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Multi-variant scheduling of critical time-triggered communication in incremental development process: Application to FlexRay

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arXiv 2019年

作者： Dvořák, Jan Hanzálek, Zdeněk Department of Control Engineering Faculty of Electrical Engineering CTU in Prague Industrial Informatics Research Center Czech Institute of Informatics Robotics and Cybernetics CTU in Prague

The portfolio of models offered by car manufacturing groups often includes many variants (i.e., different car models and their versions). With such diversity in car models, variant management becomes a formidable task. Thus, there is an effort to keep the variants as close as possible. This simple requirement forms a big challenge in the area of communication protocols. When several vehicle variants use the same signal, it is often required to simultaneously schedule such a signal in all vehicle variants. Furthermore, new vehicle variants are designed incrementally in such a way as to maintain backward compatibility with the older vehicles. Backward compatibility of time-triggered schedules reduces expenses relating to testing and fine-tuning of the components that interact with physical environment (e.g., electromagnetic compatibility issues). As this requirement provides for using the same platform, it simplifies signal traceability and diagnostics, across different vehicle variants, besides simplifying the reuse of components and tools. This paper proposes an efficient and robust heuristic algorithm, which creates the schedules for internal communication of new vehicle variants. The algorithm provides for variant management by ensuring compatibility among the new variants, besides preserving backward compatibility with the preceding vehicle variants. The proposed method can save about 20% of the bandwidth with respect to the schedule common to all variants. Based on the results of the proposed algorithm, the impact of maintaining compatibility among new variants and of preserving backward compatibility with the preceding variants on the scheduling procedure is examined and discussed. Thanks to the execution time of the algorithm, which is less than one second, the network parameters like the frame length and cycle duration are explored to find their best choice concerning the schedule feasibility. Finally, the algorithm is tested on benchmark sets and the concept

关键词： Scheduling

FSD-10: A dataset for competitive sports content analysis

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arXiv 2020年

作者： Liu, Shenglan Liu, Xiang Huang, Gao Feng, Lin Hu, Lianyu Jiang, Dong Zhang, Aibin Liu, Yang Qiao, Hong Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China Faculty of Tsinghua University of Technology Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep learning, such process has been slow in competitive sports content analysis. To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for finegrained sports content analysis. To this end, we collect 1484 clips from the worldwide figure skating championships in 2017-2018, which consist of 10 different actions in men/ladies programs. Each clip is at a rate of 30 frames per second with resolution 1080 × 720. These clips are then annotated by experts in type, grade of execution, skater info,.etc. To build a baseline for action recognition in figure skating, we evaluate state-of-the-art action recognition methods on FSD-10. Motivated by the idea that domain knowledge is of great concern in sports field, we propose a keyframe based temporal segment network (KTSN) for classification and achieve remarkable performance. Experimental results demonstrate that FSD-10 is an ideal dataset for benchmarking action recognition algorithms, as it requires to accurately extract action motions rather than action poses. We hope FSD-10, which is designed to have a large collection of finegrained actions, can serve as a new challenge to develop more robust and advanced action recognition models. Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

Short-Term Photovoltaic Power Prediction Modeling Based on AdaBoost Algorithm and Elman

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Short-Term Photovoltaic Power Prediction Modeling Based on A...

IEEE International Conference on Power and Energy Systems (ICPES)

作者： Wenxuan Sun Tao Zhang Ran Tao Anna Wang College Of Information Science and Engineering Northeastern University Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781665404945

ISBN: (纸本)9781665404952

In recent years, with the rapid expansion of the installed capacity of renewable energy systems, the availability, stability and quality of smart grids have become increasingly important [1] . The application of renewable energy production forecasting has also been rapidly developed, especially in the field of solar photovoltaic (PV) [2][3] . In the example of solar PV output prediction, machine learning and hybrid technologies have been implemented for many applications. In this paper, a high-precision PV system output power prediction model based on improved AdaBoost and Elman is proposed. Multiple model using integrated AdaBoost algorithm fusion with the bat algorithm for the parameters of optimized combination of weak Elman neural network predictor to become a higher prediction precision, the method of strong predictor of the model can according to the weather information, such as temperature, solar radiation and the history of the output of the PV system data, the probability of photovoltaic power generation for 12 hours and deterministic prediction. The prediction accuracy of the model is determined by Root Mean Squared Error (RMSE). Experimental results show that the prediction accuracy of this algorithm is better than that of other benchmark models, and the algorithm can effectively predict the volatility and irregularity of complex time series.

关键词： Photovoltaic systems Renewable energy sources Machine learning algorithms Machine learning Predictive models Prediction algorithms Numerical models

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

Lecture Notes in Control and Information Sciences

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Preface

Lecture Notes in control and information Sciences 2021年 485卷 v-viii页

作者： Faulwasser, Timm Müller, Matthias A. Worthmann, Karl Department of Electrical Engineering and Information Technology Institute of Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Dortmund Germany Faculty of Electrical Engineering and Computer Science Institute of Automatic Control Leibniz University Hannover Hannover Germany Faculty of Mathematics and Natural Sciences Institute for Mathematics Optimization-based Control Technische Universität Ilmenau Ilmenau Germany

Saturated Continuous Twisting Algorithm 15

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Saturated Continuous Twisting Algorithm

15th International Workshop on Variable Structure Systems, VSS 2018

作者： Golkani, M.A. Fridman, L.M. Koch, S. Reichhartinger, M. Horn, M. Faculty of Electrical and Information Engineering Graz University of Technology Institute of Automation and Control Graz Austria Department of Control Engineering and Robotics Division of Electrical Engineering Engineering Faculty National Autonomous University of Mexico Mexico D.F. Mexico Institute of Automation and Control Graz University of Technology Christian Doppler Laboratory for Model Based Control of Complex Test Bed Systems Graz Austria

ISBN: (纸本)9781538664391

In this paper, a second-order system affected by perturbations is considered. A feedback control law adopting the continuous twisting algorithm is designed such that a saturated and continuous control signal is introduced to the system. In the case that a state variable is not measurable, estimate information obtained through a super-twisting observer is incorporated into the design. For the closed-loops (with and without observer), global finite-time stability properties are established. The feasibility and effectiveness of the strategy is shown employing numerical simulations. © 2018 IEEE.

关键词： Stability

White paper on broadband connectivity in 6G

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arXiv 2020年

作者： Rajatheva, Nandana Atzeni, Italo Björnson, Emil Bourdoux, André Buzzi, Stefano Doré, Jean-Baptiste Erkucuk, Serhat Fuentes, Manuel Guan, Ke Hu, Yuzhou Huang, Xiaojing Hulkkonen, Jari Jornet, Josep Miquel Katz, Marcos Nilsson, Rickard Panayirci, Erdal Rabie, Khaled Rajapaksha, Nuwanthika Salehi, MohammadJavad Sarieddeen, Hadi Svensson, Tommy Tervo, Oskari Tölli, Antti Wu, Qingqing Xu, Wen Centre for Wireless Communications University of Oulu Finland Linköping University Sweden IMEC Belgium Department of Electrical and Information Engineering University of Cassino and Southern Latium Italy CEA-Leti France Department of Electrical and Electronics Engineering Kadir Has University Turkey Institute of Telecommunications and Multimedia Applications Universitat Politecnica de Valencia Spain State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications China Algorithm Department ZTE Corporation China School of Electrical and Data Engineering Faculty of Engineering and Information Technology University of Technology Sydney Australia Nokia Bell Labs Finland Department of Electrical and Computer Engineering Institute for the Wireless Internet of Things Northeastern University United States Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden Department of Engineering Manchester Metropolitan University United Kingdom Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Saudi Arabia Department of Electrical Engineering Chalmers University of Technology Sweden Department of Electrical and Computer Engineering National University of Singapore Singapore Huawei Technologies Germany

This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h. To achieve these goals, not only the terrestrial networks will be evolved but they will also be integrated with satellite networks, all facilitating autonomous systems and various interconnected structures. We believe that several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric and scalable cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be used for pushing the peak rates of point-to-point links. The latter path will lead to THz communications complemented by visible light communications in specific scenarios. At the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latencies, higher reliability, and reduced complexity. Different options will be needed to optimally support different use cases. The resource efficiency can be further improved by using various combinations of full-duplex radios, interference management based on rate-splitting, machine-learning-based optimization, coded caching, and broadcasting. Finally, the three levels of enablers must be utilized not only to deliver better broadband services in urban areas, but also to provide full-coverage broadband connectivity must be one of the k

关键词： Visible light communication

Dark photon constraints from a 7.139 GHz cavity haloscope experiment

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arXiv 2024年

作者： He, Dong Fan, Jie Gao, Xin Gao, Yu Houston, Nick Ji, Zhongqing Jin, Yirong Li, Chuang Li, Jinmian Li, Tianjun Liu, Shi-Hang Niu, Jia-Shu Peng, Zhihui Sun, Liang Sun, Zheng Wang, Jia Wei, Puxian Wu, Lina Xiang, Zhongchen Yang, Qiaoli Zhang, Chi Zhang, Wenxing Zhang, Xin Zheng, Dongning Zheng, Ruifeng Zhou, Jian-Yong Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Institute of Physics Chinese Academy of Sciences Beijing100190 China College of Physics Sichuan University Chengdu610065 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Institute of Theoretical Physics Faculty of Science Beijing University of Technology Beijing100124 China Beijing Academy of Quantum Information Sciences Beijing100193 China College of Mechanical and Electrical Engineering Wuyi University Nanping354300 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China School of Physical Sciences University of Chinese Academy of Sciences No. 19A Yuquan Road Beijing100049 China Institute of Theoretical Physics Shanxi University Taiyuan030006 China College of Physics and Optoelectronic Engineering Department of Physics Jinan University Guangzhou510632 China School of Sciences Xi’an Technological University Xi’an710021 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China National Astronomical Observatories Chinese Academy of Sciences 20A Datun Road Chaoyang District Beijing100101 China School of Astronomy and Space Science University of Chinese Academy of Sciences Beijing100049 China

The dark photon is a promising candidate for the dark matter which comprises most of the matter in our visible Universe. Via kinetic mixing with the Standard Model it can also be resonantly converted to photons in an electromagnetic cavity, offering novel experimental possibilities for the discovery and study of dark matter. We report the results of a pathfinder dark photon dark matter cavity search experiment performed at Hunan Normal University and the institute of Physics, Chinese Academy of Sciences, representing the first stage of the APEX (Axion and dark Photon EXperiment) program. Finding no statistically significant excess, we place an upper limit on the kinetic mixing parameter |χ| −13 around mA 29.5 µeV at 90% confidence level. This result exceeds other constraints on dark photon dark matter in this frequency range by roughly an order of magnitude. Copyright © 2024, The Authors. All rights reserved.

关键词： Photons

Calibration of the Cryogenic Measurement System of a Resonant Haloscope Cavity

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arXiv 2024年

Possible light bosonic dark matter interactions with the Standard Model photon have been searched by microwave resonant cavities. In this paper, we demonstrate the cryogenic readout system calibration of a 7.138 GHz copper cavity with a loaded quality factor Ql = 104, operated at 22 mK temperature based on a dilution refrigerator. Our readout system consists of High Electron Mobility Transistors as cryogenic amplifiers at 4 K, plus room-temperature amplifiers and a spectrum analyzer for signal power detection. We test the system with a superconducting two-level system as a single-photon source in the microwave frequency regime and report an overall 95.6 dB system gain and -71.4 dB attenuation in the cavity’s input channel. The effective noise temperature of the measurement system is 7.5 K. © 2024, CC BY.

关键词： Spectrum analyzers