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47th ICT and Electronics Convention, MIPRO 2024

作者： Marković, Milorad Kaštelan, Ivan University Of Novi Sad Department Of Computing And Control Engineering Sub-department Of Computer Engineering And Communications Novi Sad Serbia

ISBN: (纸本)9798350382495

Visualization is a powerful tool for learning and teaching complex concepts, especially in the field of computer science. However, creating effective and engaging visualizations can be challenging and time-consuming for educators and students. This paper demonstrates how the Manim Python library, a free and open-source project for creating mathematical animations, can be used to create visualizations that illustrate algorithms and data structures in an undergraduate course. The paper showcases several examples of visualizations created with the Manim library, and explains how they help the students to understand the logic, behavior, and performance of the algorithms and data structures. The paper also discusses the benefits and limitations of the Manim library, and suggests some directions for future research and development. © 2024 IEEE.

关键词： Python

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control Strategy based on Frequency Response for a Single-Phase Full- Bridge Series Active Filter 16

Control Strategy based on Frequency Response for a Single-Ph...

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16th Brazilian Power Electronics Conference, COBEP 2021

作者： Curi Busarello, Tiago Davi Automation and Computing Engineering Federal University of Santa Catarina Department of Control Blumenau Brazil

ISBN: (纸本)9781665421294

Series active filters are a mature technology and well covered in the literature. However, they are usually designed for three-phase systems employing control strategies in dq-rotating reference frame. As a result, proportional-integrator controllers are used. However, they are not suited when the system has abnormal conditions. Moreover, with the high penetration of distribution generators, single-phase distribution voltage is being deteriorated. This paper presents a control strategy based on frequency response for a single-phase full bridge series active filter. The series active filter is controlled in voltage mode through a digital lead-lag controller. The controller parameters are obtained by frequency response technique using the k-factor methodology and later discretized via Backward-Euler approximation. The series active filter is tested in a system with nonlinear loads, distortions at the distribution voltage and under disturbance at the DC-link. The proposal was verified under simulation results and under Hardware-in-Loop Typhoon HIL402 with external microcontroller TMS320F28335. Results showed the effectiveness of the proposed control strategy. © 2021 IEEE.

关键词： Active filters

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Automatic modelling and analysis of dynamic physical systems using qualitative reasoning and bond graphs

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Intelligent systems engineering 1993年第3期2卷 201-212页

作者： Xia, S. Linkens, D.A. Bennett, S. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK School of Computing and Mathematical Sciences De Montfort University Milton Keynes UK

A good model is essential in simulating and analyzing a system satisfactorily. This paper proposes a new computer-aided modelling methodology to construct parsimonious models for dynamic physical systems. A set of domain-independent modelling principles and domain-dependent modelling constraints has been formulated to guide parsimonious model construction. Models and the knowledge base for the enhancement of models have been described by bond graphs. After a parsimonious model is generated, two types of qualitative analysis are conducted;one is to derive unknown states from known states and the other is to predict the effects of parameter changes on the whole system. This methodology is only applicable when the structure of a dynamic system is known beforehand. A detailed case study is presented to demonstrate this approach.

关键词： Systems analysis

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Angular Speed control of Brushed DC Motor Using Nonlinear Method: Design and Experiment 35

Angular Speed Control of Brushed DC Motor Using Nonlinear Me...

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第35届中国控制会议

作者： ZHANG Sen GU Wanli HU Yunfeng DU Juan CHEN Hong Department of Control Science and Engineering Jilin University State Key Laboratory of Automotive Simulation and Control Jilin University Computing Center of Jilin Province

ISBN: (纸本)9781509009107

The major concentration of this study is on developing a novel control system with response and tracking accuracy features capable of precise angular speed regulation of brushed DC motor. Towards this objective, speed loop controller of brushed DC motor based on Triple-step nonlinear method has been designed. The Triple-step nonlinear method consists of the steady-state control, the reference variation-based feed-forward control, the error feedback control. The designed nonlinear controller has the advantage of concision and specific signification. The controller can greatly enhance the transient response performance of brushed DC motor. When a brushed DC motor running at low angular speed, the system appears the speed fluctuation and dead-zone characteristic. Therefore, the friction model of motor is considered in the design of controller. Current dynamic is neglected due to the fast electric response, the commonly used feedforward controller and PI feedback controller is designed. The effectiveness of the control method compared with conventional PID controllers is verified through experiments.

关键词： Brushed DC Motor Triple-step Method Friction model Angular Speed control

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A RELIABLE AND EFFICIENT LINEAR-PROGRAMMING ALGORITHM FOR 2-LEVEL POWER-SYSTEM STATE ESTIMATION

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ELECTRIC POWER SYSTEMS RESEARCH 1988年第1期14卷 51-60页

作者： LO, KL SALEM, MM Power Systems Research Group Department of Electronic and Electrical Engineering University of Strathclyde 204 George Street Glasgow Scotland U.K. Control and Computing Engineering Faculty of Engineering El-Mansoura University El-Mansoura Egypt

Two linear programming (LP) algorithms for the integrated state estimation (ISE) for the whole system are formulated and tested. It was found that a direct application of an ISE on a large power system suffers certain limitations. This paper presents an efficient and reliable two-level state estimator (TLSE) based on LP techniques. Both the ISE and the proposed TLSE were tested under different conditions. The results are discussed and comparisons are given which show that the TLSE has many advantages over the ISE.

关键词： ELECTRIC POWER SYSTEMS

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Enhancing Collaborative and Geometric Multi-Kernel Learning Using Deep Neural Network

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Computers, Materials & Continua 2022年第9期72卷 5099-5116页

作者： Bareera Zafar Syed Abbas Zilqurnain Naqvi Muhammad Ahsan Allah Ditta Ummul Baneen Muhammad Adnan Khan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54890Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department Software Gachon UniversitySeongnam13120Korea

This research proposes a method called enhanced collaborative andgeometric multi-kernel learning (E-CGMKL) that can enhance the CGMKLalgorithm which deals with multi-class classification problems with non-lineardata distributions. CGMKL combines multiple kernel learning with softmaxfunction using the framework of multi empirical kernel learning (MEKL) inwhich empirical kernel mapping (EKM) provides explicit feature constructionin the high dimensional kernel space. CGMKL ensures the consistent outputof samples across kernel spaces and minimizes the within-class distance tohighlight geometric features of multiple classes. However, the kernels constructed by CGMKL do not have any explicit relationship among them andtry to construct high dimensional feature representations independently fromeach other. This could be disadvantageous for learning on datasets with complex hidden structures. To overcome this limitation, E-CGMKL constructskernel spaces from hidden layers of trained deep neural networks (DNN).Due to the nature of the DNN architecture, these kernel spaces not onlyprovide multiple feature representations but also inherit the compositionalhierarchy of the hidden layers, which might be beneficial for enhancing thepredictive performance of the CGMKL algorithm on complex data withnatural hierarchical structures, for example, image data. Furthermore, ourproposed scheme handles image data by constructing kernel spaces from aconvolutional neural network (CNN). Considering the effectiveness of CNNarchitecture on image data, these kernel spaces provide a major advantageover the CGMKL algorithm which does not exploit the CNN architecture forconstructing kernel spaces from image data. Additionally, outputs of hiddenlayers directly provide features for kernel spaces and unlike CGMKL, do notrequire an approximate MEKL framework. E-CGMKL combines the consistency and geometry preserving aspects of CGMKL with the compositionalhierarchy of kernel spaces extracted from DNN hidde

关键词： CGMKL multi-class classification deep neural network multiplekernel learning hierarchical kernel spaces

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Software for Small-scale Robotics: A Review

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International Journal of Automation and computing 2018年第5期15卷 515-524页

作者： Tobias Tiemerding Sergej Fatikow Department of Computing Science Division Microrobotics and Control Engineering (AMiR) University of Oldenburg OFFIS–Institute for Information Technology R&D Division Automation and Integration Technology (AIT)

In recent years, a large number of relatively advanced and often ready-to-use robotic hardware components and systems have been developed for small-scale use. As these tools are mature, there is now a shift towards advanced applications. These often require automation and demand reliability, efficiency and decisional autonomy. New software tools and algorithms for artificial intelligence（AI） and machine learning（ML） can help here. However, since there are many software-based control approaches for small-scale robotics, it is rather unclear how these can be integrated and which approach may be used as a starting point. Therefore, this paper attempts to shed light on existing approaches with their advantages and disadvantages compared to established requirements. For this purpose, a survey was conducted in the target group. The software categories presented include vendor-provided software, robotic software frameworks（RSF）, scientific software and in-house developed software（IHDS）. Typical representatives for each category are described in detail, including Smar Act precision tool commander, Math Works Matlab and national instruments Lab VIEW, as well as the robot operating system（ROS）. The identified software categories and their representatives are rated for end user satisfaction based on functional and non-functional requirements, recommendations and learning curves. The paper concludes with a recommendation of ROS as a basis for future work.

关键词： Robotic control software engineering micro/nano robotics artificial intelligence （AI） machine learning （ML） open

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Compliant net for AUV retrieval using a UAV

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IFAC-PapersOnLine 2018年第29期51卷 431-437页

作者： Ivanovic, Antun Polic, Marsela Salah, Omar Orsag, Matko Bogdan, Stjepan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb10 000 Croatia Mechanical Engineering Department Faculty of Engineering Assiut University Assiut Egypt

This paper addresses the problem of retrieving an autonomous underwater vehicle (AUV) with an unmanned aerial vehicle (UAV). The design of the compliant net that naturally adapts to the payload morphology is proposed as a retrieval tool. We constructed the proposed compliant net and conducted experiments with an underwater vehicle model as payload. Furthermore, mathematical model of a system comprised of the UAV and the payload is presented and a mid-ranging controller is utilized for such a system. We also present simulation results and analyze the stability of the UAV with the cable attached payload. © 2018

关键词： Autonomous underwater vehicles Antennas Unmanned aerial vehicles (UAV) Autonomous underwater vehicles (AUV) Marine systems Mechanical design Retrieval tool Soft robotics Underwater vehicles

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Unmanned marsupial sea-air system for object recovery 22

Unmanned marsupial sea-air system for object recovery

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22nd Mediterranean Conference on control and Automation, MED 2014

作者： Miskovic, Nikola Bogdan, Stjepan Nad, Eula Mandic, Filip Orsag, Matko Haus, Tomislav University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Unska 3 Zagreb Croatia

ISBN: (纸本)9781479959006

This paper presents preliminary results obtained from a cooperative heterogeneous system consisting of an unmanned surface marine vehicle (USV) and an unmanned aerial vehicle (UAV). The envisioned scenario for this marsupial system is unmanned recovery of objects floating at the sea surface. The specific mission that is addressed in this paper includes the following phases: coarse approach where the USV approaches the object area using navigation filter based on GPS measurements;fine approach where the UAV tracking the USV sends relative distances between the USV and the object which is visible in the UAV's field of view;and tugging where the USV takes the object to safety after the initial contact has been achieved. The paper describes the ROS-based control architecture, presents simulation results, and addresses control issues related to obtaining measurements from two sources with different variances. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

arXiv

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arXiv 2025年

作者： Luo, Gongning Xu, Mingwang Chen, Hongyu Liang, Xinjie Tao, Xing Ni, Dong Jeong, Hyunsu Kim, Chulhong Stock, Raphael Baumgartner, Michael Kirchhoff, Yannick Rokuss, Maximilian Maier-Hein, Klaus Yang, Zhikai Fan, Tianyu Boutry, Nicolas Tereshchenko, Dmitry Moine, Arthur Charmetant, Maximilien Sauer, Jan Du, Hao Bai, Xiang-Hui Raikar, Vipul Pai Montoya-Del-Angel, Ricardo Martí, Robert Luna, Miguel Lee, Dongmin Qayyum, Abdul Mazher, Moona Guo, Qihui Wang, Changyan Awasthi, Navchetan Zhao, Qiaochu Wang, Wei Wang, Kuanquan Wang, Qiucheng Dong, Suyu School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Department of Mathematics Faculty of Science National University of Singapore Singapore National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen University Shenzhen China Laboratory Shenzhen University Shenzhen China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China Pohang Korea Republic of Heidelberg Division of Medical Image Computing Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Germany Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany Department of Biomedical Engineering and Health KTH Royal Institute of Technology Stockholm Sweden France FathomX Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Philips Research University of Girona Spain Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Interdisciplinary Studies of Artificial Intelligence DGIST Korea Republic of National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Lab School of Communication and Information Engineering Shanghai University Shanghai China Faculty of Science Mathematics and Computer Science Informatics Institute University of Amsterdam Amsterdam1090 GH Netherlands Department of Biomedical Engineering and Physics Amsterdam UMC Amsterdam1081 HV Netherlands Xi’an Jiaotong-Liverpool University China Department of Ultrasound Harbin Medical University Cancer Hospital No. 150 Haping Road Nangang

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher detection rate of breast cancer. Tumor detection, segmentation, and classification are key components in the analysis of medical images, especially challenging in the context of 3D ABUS due to the significant variability in tumor size and shape, unclear tumor boundaries, and a low signal-to-noise ratio. The lack of publicly accessible, well-labeled ABUS datasets further hinders the advancement of systems for breast tumor analysis. Addressing this gap, we have organized the inaugural Tumor Detection, Segmentation, and Classification Challenge on Automated 3D Breast Ultrasound 2023 (TDSC-ABUS2023). This initiative aims to spearhead research in this field and create a definitive benchmark for tasks associated with 3D ABUS image analysis. In this paper, we summarize the top-performing algorithms from the challenge and provide critical analysis for ABUS image examination. We offer the TDSC-ABUS challenge as an open-access platform at https://***/ to benchmark and inspire future developments in1algorithmic research. © 2025, CC BY.

关键词： Image segmentation

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