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arXiv 2018年

作者： Yang, Insoon Department of Electrical and Computer Engineering Automation and Systems Research Institute Seoul National University

Standard stochastic control methods assume that the probability distribution of uncertain variables is available. Unfortunately, in practice, obtaining accurate distribution information is a challenging task. To resolve this issue, we investigate the problem of designing a control policy that is robust against errors in the empirical distribution obtained from data. This problem can be formulated as a two-player zero-sum dynamic game problem, where the action space of the adversarial player is a Wasserstein ball centered at the empirical distribution. We propose computationally tractable value and policy iteration algorithms with explicit estimates of the number of iterations required for constructing an ∊-optimal policy. We show that the contraction property of associated Bellman operators extends a single-stage out-of-sample performance guarantee, obtained using a measure concentration inequality, to the corresponding multi-stage guarantee without any degradation in the confidence level. In addition, we characterize an explicit form of the optimal distributionally robust control policy and the worst-case distribution policy for linear-quadratic problems with Wasserstein penalty. Our study indicates that dynamic programming and Kantorovich duality play a critical role in solving and analyzing the Wasserstein distributionally robust stochastic control problems. Copyright © 2018, The Authors. All rights reserved.

关键词： Robust control

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Intensive summer course in robotics – Robotcraft

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Applied Computing and Informatics 2018年第1-2期16卷 155-179页

作者： Ferreira, N.M. Fonseca Araujo, André Couceiro, M.S. Portugal, David Department of Electrical Engineering (DEE) Engineering Institute of Coimbra (ISEC) Polytechnic of Coimbra (IPC) Rua Pedro Nunes – Quinta da Nora Coimbra Portugal GECAD - Knowledge Research Group on Intelligent Engineering and Computing for Advanced Innovation Development of the Engineering Institute of Porto (ISEP) Polytechnic Institute of Porto (IPP) Porto Portugal INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Ingeniarius Lda Coimbra Portugal

This paper describes a two-month summer intensive course designed to introduce participants with a hands-on technical craft on robotics and to acquire experience in the low-level details of embedded systems. Attendants started this course with a brief introduction to robotics;learned to draw, design and create a personalized 3D structure for their mobile robotic platform and developed skills in embedded systems. They were familiarize with the practices used in robotics, learning to connect all sensors and actuator, developing a typical application on differential kinematic using Arduino, exploring ROS features under Raspberry Pi environment and Arduino – Raspberry Pi communication. Different paradigms and some real applications and programming were addressed on the topic of Artificial Intelligence. Throughout the course, participants were introduced to programming languages (including Python and C++), advanced programming concepts such as ROS, basic API development, system concepts such as I2C and UART serial interfaces, PWM motor control and sensor fusion to improve robotic navigation and localization. This paper describes not just the concept, layout and methodology used on RobotCraft 2017 but also presents the participants knowledge background and their overall opinions, leading to focus on lessons learned and suggestions for future editions. © 2018, N.M. Fonseca Ferreira, André Araujo, M.S. Couceiro and David Portugal.

关键词： International trends in educational robotics Project-based learning ROS

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Semidefinite relaxation-based optimization of Yagi-Uda array antennas 12

Semidefinite relaxation-based optimization of Yagi-Uda array...

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12th European Conference on Antennas and Propagation, EuCAP 2018

作者： Lang, Hans-Dieter Sarris, Costas D. ICOM - Institute for Communication Systems HSR Hochschule für Technik Rapperswil Rapperswil Switzerland Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoON Canada

ISBN: (纸本)9781785617911

The semidefinite relaxation-based optimization framework developed for finding the physical limits on the performance of WPT systems is adopted for optimization of antenna array gain in the far-field. The technique is adapted to account for typical antenna design requirements by adding power constraints for impedance matching considerations. Simulation examples and comparisons to global optimization verify the applicability, versatility and reliability of this powerful and general method in the context of Yagi-Uda array antennas. © Institution of engineering and *** Rights Reserved.

关键词： Convex optimization

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Exponential convergence for distributed smooth optimization under the restricted secant inequality condition

arXiv

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arXiv 2019年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Chai, Tianyou Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the distributed smooth optimization problem in which the objective is to minimize a global cost function formed by a sum of local smooth cost functions, by using local information exchange. The standard assumption for proving exponential/linear convergence of first-order methods is the strong convexity of the cost functions, which does not hold for many practical applications. In this paper, we first show that the continuous-time distributed primal-dual gradient algorithm converges to one global minimizer exponentially under the assumption that the global cost function satisfies the restricted secant inequality condition. This condition is weaker than the strong convexity condition since it does not require convexity and the global minimizers are not necessary to be unique. We then show that the discrete-time distributed primal-dual algorithm constructed by using the Euler's approximation method converges to one global minimizer linearly under the same condition. The theoretical results are illustrated by numerical simulations. Copyright © 2019, The Authors. All rights reserved.

关键词： Continuous time systems

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Gait speed tracking system using UWB radar 12

Gait speed tracking system using UWB radar

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12th European Conference on Antennas and Propagation, EuCAP 2018

作者： Lau, Bernard Haider, Sahar Boroomand, Ameneh Shaker, George Boger, Jennifer Morita, Plinio Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo Canada Department of Systems Design Engineering University of Waterloo Waterloo Canada Department of Applied Health Sciences University of Waterloo Waterloo Canada Research Institute of Aging University of Waterloo Waterloo Canada

ISBN: (纸本)9781785617911

The ability to measure the level of activity among older adults is crucial in assessing any signs of cognitive disorders, dementia, falls and/or mortality. The use of continuous gait monitoring devices can aid in early interventions and risk detection in a frequent and accurate manner. The paper presents a study which utilizes an ultra-wide band (UWB) radar for gait speed detection. The experiment was performed on six healthy young individuals in three different speed categories i.e. slow, normal and fast. The speed measurements from the radar were then compared against the data gathered from a GAITRite mat (the gold standard commercial sensor-loaded mat for the detection of walking speed) to determine the accuracy of data acquired from the radar. © Institution of engineering and *** Rights Reserved.

关键词： Ultra-wideband (UWB)

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Congestion and Emissions Reduction in Freeway Traffic Networks via Supervisory Event-triggered Control

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IFAC-PapersOnLine 2017年第1期50卷 4240-4245页

作者： Ferrara A. Pasquale C. Sacone S. Siri S. Department of Electrical Computer and Biomedical Engineering University of Pavia Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Italy

This paper proposes an innovative control scheme for regulating traffic in freeway networks via ramp metering in order to reduce congestion and traffic emissions. The control scheme is composed by a supervisor, acting at a higher level, which receives measurements from the whole network and periodically makes a prediction on the system evolution, and by local feedback controllers, acting at a lower level. These latter are extended PI-ALINEA controllers which compute the control action not only on the basis of measurements immediately downstream the on-ramp, as in standard PI-ALINEA, but also on the basis of other measurements or predictions referred to farther locations which are time-varying and communicated by the supervisor. The supervisor decides when the control law of extended PI-ALINEA controllers needs to be changed according to an event-triggered logic. © 2017

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Smooth Behavioral Estimation for Ramp Merging Control in Autonomous Driving

Smooth Behavioral Estimation for Ramp Merging Control in Aut...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Dong, Chiyu Dolan, John M. Litkouhi, Bakhtiar Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States Robotics Institute Carnegie Mellon University PittsburghPA15213 United States GM R and D Center WarrenMI48090 United States

ISBN: (纸本)9781538644522

Cooperative driving behavior is essential for driv- ing in traffic, especially for ramp merging, lane changing or navigating intersections. Autonomous vehicles should also man- age these situations by behaving cooperatively and naturally. In this paper, we enhance our previous learning-based method to efficiently estimate other vehicles' intentions and interact with them in ramp merging scenarios, without over-the-air commu- nication between vehicles. The proposed approach inherits our previous Probabilistic grahpical Model (PGM) and distance- keeping framework. Real driving trajectories are used to learn transition models in the PGM. Thus, besides the structure of the PGM, our method does not require human-designed reward or cost functions. The PGM-based intention estimation is followed by an off-the-shelf distance-keeping model to generate proper acceleration/deceleration controls. The PGM plays a plug-in role in our self-driving framework. The new model eliminates two assumptions in the previous model: 1) a fixed merging point for all merging agents, which is hard to determine before the merging vehicles make the merge;2) Perfect velocity mea- surement, which requires sophisticated perception systems. We validate the performance of our method both on real merging data and using a designed merging strategy in simulation, and show significant improvements compared with previous methods. Parameter design is also discussed by experiments. The new method is computationally efficient, and exhibits better robustness against sensing uncertainty. © 2018 IEEE.

关键词： Merging

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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Innovation 2025年第6期6卷 100948页

作者： Huang, Jincai Xu, Yongjun Wang, Qi Wang, Qi [Cheems] Liang, Xingxing Wang, Fei Zhang, Zhao Wei, Wei Zhang, Boxuan Huang, Libo Chang, Jingru Ma, Liantao Ma, Ting Liang, Yuxuan Zhang, Jie Guo, Jian Jiang, Xuhui Fan, Xinxin An, Zhulin Li, Tingting Li, Xuefei Shao, Zezhi Qian, Tangwen Sun, Tao Diao, Boyu Yang, Chuanguang Yu, Chenqing Wu, Yiqing Li, Mengxian Zhang, Haifeng Zeng, Yongcheng Zhang, Zhicheng Zhu, Zhengqiu Lv, Yiqin Li, Aming Chen, Xu An, Bo Xiao, Wei Bai, Chenguang Mao, Yuxing Yin, Zhigang Gui, Sheng Su, Wentao Zhu, Yinghao Gao, Junyi He, Xinyu Li, Yizhou Jin, Guangyin Ao, Xiang Zhai, Xuehao Tan, Haoran Yun, Lijun Shi, Hongquan Li, Jun Fan, Changjun Huang, Kuihua Harrison, Ewen Leung, Victor C.M. Qiu, Sihang Dong, Yanjie Zheng, Xiaolong Wang, Gang Zheng, Yu Wang, Yuanzhuo Guo, Jiafeng Wang, Lizhe Cheng, Xueqi Wang, Yaonan Yang, Shanlin Fu, Mengyin Fei, Aiguo Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Huazhong University of Science and Technology Wuhan430074 China School of Automation Beijing Institute of Technology Beijing100081 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing100081 China Guangzhou511453 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China IDEA Research International Digital Economy Academy Shenzhen518057 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Science National University of Defense Technology Changsha410073 China Center for Systems and Control College of Engineering Peking University Beijing100871 China Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China College of Systems Engineering National University of Defense Technology Changsha410073 China Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Electrical Engineering Chongqing University Chongqing400044 China Department of Mathematics The University of Hong Kong Hong Kong SAR999077 China School of Food Science and Technology Dalian Polytechnic University Dalian116034 China Centre for Medical Informatics University of Edinburgh EdinburghEH16 4UX United Kingdom Department of Stomatology Peking Union Medical College Hospital Chinese Academ

Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM's evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. © 2025 The Authors

关键词： Reinforcement learning

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Benchmarking quality-dependent and cost-sensitive score-level multimodal biometric fusion algorithms

arXiv

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arXiv 2021年

作者： Poh, Norman Bourlai, Thirimachos Kittler, Josef Allano, Lorene Alonso-Fernandez, Fernando Ambekar, Onkar Baker, John Dorizzi, Bernadette Fatukasi, Omolara Fierrez, Julian Ganster, Harald Ortega-Garcia, Javier Maurer, Donald Salah, Albert Ali Scheidat, Tobias Vielhauer, Claus Centre for Vision Speech and Signal Processing School of Electronics and Physical Sciences University of Surrey Guildford SurreyGU2 7XH United Kingdom Biometrics Center Lane Department of Computer Science and Electrical Engineering College of Engineering and Mineral Resources West Virginia University MorgantownWV26506-6109 United States Institut Telecom Telecom and Management SudParis Evry91011 France Biometric Recognition Group – ATVS Escuela Politecnica Superior Universidad Autonoma de Madrid Madrid28049 Spain Amsterdam1098 XG Netherlands Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Electronics and Physics Department Institut Telecom Telecom and Management SudParis Evry91011 France Institute of Digital Image Processing Joanneum Research Graz8010 Austria ISLA-ISIS University of Amsterdam Amsterdam1098 XG Netherlands Department of Informatics and Media Brandenburg University of Applied Sciences Brandenburg an der HavelD-14770 Germany Research Group Multimedia and Security Department of Technical and Business Information Systems Faculty of Computer Science Otto-von-Guericke-University of Magdeburg MagdeburgD-39106 Germany

Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign organized by the University of Surrey, involving face, fingerprint, and iris biometrics for person authentication, targeting the application of physical access control in a medium-size establishment with some 500 persons. While multimodal biometrics is a well-investigated subject in the literature, there exists no benchmark for a fusion algorithm comparison. Working towards this goal, we designed two sets of experiments: quality-dependent and cost-sensitive evaluation. The quality-dependent evaluation aims at assessing how well fusion algorithms can perform under changing quality of raw biometric images principally due to change of devices. The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match. Since multiple capturing devices are available, a fusion algorithm should be able to handle this nonideal but nevertheless realistic scenario. In both evaluations, each fusion algorithm is provided with scores from each biometric comparison subsystem as well as the quality measures of both the template and the query data. The response to the call of the evaluation campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this campaign is the first attempt to benchmark quality-based multimodal fusion algorithms. In the presence of changing

关键词： Benchmarking

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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