Contactless Interaction System Based on Facial Expression Recognition for Humanoid Piano Robot

Contactless Interaction System Based on Facial Expression Re...

引用

IEEE International Conference on robotics and Biomimetics

作者： Ling Zhong Wen Wang Shiqiang Zhu Shanshan Ji Changhai Zha Minhong Wan Jason Gu Zhejiang Lab Research Center for Intelligent Robotics Zhejiang Engineering Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

With the wide application of service robots in people's daily life, people are not only satisfied with robots accomplishing tasks independently but also hope that robots can maintain sustainable interaction with human beings. Especially in the field of music, robots need to be equipped with intelligent cognitive skills in decision-making, so that the audience can enjoy immersive appreciation and emotional resonance in the robots performance. Visual perception and natural language understanding are essential for robots to establish human-robot friendly relationships. To enrich the interactive ability of music robots, we design a contactless interaction system based on facial expression recognition, which consists of four modules: voice wake-up, face detection, facial expression recognition, and music mapping. When people wake up the music robot with specific words, the robot will customize appropriate music to perform according to the recognition results of the FER module. As a final step, the interaction system has been successfully applied to the piano humanoid robot independently developed by our team.

关键词： Industries Service robots Face recognition Humanoid robots Speech recognition Natural language processing Pensions

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