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20th IEEE Jubilee World Symposium on Applied Machine Intelligence and Informatics, SAMI 2022

作者： Csuzdi, Domonkos Toro, Oliver Aradi, Szilard Budapest University of Technology and Economics Department of Control Engineering and Information Technology Budapest Hungary Budapest University of Technology and Economics Department of Control for Transportation and Vehicle Systems Budapest Hungary

ISBN: (纸本)9781665497046

Nonlinear state estimation related to systems with high dimensional state spaces is a difficult problem that has theoretical and practical relevance. The performance of the Kalman filter is consistent in any dimension, however the same does not hold for the particle filters, due to the curse of dimensionality and particle degeneracy. The log-homotopy based particle flow filter, introduced in recent years is a promising approach to hard state estimation problems. This paper examines the applicability of the Daum-Huang particle flow filter in a challenging multi-target tracking scenario involving a nonlinear measurement model and compares it with conventional estimation methods. © 2022 IEEE.

关键词： Target tracking Atmospheric measurements Particle measurements Particle filters Mathematical models Proposals Kalman filters

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Improving Workplace Safety in the Cargo Industry through Posture Monitoring using Mediapipe and Machine Learning 17

Improving Workplace Safety in the Cargo Industry through Pos...

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17th International Conference on INnovations in Intelligent systems and Applications, INISTA 2023

作者： Cobb, Buket Sonbas Candan, Fethi Harran University Department of Electrical-Electronics Engineering Sanliurfa63190 Turkey University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom

ISBN: (纸本)9798350338904

This research reveals the potential of Mediapipe with machine learning methods in addressing the critical need for real-time posture monitoring, offering a promising solution for creating secure work environments and improving health and safety conditions not only in the cargo industry but also in other fields, such as healthcare, sports, and industry. The findings indicate that the Random Forest Classifier demonstrates the highest accuracy in classifying untrained movements, indicating its potential for developing a posture correction warning system. Further research is needed to validate the findings and explore real-world applications. Overall, this study contributes to the advancement of workplace safety and sets the foundation for future developments in posture monitoring systems using Mediapipe and machine learning using Python programming. © 2023 IEEE.

关键词： Python

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Enhancing 3D Human Skeleton Key-point Detection through Weakly Supervised Learning and Multi-level Attention Mechanisms

Enhancing 3D Human Skeleton Key-point Detection through Weak...

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2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Xu, Meng Gong, Yuanhao Dogramadzi, Sanja University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS10 2TN United Kingdom Shenzhen University Faculty of Electronics and Information Engineering China

ISBN: (纸本)9798350383386

With the soaring interest in understanding the dynamics of human body skeletons for applications such as action recognition and video understanding, the significance of precise 3D key-point detection has become increasingly prominent. Despite the advancements, existing approaches struggle to address the issues of occlusions and limited annotated data. This paper proposes a novel framework integrating a multilevel attention mechanism and weakly supervised 3D key-point generation to tackle these prevalent issues, enhancing both the accuracy and efficiency of human pose estimation. © 2023 IEEE.

关键词： Musculoskeletal system

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An Interacting Multiple Model Approach Based on Maximum Correntropy Student's T Filter

An Interacting Multiple Model Approach Based on Maximum Corr...

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

作者： Fethi Candan Aykut Beke Lyudmila Mihaylova Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Control Systems Design ASELSAN Ankara Turkiye

This paper presents a novel approach called the Interacting Multiple Model (IMM)-based Maximum Correntropy Student's T Filter (MCStF), which addresses the challenges posed by non-Gaussian measurement noises. The MCStF demonstrates superior performance compared to the IMM algorithm based on Kalman Filters (KFs) in both simulation environments and real-time systems. The Crazyflie 2.0 nano Unmanned Air Vehicle (UAV) model is used in the simulation validation, and results from 3000 independent Monte Carlo runs are shown. After getting the simulation results under monotonously changed non-Gaussian distribution, their performance results have been compared to each other. The same scenario has been applied in the real-time system using Crazyflie 2.0. Next, results from real-time tests are presented in which the position of Crazyflie 2.0 is estimated online.

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Weighting Attributes Based on the Greedy Algorithm Properties 28th

Weighting Attributes Based on the Greedy Algorithm Propertie...

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28th International Conference on Knowledge Based and Intelligent information and Engineering systems, KES 2024

作者： Zielosko, Beata Stanczyk, Urszula Jablonski, Kamil University of Silesia in Katowice Institute of Computer Science Bedzinska 39 Sosnowiec41-200 Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim was the development of a methodology for creating attribute rankings. Based on the properties of the greedy algorithm for inducing decision rules, a new application of this algorithm has been proposed. Instead of constructing a single ordering of features, attributes were weighted multiple times. The input datasets were discretised with several algorithms representing supervised and unsupervised discretisation approaches. Each resulting discrete data variant was exploited to construct a ranking of attributes. The effectiveness of the obtained rankings was confirmed through a rule filtering process governed by weighted attributes. The methodology was applied to the stylometric task of authorship attribution. The experimental outcomes demonstrate the value of the proposed research method, as it generally led to improved predictions while taking into account a noticeably decreased sets of attributes and decision rules. © 2024 The Authors.

关键词： Consensus algorithm

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Towards safe Bayesian optimization with Wiener kernel regression

arXiv

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arXiv 2024年

作者： Molodchyk, Oleksii Teutsch, Johannes Faulwasser, Timm Institute of Control Systems Hamburg University of Technology Hamburg21073 Germany Chair of Automatic Control Engineering Technical University of Munich Munich80333 Germany

Bayesian Optimization (BO) is a data-driven strategy for minimizing/maximizing black-box functions based on probabilistic surrogate models. In the presence of safety constraints, the performance of BO crucially relies on tight probabilistic error bounds related to the uncertainty surrounding the surrogate model. For the case of Gaussian Process surrogates and Gaussian measurement noise, we present a novel error bound based on the recently proposed Wiener kernel regression. We prove that under rather mild assumptions, the proposed error bound is tighter than bounds previously documented in the literature, leading to enlarged safety regions. We draw upon a numerical example to demonstrate the efficacy of the proposed error bound in safe BO. Copyright © 2024, The Authors. All rights reserved.

关键词： Gaussian distribution

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Using Optimal Filters for Plug-in Type Repetitive controllers for Periodic Inputs 28

Using Optimal Filters for Plug-in Type Repetitive Controller...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Diaconu, Larisa Vilanova, Ramon Barbu, Marian Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Universitat Autonoma de Barcelona Department of Telecommunications and Systems Engineering Barcelona Spain

ISBN: (纸本)9798350339918

This paper proposes some solutions to optimize the Butterworth filter from the structure of plug-in type repetitive controllers, as well as the use of the Bessel filter, which offers a simpler way of choosing the anticipatory factor from the repetitive controller structure. The comparative analysis of the two types of filters was made on the basis of three criteria: 1) the standard deviation of the error in the control loop, where the first type of filter proved to be superior;2) ease of obtaining the optimal value of the anticipative parameter, in which case the Bessel filter is preferred;3) sensitivity to changes in the filter parameters and/or process model, where the second filter is also preferred © 2023 IEEE.

关键词： Butterworth filters

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Cooperative Decision-Making in Shared Spaces: Making Urban Traffic Safer Through Human-Machine Cooperation 21

Cooperative Decision-Making in Shared Spaces: Making Urban T...

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21st IEEE International Symposium on Intelligent systems and Informatics, SISY 2023

作者： Varga, Balint Yang, Dongxu Martin, Manuel Hohmann, Soren Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany Department Interactive Analysis and Diagnosis Fraunhofer IOSB Karlsruhe Germany

ISBN: (纸本)9798350343366

In this paper, a cooperative decision-making is presented, which is suitable for intention-aware automated vehicle functions. With an increasing number of highly automated and autonomous vehicles on public roads, trust is a very important issue regarding their acceptance in our society. The most challenging scenarios arise at low driving speeds of these highly automated and autonomous vehicles, where interactions with vulnerable road users likely occur. Such interactions must be addressed by the automation of the vehicle. The novelties of this paper are the adaptation of a general cooperative and shared control framework to this novel use case and the application of an explicit prediction model of the pedestrian. An extensive comparison with state-of-the-art algorithms is provided in a simplified test environment. The proposed approach is also implemented on the experimental vehicle. The results show the superiority of the proposed model-based algorithm and its suitability for real-world applications. © 2023 IEEE.

关键词： Autonomous vehicles

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controller-Aware Dynamic Network Management for Industry 4.0 48

Controller-Aware Dynamic Network Management for Industry 4.0

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Balta, Efe C. Mamduhi, Mohammad H. Lygeros, John Rupenyan, Alisa Eth Zürich Automatic Control Laboratory Department of Information Technology and Electrical Engineering Zürich Switzerland

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In this paper, we consider a cyber-physical manufacturing system (CPMS) scenario containing physical components (robots, sensors, and actuators), operating in a digitally connected, constrained environment to perform industrial tasks. The CPMS has a centralized control plane with digital twins (DTs) of the physical resources, computational resources, and a network manager that allocates network resources. Existing approaches for the allocation of network resources are typically fixed with respect to controller-dependent run-time specifications, which may impact the performance of physical processes. We propose a dynamic network management framework, where the network resource allocation schemes are controller-aware. The information about the controllers of the physical resources is implemented at the DT level, and metrics, such as regret bounds, take the process performance measures into account. The proposed network management schemes optimize physical system performance by balancing the shared resources between the physical assets on the plant floor, and by considering their control requirements, providing a new perspective for dynamic resource allocation. A simulation study is provided to illustrate the performance of the proposed network management approaches and compare their resource allocation performance efficiencies. © 2022 IEEE.

关键词： controllers

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Creating and Studying a Methodology for Calculating a Resistive Voltage Divider for Use in Electronic Voltage Transformers

Creating and Studying a Methodology for Calculating a Resist...

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International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： A.A. Yablokov A.V. Panashchatenko E.E. Gotovkina R.A. Maltsev Electric power systems automatic control department Electric systems department Ivanovo State Power Engineering University Ivanovo Russia

ISBN: (数字)9798331501105

ISBN: (纸本)9798331501112

In 2017 the Russian government approved a programme, Russian Federation Digital Economy, the main goal of which is to create an ecosystem with large scale use of digital format data in all fields of social and economic activity [1]. The electric power industry is being transformed in accordance with the concept, Digital Transformation 2030, developed by Russian Power Grids PLC [2]. Pursuant to this concept, electric substations under construction should be digital. At present, Russia has a number of operating digital substations (DSS) (Medvedevskaya SS, UVAT SS, Desna SS, Tobol SS [3]–[5], while many DSSs are at the design or construction stage. The creation of new substations, and also reconstruction of already operating ones, requires solving the problems of operating conventional electromagnetic current and voltage transformers. Electromagnetic voltage transformers (VT) are energy-inefficient, explosion – and flammability- hazardous equipment (due to their requiring additional charging with low consumption by micro-processing devices), with large weight and dimensions (an NKF-100 type transformer weighing 840 kg).

关键词： Resistors Resistance Substations Voltage measurement Voltage transformers Biological system modeling Spread spectrum communication Transformers Integrated circuit modeling Electromagnetics

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