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Sequential subspace change-point detection

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arXiv 2018年

作者： Xie, Liyan Xie, Yao Moustakides, George V. School of Industrial and Systems Engineering Georgia Institute of Technology United States Department of Computer Science Rutgers University United States Department of Electrical and Computer Engineering University of Patras Greece

We consider the online monitoring of multivariate streaming data for changes that are characterized by an unknown subspace structure manifested in the covariance matrix. In particular, we consider the covariance structure changes from an identity matrix to an unknown spiked covariance model. We assume the post-change distribution is unknown, and propose two detection procedures: the Largest-Eigenvalue Shewhart chart and the Subspace-CUSUM detection procedure. We present theoretical approximations to the average run length (ARL) and the expected detection delay (EDD) for the Largest-Eigenvalue Shewhart chart and also provide analysis for tuning parameters of the Subspace-CUSUM procedure. The performance of the proposed methods is illustrated using simulation and real data for human gesture detection and seismic event detection. Copyright © 2018, The Authors. All rights reserved.

关键词： Covariance matrix

Alternative materials for PM synchronous motors 11

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Alternative materials for PM synchronous motors

11. GMM/ETG-Fachtagung Innovative Small Drives and Micro-Motor systems - 11th GMM/ETG Symposium Innovative Small Drives and Micro-Motor systems

作者： Huth, Gerhard Löhlein, Bernd Institute of Mechatronic and Electrical Drive Systems Department of Electrical and Computer Engineering Technical University of Kaiserslautern Germany

ISBN: (纸本)9783800744619

Also in the field of small electrical motors, there is a clear trend towards energy efficiency improvement which makes the use of permanent magnet (PM) synchronous machines more and more attractive. The demand for a highly automated manufacture of motors favors tooth coil stator concepts requiring inherently a higher number of pole pairs. At higher speeds, specific measures have to be taken to reduce the core losses. In addition, a compact rotor design is necessary to keep eddy-current losses low. When designing the active part of a rotor and stator, SMC materials and duplex stainless steels are an appropriate choice. Soft magnetic composites (SMC) have already been used for the design of PM synchronous machines. In contrast, duplex steel is more or less unknown in the field of electrical machines. After an introduction of the two materials, the physical properties of the materials selected for the experimental model will be described and compared to those of electrical steel commonly used up to now. A stator concept consisting of SMC subcomponents and a one-piece rotor made of duplex steel is seen as a suitable solution. The rare-earth magnets can either be mounted on the rotor surface or integrated into the rotor body. Based on this concept, an experimental model will be designed and created based on FE simulations. The experimental model will be developed for an application with a speed setting range of up to 30,000 min-1. The test set-up developed will then be described and finally, the test results will be discussed by comparing them with those obtained from simulations. © Innov. Small Drives and Micro-Motor systems. All rights reserved.

关键词： Stators

Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations

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Scientific Data 2018年第1期5卷 180237-180248页

作者： Ker, Dai Fei Elmer Eom, Sungeun Sanami, Sho Bise, Ryoma Pascale, Corinne Yin, Zhaozheng Huh, Seung-Il Osuna-Highley, Elvira Junkers, Silvina N. Helfrich, Casey J. Liang, Peter Yongwen Pan, Jiyan Jeong, Soojin Kang, Steven S. Liu, Jinyu Nicholson, Ritchie Sandbothe, Michael F. Van, Phu T. Liu, Anan Chen, Mei Kanade, Takeo Weiss, Lee E. Campbell, Phil G. Department of Biological Sciences Carnegie Mellon University Pittsburgh United States Institute for Tissue Engineering and Regenerative Medicine The Chinese University of Hong Kong Shatin Hong Kong School of Biomedical Sciences Faculty of Medicine The Chinese University of Hong Kong Shatin Hong Kong Robotics Institute Carnegie Mellon University Pittsburgh United States Dai Nippon Printing Tokyo Japan Department of Advanced Information Technology Kyushu University Fukuoka Japan Engineering Research Accelerator Carnegie Mellon University Pittsburgh United States Department of Computer Science Missouri University of Science and Technology Rolla United States Intel Labs Pittsburgh Pittsburgh United States Department of Computer Science Carnegie Mellon University Pittsburgh United States School of Electrical and Information Engineering Tianjin University Tianjin China Department of Electrical and Computer Engineering University at Albany State University of New York Albany United States Department of Biomedical Engineering Carnegie Mellon University Pittsburgh United States

Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research. © The Author(s) 2018.

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Distributed Leader-follower Formation Control of Nonholonomic Mobile Robots

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IFAC-PapersOnLine 2019年第15期52卷 67-72页

作者： Qun Lu Zhiqiang Miao Dan Zhang Li Yu Wenjun Ye Simon X. Yang Chun-Yi Su College of Electrical Engineering Yancheng Institute of Technology Yancheng 224003 China College of Electrical and Information Engineering Hunan University Changsha 410082 China College of Information Engineering Zhejiang University of Technology Hangzhou 310023 China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal QC H3G 1M8 Canada Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph Guelph ON N1G 2W1 Canada School of Automation Guangdong University of Technology Guangzhou 510006 China on leave from Concordia University Montreal QC H3G 1M8 Canada

This paper considers the problem of distributed leader-follower formation control for nonholonomic mobile robots only using local interactions among the robots. First, a distributed estimation strategy is presented for each follower robot to estimate the leader’s state. Then the dynamic equations of the formation tracking errors are formulated and a distributed formation control scheme is designed, which yields globally uniformly ultimately bounded stability for the closed-loop systems without requiring persistent excitation conditions. Finally, a simulation example demonstrates the effectiveness of the proposed approach.

关键词： Distributed formation control nonholonomic mobile robots distributed formation control persistent exciting conditions

Flexible disaster response of tomorrow final presentation and evaluation of the CENTAURO system

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arXiv 2019年

作者： Klamt, Tobias Rodriguez, Diego Baccelliere, Lorenzo Chen, Xi Chiaradia, Domenico Cichon, Torben Gabardi, Maßimiliano Guria, Paolo Holmquist, Karl Kamedula, Malgorzata Karaoguz, Hakan Kashiri, Navvab Laurenzi, Arturo Lenz, Christian Leonardis, Daniele Hoffman, Enrico Mingo Muratore, Luca Pavlichenko, Dmytro Porcini, Francesco Ren, Zeyu Schilling, Fabian Schwarz, Max Solazzi, Maßimiliano Felsberg, Michael Frisoli, Antonio Gustmann, Michael Jensfelt, Patric Nordberg, Klas Roßmann, Jürgen Süß, Uwe Tsagarakis, Nikos G. Behnke, Sven Autonomous Intelligent Systems University of Bonn Germany Humanoids and Human-Centred Mechatronics Istituto Italiano di Tecnologia Genoa Italy Department of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden PERCRO Laboratory TeCIP Institute Sant'Anna School of Advanced Studies Pisa Italy Institute for Man-Machine Interaction RWTH Aachen University Germany Computer Vision Laboratory Linköping University Sweden Lausanne Switzerland Kerntechnische Hilfsdienst GmbH Karlsruhe Germany School of Electrical and Electronic Engineering University of Manchester United Kingdom

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

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arXiv 2023年

作者： Moawad, Ahmed W. Janas, Anastasia Baid, Ujjwal Ramakrishnan, Divya Saluja, Rachit Ashraf, Nader Jekel, Leon Amiruddin, Raisa Adewole, Maruf Albrecht, Jake Anazodo, Udunna Aneja, Sanjay Anwar, Syed Muhammad Bergquist, Timothy Calabrese, Evan Chiang, Veronica Chung, Verena Conte, Gian Marco Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Iglesias, Juan Eugenio Jiang, Zhifan Johanson, Elaine Kazerooni, Anahita Fathi Kofler, Florian Krantchev, Kiril LaBella, Dominic Van Leemput, Koen Li, Hongwei Bran Linguraru, Marius George Link, Katherine E. Liu, Xinyang Maleki, Nazanin Meier, Zeke Menze, Bjoern H. Moy, Harrison Osenberg, Klara Piraud, Marie Reitman, Zachary Shinohara, Russel Takeshi Tahon, Nourel hoda Nada, Ayman Velichko, Yuri S. Wang, Chunhao Wiestler, Benedikt Wiggins, Walter Shafique, Umber Willms, Klara Avesta, Arman Bousabarah, Khaled Chakrabarty, Satrajit Gennaro, Nicolo Holler, Wolfgang Kaur, Manpreet LaMontagne, Pamela Lin, MingDe Lost, Jan Marcus, Daniel S. Maresca, Ryan Merkaj, Sarah Nada, Ayaman Pedersen, Gabriel Cassinelli von Reppert, Marc Sotiras, Aristeidis Teytelboym, Oleg Tillmans, Niklas Westerhoff, Malte Youssef, Ayda Godfrey, Devon Floyd, Scott Rauschecker, Andreas Villanueva-Meyer, Javier Pflüger, Irada Cho, Jaeyoung Bendszus, Martin Brugnara, Gianluca Cramer, Justin Perez-Carillo, Gloria Guzman J. Johnson, Derek R. Kam, Anthony Kwan, Benjamin Yin Ming Lai, Lillian Lall, Neil U. Memon, Fatima Patro, Satya Narayana Petrovic, Bojan So, Tiffany Y. Thompson, Gerard Wu, Lei Schrickel, E. Brooke Bansal, Anu Barkhof, Frederik Besada, Cristina Chu, Sammy Druzgal, Jason Dusoi, Alexandru Farage, Luciano Feltrin, Fabricio Fong, Amy Fung, Steve H. Gray, R. Ian Ikuta, Ichiro Iv, Michael Postma, Alida A. Mahajan, Amit Joyner, David Krumpelman, Chase Letourneau-Guillon, Laurent Lincoln, Christie M. Maros, Mate E. Miller, Elka Morón, Fanny Nimchinsky, Esther A. Ozsarlak, Ozkan Patel, Uresh Rohatgi, Saurabh Saha, Atin Sayah, Anousheh Schwartz, Eric D. Shih, Robert Shiroishi, Mark Trinity health Mid Atlantic Hosiptals DarbyPA United States Department of Radiology and Biomedical Imaging Yale School of Medicine New HavenCT United States Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electical and Computer Engineering Cornell University Cornell Tech New YorkNY United States Department of Radiology Weill Cornell Medicine New YorkNY United States ImagineQuant Children’s Hospital of Philadelphia PhiladelphiaPA United States College of Medicine Alfaisal University Riyadh Saudi Arabia DKFZ Division of Translational Neurooncology The WTZ German Cancer Consortium DKTK Partner Site University Hospital Essen Essen Germany Medical Artificial Intelligence Lab Crestview Radiology Lagos Nigeria Sage Bionetworks SeattleWA United States Montreal Neurological Institute McGill University Montreal Canada lab Crestview Radiology Lagos Nigeria Department of Therapeutic Radiology Yale School of Medicine New HavenCT United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Department of Radiology Mayo Clinic RochesterMN United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Neurosurgery Yale School of Medicine New HavenCT United States Center for Global Health Perelman School of Medicine University of Pennsylvania PA United States Department of Informatics Technical University Munich Germany Children’s Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Children’s National Hospital WashingtonDC United States PrecisionFDA U.S. Food and Drug Administration S

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well-annotated, diverse d

关键词： Image segmentation

RFID-based smart parking management system

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Cyber-Physical systems 2017年第1-4期3卷 22-41页

作者： Tsiropoulou, Eirini Eleni Baras, John S. Papavassiliou, Symeon Sinha, Surbhit Department of Electrical and Computer Engineering University of Maryland College ParkMD United States Institute for Systems Research University of Maryland College ParkMD United States School of Electrical & Computer Engineering National Technical University of Athens Zografou Greece Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States

In this paper, the adoption of passive Radio Frequency Identification (RFID) tag-to-tag communication paradigm within the context of a smart parking system is evangelised, in terms of achieving improved energy-efficiency and operational effectiveness. To demonstrate that the joint routing and RFID readers’ transmission power minimisation problem is studied, considering tag-to-tag communication. The superiority of the proposed framework against conventional direct RFID reader-tag communication is demonstrated in terms of: (i) reduction of RFID readers’ transmission power to the minimum required to guarantee connectivity, and (ii) expansion of RFID reader’s coverage area towards communicating with more distant tags, otherwise unreachable through direct communication. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Energy efficiency

Skeleton model based behavior recognition for pedestrians and cyclists from vehicle scene camera

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Skeleton model based behavior recognition for pedestrians an...

IEEE Intelligent Vehicles Symposium

作者： Qiwen Deng Renran Tian Yaobin Chen Kang Li Transportation Active Safety Institute and Department of Electrical and Computer Engineering Indiana University Purdue University Indianapolis Department of Industrial and Systems Engineering School of Engineering Rutgers University

ISBN: (纸本)9781538644539

With the significant advances in computer vision research, skeleton model based human pose recognition has become more accurate and time-efficient, although most of the applications are limited in laboratory environment or on surveillance videos. This paper proposes a pose tracking and behavior recognition method fromgehicle scene camera. It will not only detect pedestrians on the road, but also generate their skeleton models describing head, limb, and trunk movements. Based on these more detailed movements of body parts, the proposed method is designed to track poses of pedestrians and cyclists with the potentials to enable automated pedestrian gesture reading and non-verbal interactions between autonomous vehicles and pedestrians. The proposed algorithm has been tested on different databases including TASI 110-car naturalistic driving database and Joint Attention for Autonomous Driving (JAAD) database. Results show that key frames describing different pedestrian and cyclist negotiation gestures are detected from the raw video streams using the proposed method. These results will improve our understanding of pedestrian and cyclist's intentions and can be further used for autonomous vehicle control algorithm development.

关键词： Pose tracking Behavior recognition Pedestrian and cyclists Human-autonomous vehicle interaction

Coordinating vehicle platoons for highway bottleneck decongestion and throughput improvement

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arXiv 2019年

作者： Čičić, Mladen Jin, Li Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Malvinas väg 10 Stockholm10044 Sweden Department of Civil and Urban Engineering C2SMART University Transportation Center New York University Tandon School of Engineering 15 MetroTech Center BrooklynNY11201 USA United States

Truck platooning is a technology that is expected to become widespread in the coming years. Apart from the numerous benefits that it brings, its potential effects on the overall traffic situation needs to be studied further, especially at bottlenecks and ramps. However, assuming we can control the truck platoons from the infrastructure, they can be used as controlled moving bottlenecks, actuating control actions on the rest of the traffic. Thus properly controlled platoons can possibly improve the efficiency and throughput of the whole system. In this paper, we use a multi-class cell transmission model to capture the interaction between truck platoons and background traffic, and propose a corresponding queuing model, which we use for control design. As control inputs, we use platoon speeds, and the number of lanes platoons occupy, and we devise a control strategy for throughput improvement. This control law is applied on a highway section upstream of a bottleneck, with one on- ramp and one off-ramp. By postponing and shaping the inflow to the bottleneck, we are able to keep it in free flow, avoiding traffic breakdown and capacity drop, leading to significant reduction of total time spent of all vehicles. We tested the proposed control in a simulation study and found that by applying, we reduce the median delay of all vehicles by 75:6%. Notably, although they are slowed down while actuating control actions, platoons experience less delay compared to the case without control, since they avoid going through congestion at the bottleneck. Copyright © 2019, The Authors. All rights reserved.

关键词： Queueing theory