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Gaussian process-based visual pursuit control with unknown target motion learning in three dimensions

SICE Journal of Control, Measurement, and System Integration 2021年第1期14卷 116-127页

作者： Omainska, Marco Yamauchi, Junya Beckers, Thomas Hatanaka, Takeshi Hirche, Sandra Fujita, Masayuki Department of Information Physics and Computing The University of Tokyo Tokyo Japan Department of Electrical and Systems Engineering University of Pennsylvania PennsylvaniaPA United States Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan Department of Electrical and Computer Engineering Technical University of Munich Munich Germany

In this paper, we propose an observer-based visual pursuit control integrating three-dimensional target motion learning by Gaussian Process Regression (GPR). We consider a situation where a visual sensor equipped rigid body pursuits a target rigid body whose velocity is unknown but dependent on the target's pose. We estimate the pose from visual information and propose a Gaussian Process (GP) model to predict the target velocity from the pose estimate. We analyse stability of the proposed control by showing that estimation and control errors are ultimately bounded with high probability. Finally, simulations illustrate the performance of the proposed control schemes even if the visual measurement is corrupted by noise. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Gaussian distribution

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Compression with Unlabeled Graph Side information

Compression with Unlabeled Graph Side Information

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IEEE International Symposium on information Theory

作者： Hesam Nikpey Saswati Sarkar Shirin Saeedi Bidokhti Department of Computer and Information Science University of Pennsylvania Department of Electrical and Systems Engineering University of Pennsylvania

With the growth of big data in the past few decades, compression has become inseparable from data generation. The data generated daily across different platforms are correlated: friend networks on Facebook and Instagram, contact networks in subsequent days, and many more. This raises the question of compressing a dataset using another correlated dataset. For instance, can we compress the Facebook graph of friends when we know Instagram’s graph? This can be cast as the classical problem of source coding with side information, and the answer is known to be positive when the graphs are "labeled" and/or aligned, meaning we need to know the node corresponding to Jon Doe in both Facebook and Instagram graphs. The classical idea is to utilize joint typicality to decide whether two graphs are correlated or not. In practice, graphs are often not aligned and/or the labels are concealed to keep the identity of the users private. In these scenarios, classical ideas are no longer applicable as joint typicality highly depends on the ordering of sequences. In this work, we prove for the first time the existence of lossless graph compression schemes that utilize unlabeled side information and improve the compression rate. In order to do that, we design binning along with a novel testing criterion that relies on graph matching, the closely related quadratic assignment problem and its asymptotic properties.

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Robotic fish:Opening a new era of underwater detection

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The Innovation 2025年第3期6卷 13-14页

作者： Dongfang Li Suet To Zhicheng Xu Guanghong Liu Rob Law Edmond Q.Wu Limin Zhu State Key Laboratory of Ultraprecision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHong Kong 999077China School of Electrical Engineering and Automation Fuzhou UniversityFujian 350108China China Electronics Technology Group Corporation Information Science Research InstituteBeijing 100086China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Asia-Pacific Academy of Economics and Management Faculty of Business AdministrationUniversity of MacaoMacao 999078China Department of Computer Science and Engineering Shanghai JiaoTong UniversityShanghai 200240China

Escalating competition within aquatic environments,particularly in oceans,underscores the imperative for innovative solutions in underwater *** solutions necessitate the development of intelligent underwater equipment,with robotic fish emerging as a promising contender.1 Leveraging advancements in robotics and artificial intelligence,robotic fish offer a suite of advantages that position them as transformative assets in underwater exploration and *** fish are autonomous robots designed based on biomimetics principles that mimic the appearance of fish and can autonomously swim and perform specific tasks in water.

关键词： robotic fish intelligent underwater equipmentwith autonomous robots underwater detection oceans artificial intelligencerobotic fish aquatic environments innovative solutions

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Australia’s Power System Frequency: Current Situation, Industrial Challenges, Efforts, and Future Research Directions

TechRxiv

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TechRxiv 2023年

作者： Alhelou, Hassan Haes Bahrani, Behrooz Ma, Jin Hill, David J. The Department of Electrical and Computer Systems Engineering Monash University Australia The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia

This industry-oriented paper presents an overview and in-depth analysis of previous and current situations of power system frequency response and control in Australia. The evaluation of different services provided by different electricity market players under the supervision of the Australian Energy Market Operator (AEMO) as an independent system operator provides lessons and an understanding of the current operation status with its real challenges and opportunities from frequency stability and security perspectives. Based on the evaluation of the current situation and future national planning, a number of research gaps and industrial technical issues are identified, and some perspectives on future research directions are presented to help move the power system transformation toward almost 100% renewable and more secure energy systems. © 2023, CC BY.

关键词： Frequency response

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Consistent Scene Graph Generation by Constraint Optimization 22

Consistent Scene Graph Generation by Constraint Optimization

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Proceedings of the 37th IEEE/ACM International Conference on Automated Software engineering

作者： Boqi Chen Kristóf Marussy Sebastian Pilarski Oszkár Semeráth Daniel Varro Electrical and Computer Engineering McGill University Canada Deptartment of Measurement and Information Systems Budapest University of Technology and Economics Hungary Electrical and Computer Engineering McGill University Hungary

ISBN: (纸本)9781450394758

Scene graph generation takes an image and derives a graph representation of key objects in the image and their relations. This core computer vision task is often used in autonomous driving, where traditional software and machine learning (ML) components are used in tandem. However, in such a safety-critical context, valid scene graphs can be further restricted by consistency constraints captured by domain or safety experts. Existing ML approaches for scene graph generation focus exclusively on relation-level accuracy but provide little to no guarantee that consistency constraints are satisfied in the generated scene graphs. In this paper, we aim to complement existing ML-based approaches by a post-processing step using constraint optimization over probabilistic scene graphs that can (1) guarantee that no consistency constraints are violated and (2) improve the overall accuracy of scene graph generation by fixing constraint violations. We evaluate the effectiveness of our approach using well-known, and novel metrics in the context of two popular ML datasets augmented with consistency constraints and two ML-based scene graph generation approaches as baselines.

关键词： scene graph generation probabilistic logic programming machine learning constraint optimization consistency constraints

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Parameter fault estimation in distributed heating/cooling systems 22

Parameter fault estimation in distributed heating/cooling sy...

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Proceedings of the 7th International Conference on Sustainable information engineering and Technology

作者： Wijaya Kurniawan Katalin M. Hangos Lorinc Marton Faculty of Computer Science University of Brawijaya Indonesia) and Departement of Electrical Engineering and Information Systems University of Pannonia Hungary Departement of Electrical Engineering and Information Systems University of Pannonia Hungary and Institute for Computer Science and Control Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Romania)

ISBN: (纸本)9781450397117

In this paper, the problem of fault estimation and localization in the connecting dynamic elements of distributed heating and cooling systems are treated. The fault represents the physical parameter change related to the heat transfer between the system and the external environment. First, based on the bi-linear dynamic state space model of the system in the presence of a fault, structural observability analysis using Signed Directed Graph (SDG) has been performed to investigate the sensor placement problem. Then, a nonlinear observer with a parameter adaptation algorithm was proposed for fault estimation. The simulation results show that it can successfully detect and estimate the fault. Fault localization along the length of the element has also been attempted, but it has been found that the localization cannot be performed using practically changeable input variables. Frequency domain analysis is presented to discuss this phenomenon.

关键词： Nonlinear Observer Heating/cooling system Fault diagnosis Structural observability Parameter estimation

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Quality of Service (QoS)-Driven Edge Computing and Smart Hospitals: A Vision, Architectural Elements, and Future Directions 1

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NIELIT's International Conference on Communication, Electronics and Digital Technology, NICE-DT 2023

作者： Buyya, Rajkumar Srirama, Satish N. Mahmud, Redowan Goudarzi, Mohammad Ismail, Leila Kostakos, Vassilis Lab School of Computing and Information Systems The University of Melbourne Melbourne Australia School of Computer and Information Sciences The University of Hyderabad Hyderabad India School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia Lab Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

ISBN: (数字)9789819916993

ISBN: (纸本)9789819916986

The Internet of Things (IoT) paradigm is drastically changing our world by making everyday objects an integral part of the Internet. This transformation is increasingly being adopted in the healthcare sector, where Smart Hospitals are now relying on IoT technologies to track staff, patients, devices, and equipment, both within a hospital and beyond. This paradigm opens the door to new innovations for creating novel types of interactions among objects, services, and people in smarter ways to enhance the quality of patient services and the efficient utilisation of resources. However, the realisation of real-time IoT applications in health care and, ultimately, the development of Smart Hospitals are constrained by their current Cloud-based computing environment. Edge computing emerged as a new computing model that harnesses Edge-based resources alongside Clouds for real-time IoT applications. It helps to capitalise on the potential economic impact of the IoT paradigm of $11 trillion per year, with a trillion IoT devices deployed by 2025 to sense, manage, and monitor the hospital systems in real time. This vision paper proposes new algorithms and software systems to tackle important challenges in Edge computing-enabled Smart Hospitals, including how to manage and execute diverse real-time IoT applications and how to meet their diverse and strict Quality of Service (QoS) requirements in hospital settings. The vision we outline can help tackle timely challenges that hospitals increasingly face. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

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computer systems Science & engineering 2023年第5期45卷 1711-1726页

作者： Manar Ahmed Hamza Aisha Hassan Abdalla Hashim Dalia H.Elkamchouchi Nadhem Nemri Jaber S.Alzahrani Amira Sayed A.Aziz Mnahel Ahmed Ibrahim Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt College of Science and Humanities Studies in Alquwayiyah Shaqra UniversitySaudi Arabia

Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the *** the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the *** node clustering is a popular approach for ***,the sensor nodes are grouped to form clusters in a cluster-based WSN *** battery performance of the sensor nodes is likewise *** a result,the energy efficiency of WSNs is *** specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in *** the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was *** selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed *** provides the best routing path and increases the lifetime and energy efficiency of the ***-to-end delay and packet loss rate have also been *** proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor *** to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.

关键词： Wireless sensor networks energy-efficient load balancing energy consumption network’s lifetime cluster heads grey wolf optimization tabu search particle swarm optimization

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Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple Access Perspective

Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple...

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2024 IEEE Conference on Standards for Communications and Networking, CSCN 2024

作者： Agostini, Patrick Chamberland, Jean-Francois Clazzer, Federico Dommel, Johannes Liva, Gianluigi Munari, Andrea Narayanan, Krishna Polyanskiy, Yury Stanczak, Slawomir Utkovski, Zoran Fraunhofer Heinrich-Hertz-Institut Berlin Germany Texas A&M University College Station Dep. of Electrical and Computer Engineering TX United States Wessling Germany Massachusetts Institute of Technology Laboratory for Information and Decision Systems CambridgeMA United States

ISBN: (纸本)9798331507428

The ever increasing demand for massive connectivity, combined with the specific characteristics of machinegenerated wireless traffic, is pushing the existing solutions for device registration and data transfer beyond their operational limits. In this paper, we target specifically the 3GPP 5G New Radio random access channel, proposing some enhancements inspired by recent research results in the field of unsourced multiple access (UMAC). Aiming to enable massive grant-free connectivity for large machine-type and Internet of things terminals, we focus on modifications of the two-step random access procedures originally introduced in 3GPP Release 16. By means of simulations, we show that remarkable gains in both energy and spectral efficiency can be attained while retaining a strong resemblance to the legacy protocol. © 2024 IEEE.

关键词： 5G mobile communication systems

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Automated Wood Surface Defects Recognition System Using Yolov4-tiny Model

Automated Wood Surface Defects Recognition System Using Yolo...

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2023 Innovations in Power and Advanced Computing Technologies, i-PACT 2023

作者： Musa, Ahmad Muaz bin Momin, Md. Abdul Khairuddin, Anis Salwa Mohd Khairuddin, Uswah Ahmad, Azlin Rosli, Nenny Ruthfalydia Department of Electrical Engineering Faculty of Engineering Universiti Malaya Kuala Lumpur Malaysia Department of Mechanical Precision Engineering MJIIT Universiti Teknologi Malaysia Kuala Lumpur Malaysia Centre of Information Systems Studies Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Selangor Malaysia Universiti Teknologi Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798350325188

Wood surface detection is a process of identifying and locating wooden surfaces in an image or video using computer vision techniques. This technique can be used in various applications such as furniture manufacturing, construction, and lumber mills. Wood defect detection is an important task in the wood industry as it ensures the quality of wood products. In this study, YOLOv4-tiny algorithm is proposed to detect seven types of wood defects from wood texture images. Analysis was performed by applying several detection models to detect the wood defects. The performance of the proposed model is evaluated in terms of precision, recall, F1-score, and mAP. The algorithm has the potential to improve the efficiency and quality of the wood industry and could be applied to other similar tasks, such as identifying defects in other materials and products. © 2023 IEEE.

关键词： CNN deep learning defects wood images

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