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IEEE International Conference on Intelligent Transportation systems

作者： Fei Wang Li Zhu Hongli Zhao State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University China

ISBN: (纸本)9781509018901

Train ground communication systems for different applications are deployed and managed independently in current urban rail transit systems with Wireless Local Area Network (WLAN) technology. Investing and constructing communication infrastructures repeatedly not only waste substantial social resources but also bring many difficulties to maintain all these infrastructures. In this paper, we design a network virtualization based integrated train ground communication system for urban rail transit systems. The virtual resource allocation in the integrated system is formulated as an optimization problem. On the premise that the train ground communication requirement of communication based train control system is guaranteed, the optimization objective is to maximize the long-term general utility for all the urban rail transit applications. We use the distributed method based on alternating direction method of multipliers (ADMM) to solve the optimization problem. Simulation results show that the designed integrated train ground communication system quality of service (QoS) can be improved effectively with the proposed approach.

关键词： Virtualization Rails Resource management Wireless communication Optimization Quality of service

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Optimized generation of test sequences for high-speed train using deep learning and genetic algorithm

Optimized generation of test sequences for high-speed train ...

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International Conference on Intelligent Transportation

作者： Kaicheng Li Qingpeng Gan Lei Yuan Qiang Fu National Engineering Research Center of RailTransportation Operation and Control System Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781509018901

Interface type test guarantees the suitability and safety of interface between high-speed train and ATP (Auto Train Protection) onboard equipment, which makes the generation of test sequences much significant. However, test sequences are normally redacted manually, of which the requirements of availability, safety, redundancy and coverage of test cases usually fail to meet expected standards. Specifying optimal time spend and energy consumption of test sequences, we use a simple deep learning network to decide the potential set of test cases at decision points, and implement the modified genetic algorithm adapted to our objective to generate and optimize the test sequences. Experiments are conducted using the field data of type test for CRH3C high speed train with CTCS3-300T ATP onboard equipment. Comparing with the actual sequences used in type test indicates that, based on satisfying the requirements of test cases, the proposed strategy can effectively generate test sequences with optimized time spend and energy consumption by 10.63% and 27.16% better improvement respectively.

关键词： Conferences Intelligent transportation systems

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Variable eccentric distance-based tool path generation for orthogonal turn-milling

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Frontiers of Mechanical engineering 2015年第4期10卷 352-366页

作者： Fangyu PENG Wei WANG Rong YAN Xianyin DUAN Bin LI State Key Laboratory of Digital Manufacturing Equipment andTechnology School of Mechanical Science and Engineering HuazhongUniversity of Science and Technology Wuhan 430074 China National Numerical Control System Engineering Research Center Huazhong University of Science and Technology Wuhan 430074 China

This study proposes an algorithm for max- imizing strip width in orthogonal tum-miUing based on variable eccentric distance. The machining error model is first established based on the local cutting profile at the contact line. The influencing factors of the strip width are then investigated to analyze their features and determine an optimizing strategy. The optimized model for maximum machining strip width is formulated by adopting a variable eccentric distance. Hausdorff distance and Fr6chet distance are introduced in this study to implement the constraint function of the machining error in the optimized model. The computing procedure is subsequently provided. Simulations and experiments have been conducted to verify the effectiveness of the proposed algorithm.

关键词： orthogonal turn-milling variable eccentricdistance local cutting profile machining strip-widthmaximization

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A model-based test case generation method for function testing of Train control systems

A model-based test case generation method for function testi...

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IEEE International Conference on Intelligent Rail Transportation (ICIRT)

作者： Jidong Lv Haifeng Wang Hongjie Liu Lu Zhang Tao Tang National Engineering Research Center Of Rail Transportation Operation And Control System Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

Potential faults in safety critical systems may lead to system failures thus bring huge human injuries. How to ensure the correctness of the system during the system development is very important. system function testing has been regarded as an effective approach which normally applied in the final stage of system development to ensure the consistence of system functions and specifications. In this paper, an integrated model-based test case generation method combining Hybrid Communicating Sequential Processes (HCSP) and Timed Automata is introduced, in which HCSP is used to formally model the scenarios of the system, while Timed Automata is used to verify the system properties in HCSP models. To bridge the gap between the HCSP model and Timed Automata model, transition rules are defined according to the characteristics of systems. Based on the Network Timed Automaton model, a tool chain (UPPAAL and CoVer) is presented to automatically generate test case with coverage criteria in a simple and flexible manner. The tool chain is also applied to analyze the typical Radio Block center (RBC) handover scenario in Chinese Train control system Level 3 (CTCS-3). Logical and timing properties of the case study are verified and different test case suites of Vital Computer (VC) components in RBC handover model are automatically generated with different coverage criteria.

关键词： Automata Safety Delays Clocks Testing control systems

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Optimal control of heavy haul train on steep downward slope

Optimal control of heavy haul train on steep downward slope

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International Conference on Intelligent Transportation

作者： Xi Wang Tao Tang National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781509018901

In this paper, we investigate the optimal control problem of heavy haul train on steep downward slope. Aiming to reduce train's maintenance cost and, most importantly, to ensure operation safety, a multi-stage dynamic programming model is formulated with the minimized in-train forces criteria. To solve the proposed model, this paper introduces a Q-learning algorithm considering operational requirements and the characteristics of air braking. As the size of a standard lookup table increases exponentially, we improve the computational performance and solution quality by maintaining a bounded lookup table. The computational results demonstrate the effectiveness and performance of the proposed model and algorithm.

关键词： Automobiles Brakes Resistance Force Optimal control Safety Aerodynamics

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Damping DFIG-associated SSR by Adding Subsynchronous Suppression Filters to DFIG Converter controllers

Damping DFIG-associated SSR by Adding Subsynchronous Suppres...

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IEEE Power and Energy Society General Meeting

作者： Huakun Liu Xiaorong Xie Jingbo He Hui Liu Yunhong Li State Key Labor. of Power System Department of Electrical Engineering Tsinghua University National Power Dispatching and Control Center North China Electric Power Research Institute

ISBN: (纸本)9781509041695

Subsynchronous resonance (SSR) issue, namely subsynchronous control interaction (SSCI), was observed in doubly-fed induction generators (DFIGs) based wind farms connected to fixed series compensation. This paper proposes a novel scheme to deactivate SSR by adding subsynchronous suppression filters (SSFs) to DFIG converter controllers. Based on the impedance model analysis, a quantitative index is defined and implemented to identify the "best" location of converter controllers for embedding a SSF. A specific SSF scheme is recommended for practical application, which is to embed a SSF into d-axis channel in inner current loop of rotor-side converter. This scheme has been applied to a practical series-compensated DFIG-based wind farm system located in North China, which has experienced real SSR events. Both impedance analysis and time-domain simulation have validated the effectiveness of the proposed scheme. This control scheme has a broad application prospect due to its easiness to implement and robustness to changeable operating conditions.

关键词： Doubly-fed induction generator (DFIG) Fixed series compensation (FSC) Subsynchronous resonance (SSR) Subsynchronous control interaction (SSCI) Subsynchronous suppression filter PPAN gene semiconductor relays Converters series compensation controllers Current rings impedance analysis Wind farms

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Field Test Results Analysis in Urban Rail Transit Train Ground Communication systems of Integrated Service Using LTE-M

Field Test Results Analysis in Urban Rail Transit Train Grou...

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IEEE International Conference on Intelligent Transportation systems

作者： Tao Tang Keping Dai Yanbing Zhang Hongli Zhao Hailin Jiang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing Rail Transit Construction and Management Co. Ltd. National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

ISBN: (纸本)9781509018901

Different services are separated by independent train ground communication networks in existing urban rail transit systems. Most of the independent train ground communication system are using IEEE 802.11 based WLAN technologies, which has many drawbacks when used in urban rail transit system, such as high speed performance degradation, open free frequency, etc. In this paper, we design a train ground communication system for Integrated Service in urban rail transit/metro system using LTE technology (LTE-M). Dedicated frequency spectrum is used in the LTE-M based system. The real LTE-M based system is built on the ring rail line in Beijing to perform the field test. The performance of the integrated services including the CBTC, PIS, IMS and TOSM (Train Operation state Monitoring) are tested. Extensive test results show the advantages of LTE-M. The test results analysis also illustrates the disadvantages of using LTE-M in urban rail, and gives some advises for LTE-M based system design in engineering.

关键词： Rails Rail transportation Wireless LAN Monitoring Delays Quality of service

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Exploring Optimal Frequency Caps in Real Time Bidding Advertising

Exploring Optimal Frequency Caps in Real Time Bidding Advert...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Rui Qin Yong Yuan Fei-Yue Wang Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781509039371

Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.

关键词： Advertising Digital signal processing Computational modeling Big data Time-frequency analysis Radio spectrum management Real-time systems

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Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

Optimizing Market Segmentation Granularity in RTB Advertisin...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

ISBN: (纸本)9781509039371

Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline, 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions.

关键词： Digital signal processing Computational modeling Advertising numerical models Big data Complex systems Automation

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