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CrowdWatcher: an open-source platform to catch the eye of the crowd

Quality and User Experience 2019年第1期4卷 1-17页

作者： Lebreton, Pierre Hupont, Isabelle Hirth, Matthias Mäki, Toni Skodras, Evangelos Schubert, Anton Raake, Alexander Group of Networked Sensing and Control (NeSC) Zhejiang University Hangzhou China Institute of Intelligent Systems and Robotics Sorbonne University Paris France User-Centric Analysis of Multimedia Data Group Technische Universität Ilmenau Ilmenau Germany Department of Computer Science Aalto University Espoo Finland Department of Electrical and Computer Engineering University of Patras Patras Greece Audio Visual Technology Group Technische Universität Ilmenau Ilmenau Germany

This paper presents the open-source eye tracking platform CrowdWatcher. It enables researchers to measure gaze location and user engagement in a crowdsourcing context through traditional RGB webcams. The proposed platform particularly advances the field of Quality of Experience (QoE) research, as it allows the experimenter to collect remotely and with very limited effort novel information from crowds of participants, such as their commitment towards a task, attention and decision-making processes. Two different experiments are described that were conducted to demonstrate the platform’s potential. The first experiment addresses the measurement of participants’ behavior while performing a movie selection task. Results show that the platform provides complementary information to traditional self-reported data by taking gaze analysis into account. This is of particular relevance, since in a crowdsourcing context decision processes and attention are difficult to assess, and there is often limited control over the engagement of the test user with the task. A second experiment is conducted in the scenario of a multimedia QoE test. Prediction accuracy is compared to a professional infrared eye tracker. While CrowdWatcher performs less well than the professional eye tracker, it is still able to collect valuable gaze information in the far more challenging environment of crowdsourcing. As an outlook to further application domains, the usage of the platform to measure user engagement allows participants who do not pay attention to the task to be identified.

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Decentralized controller design in flexure-linked gantry by H2 guaranteed cost optimization approach 18

Decentralized controller design in flexure-linked gantry by ...

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18th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2018

作者： Ma, Jun Chen, Si-Lu Liang, Wenyu Teo, Chek Sing Tay, Arthur Al Mamun, Abdullah Tan, Kok Kiong SIMTech-NUS Joint Lab. on Precision Motion Systems Department of Electrical and Computer Engineering National University of Singapore Singapore117582 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Agency for Science Technology and Research Singapore Institute of Manufacturing Technology Singapore138634 Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo Zhejiang315201 China

ISBN: (纸本)9780995775121

Dual-drive H-gantry is widely used in many industrial processes that require high-speed and high-precision Cartesian motion. Unlike the rigid-linked gantry design, the flexure-linked design is able to prevent the damage of the cross-arm because a small degree of rotation angle is possible. However, the flexure-linked design may induce the resonant modes of the gantry because of high frequency control signals. To maintain the precision tracking of two carriages and minimize the chattering of control efforts, we aim to seek the most suitable flexure joints among the available ones while optimizing the decentralized feedback controller parameters under model uncertainties. In this way, good tracking performance is achieved without costly system re-design. In this work, we formulate the mechatronic design problem as an H2 guaranteed cost control problem. All the stabilizing feedback controller gains are parameterized over a convex set, and the global optimum is obtained by means of an outer-linearization-based algorithm. Experiments are conducted and the results successfully validate the effectiveness of the proposed design approach. © 2018 CURRAN-CONFERENCE. All rights reserved.

关键词： Convex optimization Dual-drive H-gantry Flexure Mechatronic design Optimal control Parallel mechanism

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Calibration of Heterogeneous Sensor systems

arXiv

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arXiv 2018年

作者： Peršić, Juraj University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems Mobile Robotics LAMOR

Environment perception is a key component of any autonomous system and is often based on a heterogeneous set of sensors and fusion thereof for which sensor sensor calibration plays fundamental role. It can be divided to intrinsic and extrinsic sensor calibration. Former seeks for internal parameters of each individual sensor, while latter provides coordinate frame transformation between sensors. Calibration techniques require correspondence registration in the measurements which is one of the main challenges in the extrinsic calibration of heterogeneous sensors, since generally, each sensor can operate on a different physical principle. Measurement correspondences can originate from a designated calibration target or from features in the environment. Additionally, environment features can be used to estimate motion of individual sensors and the calibration is found by aligning these estimates. Motion-based calibration is the most common approach in the online calibration since it is more practical than the target-based methods, although it can lack in accuracy. Furthermore, online calibration is beneficial for system robustness as it can detect and adjust recalibration of the system in runtime, which can be seen as a prerequisite for long-term autonomy. Copyright © 2018, The Authors. All rights reserved.

关键词： Calibration

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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中国科学（信息科学） 2018年第9期61卷 226-234页

作者： Xiaohua LI Jianquan LU Jianlong QIU Xiangyong CHEN Xiaodi LI Fuad E.ALSAADI School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China School of Mathematics Southeast University Nanjing 210096 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics Southeast University Nanjing 210096 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China Department of Electrical and Computer Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia

This paper mainly analyzes the set stability of switched Boolean networks (SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop ***,the definitions of set stability are proposed for SBNs with such switching ***,we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant ***,the corresponding set stability conditions for SBNs are given in each *** addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching ***,the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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Decentralized Energy Sharing Protocol using TÆMS Framework and Coalition-based Metaheuristic for Heterogeneous Robotic systems

Decentralized Energy Sharing Protocol using TÆMS Framework ...

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作者： Arbanas, Barbara Boljuncic, Sara Petrovic, Tamara Bogdan, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Croatia

In this paper we describe a decentralized protocol that is applied for scheduling and management of energy sharing in heterogeneous systems. Particular system we have in mind comprises of agents with different mobility, energy harvesting and energy sharing capabilities herein called aPads, aFish and aMussels. aPads are surface vehicles that harvest energy and are able to transmit it to both aFishes and aMussels. aFish are underwater vehicles that can transmit energy to aMussels or to other aFish, and receive energy from aPads. aMussels, that can either be attached to the sea-ground or float on the surface, can only receive energy, either from aFish or aPads. For such a system to be able to function for an extended period of time, a decentralized energy management protocol should be designed, whose purpose is to schedule and coordinate charging of agents over time. These decisions depend on the current battery levels of different agents, as well as their positions, and should be done in a decentralized manner. In this paper we apply an energy sharing protocol based on TÆMS framework, originally applied to planning and coordination in aerial-ground robotics systems for search and rescue missions. We refine the obtained plans using the coalition-based metaheuristic for vehicle routing problems. We show execution schedules achieved using the proposed protocol and highlight its advantages and flaws when applied to our underwater scenario. © 2017

关键词： Energy management systems

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Robust lane marking detection algorithm using drivable area segmentation and extended SLT

arXiv

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arXiv 2019年

作者： Ozgunalp, Umar Fan, Rui Cheng, Shanshan Sun, Yuxiang Zuo, Weixun Zhu, Yilong Xue, Bohuan Zheng, Linwei Liang, Qing Liu, Ming Electrical and Electronics Engineering Cyprus International University North Cyprus Turkey Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Hangzhou ATG Intelligent Technology Co. Ltd. Hangzhou China Guolu Gaoke Engineering Technology Institute Co. Ltd. Beijing China Robotics and Multiperception Laboratory Robotics Institute Hong Kong University of Science and Technology Hong Kong Hong Kong

In this paper, a robust lane detection algorithm is proposed, where the vertical road profile of the road is estimated using dynamic programming from the v-disparity map and, based on the estimated profile, the road area is segmented. Since the lane markings are on the road area and any feature point above the ground will be a noise source for the lane detection, a mask is created for the road area to remove some of the noise for lane detection. The estimated mask is multiplied by the lane feature map in a bird's eye view (BEV). The lane feature points are extracted by using an extended version of symmetrical local threshold (SLT), which not only considers dark light dark transition (DLD) of the lane markings, like (SLT), but also considers parallelism on the lane marking borders. The segmentation then uses only the feature points that are on the road area. A maximum of two linear lane markings are detected using an efficient 1D Hough transform. Then, the detected linear lane markings are used to create a region of interest (ROI) for parabolic lane detection. Finally, based on the estimated region of interest, parabolic lane models are fitted using robust fitting. Due to the robust lane feature extraction and road area segmentation, the proposed algorithm robustly detects lane markings and achieves lane marking detection with an accuracy of 91% when tested on a sequence from the KITTI dataset. Copyright © 2019, The Authors. All rights reserved.

关键词： Dynamic programming

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Cost Optimal Control of Microgrids Having Solar Power and Energy Storage

Cost Optimal Control of Microgrids Having Solar Power and En...

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2018 IEEE/PES Transmission and Distribution Conference and Exposition, T and D 2018

作者： Gupta, Nikhil Francis, Griffin Ospina, Juan Newaz, Alvi Collins, Emmanuel G. Faruque, Omar Meeker, Rick Harper, Mario United States Center for Intelligent Systems Control and Robotics FAMU-FSU COE United States Department of Electrical and Computer Engineering FAMU-FSU COE United States Center for Advanced Power Systems FSU United States NHU Energy Inc. TallahasseeFL United States Department of Scientific Computing FSU United States

ISBN: (纸本)9781538655832

Solar power availability is intermittent and must be accompanied by an energy storage system (ESS) so that the effect of variability can be minimized. Hence, a strategy is needed to find the optimum combination of grid power, solar power, and power from the ESS so that the total cost of energy can be minimized. A solution to this problem is proposed here as Advanced Optimal Resource Allocation (AORA). This control scheme uses the prediction of Photovoltaic (PV) power availability, the real-time price of energy, and the levelized cost of energy for both PV and ESS to optimally combine the dispatch of power sources. Simulation results are presented for a 24 h prediction window and compared with a baseline power usage scheme that is based on a fixed charging and discharging schedule for the ESS. The comparison shows that AORA results in a substantial cost savings over the baseline scheme. © 2018 IEEE.

关键词： Forecasting

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用于糖尿病培训的大型语言模型:一项前瞻性研究（英文）

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Science Bulletin 2025年第6期 934-942页

作者：李灏萱江泽铧管洲榆包玉倩刘月星胡婷婷李佳佳刘茹涵吴量程棣纪宏伟王勇王亚星 Carol Y.Cheung 郑颖丰王继红李震吴卫兵 Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan 程景煜黄天荫李华婷蔡淳毛丽娟 Lee-Ling Lim 覃宇宗盛斌贾伟平 Shanghai University of Sport School of Clinical Medicine Beijing Tsinghua Changgung Hospital Tsinghua Medicine Tsinghua University Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua Medicine Tsinghua University Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes MoE Key Lab of Artificial Intelligence Artificial Intelligence Institute Shanghai Jiao Tong University Department of Cardiology the Affiliated Hospital of Qingdao University CEMS NCMIS HCMS MADIS Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematics University of Chinese Academy of Sciences Chinese Academy of Sciences Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Beijing Institute of Ophthalmology Beijing Tongren Hospital Capital Medical University Beijing Ophthalmology and Visual Sciences Key Laboratory Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular Diseases Department of Renal Medicine Singapore General Hospital Sing Health-Duke Academic Medical Centre Department of Endocrinology Singapore General Hospital Department of Endocrinology Austin Health Department of Medicine The University of Melbourne(Austin Health) Australian Centre for Accelerating Diabetes Innovations(ACADI) The Univ

Diabetes poses a considerable global health challenge, with varying levels of diabetes knowledge among healthcare professionals, highlighting the importance of diabetes training. Large Language Models(LLMs)provide new insights into diabetes training, but their performance in diabetes-related queries remains uncertain, especially outside the English language like Chinese. We first evaluated the performance of ten LLMs: Chat GPT-3.5, Chat GPT-4.0, Google Bard, Lla MA-7B, Lla MA2-7B, Baidu ERNIE Bot, Ali Tongyi Qianwen, Med GPT, Huatuo GPT, and Chinese Lla MA2-7B on diabetes-related queries, based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC) and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United Kingdom. Second, we assessed the training of primary care physicians(PCPs) without and with the assistance of Chat GPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical assistants. We found that Chat GPT-4.0 outperformed other LLMs in the English examination, achieving a passing accuracy of 62.50%, which was significantly higher than that of Google Bard, Lla MA-7B, and Lla MA2-7B. For the NCE-CPFC examination, Chat GPT-4.0, Ali Tongyi Qianwen, Baidu ERNIE Bot, Google Bard, Med GPT, and Chat GPT-3.5 successfully passed, whereas Lla MA2-7B, Huatuo GPT,Chinese LLa MA2-7B, and Lla MA-7B failed. Chat GPT-4.0(84.82%) surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%). In summary, LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language, and hold great potential to assist future diabetes training for physicians globally.

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Metrics Reloaded: Recommendations for image analysis validation

arXiv

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arXiv 2022年

作者： Maier-Hein, Lena Reinke, Annika Godau, Patrick Tizabi, Minu D. Buettner, Florian Christodoulou, Evangelia Glocker, Ben Isensee, Fabian Kleesiek, Jens Kozubek, Michal Reyes, Mauricio Riegler, Michael A. Wiesenfarth, Manuel Emre Kavur, A. Sudre, Carole H. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Rädsch, Tim Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Jorge Cardoso, M. Cheplygina, Veronika Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian Ginneken, Bram Van Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kofler, Florian Kopp-Schneider, Annette Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rajpoot, Nasir Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Smeden, Maarten Van Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben Van Varoquaux, Gaël Jäger, Paul F. Heidelberg Division of Intelligent Medical Systems and HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt-Marburg Germany Heidelberg Goethe University Frankfurt Germany Department of Medicine Goethe University Frankfurt Germany Department of Informatics Frankfurt Cancer Insititute Germany Department of Computing Imperial College London London United Kingdom Heidelberg Division of Medical Image Computing and HI Applied Computer Vision Lab Germany Institute for AI in Medicine University Medicine Essen Essen Germany Centre for Biomedical Image Analysis Faculty of Informatics Masaryk University Brno Czech Republic ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Bern Switzerland Simula Metropolitan Center for Digital Engineering Oslo Norway UiT The Arctic University of Norway Romsø Norway Heidelberg Division of Biostatistics Germany Heidelberg Division of Intelligent Medical Systems Division of Medical Image Computing HI Applied Computer Vision Lab Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Heidelberg Division of Medical Image Computing Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. It was developed by a large international consortium in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint – a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. © 2022, CC BY.

关键词： Semantic Segmentation

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Robust gesture-based communication for underwater human-robot interaction in the context of search and rescue diver missions

arXiv

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arXiv 2018年

作者： Chavez, Arturo Gomez Mueller, Christian A. Doernbach, Tobias Chiarella, Davide Birk, Andreas Robotics Group Computer Science & Electrical Engineering Jacobs University Bremen Germany Institute of Intelligent Systems for AutomationNational Research Council of Italy Genova Italy

We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, including an alphabet, syntax and semantics, ensuring a logical consistency. A hierarchical classification approach is introduced for hand gesture recognition based on stereo imagery and multi-descriptor aggregation to specifically cope with underwater image artifacts, e.g. light backscatter or color attenuation. Once the classification task is finished, a syntax check is performed to filter out invalid command sequences sent by the diver or generated by errors in the classifier. Throughout this process, the diver receives constant feedback from an underwater tablet to acknowledge or abort the mission at any time. The objective is to prevent the AUV from executing unnecessary, infeasible or potentially harmful motions. Experimental results under different environmental conditions in archaeological exploration and bridge inspection applications show that the system performs well in the field. Copyright © 2018, The Authors. All rights reserved.

关键词： Syntactics

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