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2nd International Conference on Communications, Signal processing, and systems, CSPS 2013

作者： Zhu, Jianglong Huang, Jun He, Dawen Leng, Yujun Xiao, Shilin Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications Chongqing 400065 China Chongqing MAS Science and Technology Co. Ltd Chongqing 400065 China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783319005355

This paper introduces the application of radio frequency identification (RFID) technology in coal mine safety. As one of the most important part of the radio frequency identification (RFID) system, RFID middleware is introduced. To resolve the problem of processing great number of RFID datum, the data filter method becomes a very hot filed for researching. Several filter methods are researched and analysed in the paper. The readers collect the data from the tags. The algorithm is to filter the data which is within the scope of setting. The algorithm achieves the effect of filter redundant data. © 2014 Springer International Publishing Switzerland.

关键词： Middleware

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The design of the RF front-end of reader based on SAW RFID

The design of the RF front-end of reader based on SAW RFID

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2nd International Conference on Communications, Signal processing, and systems, CSPS 2013

作者： Wu, Fuhai Huang, Jun Ma, Cheng Leng, Yujun Yang, Jing Xiao, Shilin Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications Chongqing 400065 China Chongqing MAS Science and Technology Co. LTD Chongqing 400065 China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783319005355

This paper first describes the system architecture and operating principle of SAW Radio Frequency Identification Devices (RFID). Then it provides the designing scheme to the radio frequency front end of 915 MHz ultra high frequency (UHF) reader. At last, it lists the test method to the RF front end system, and system-level verification of RFID reader. The results show that, this design meets the performance index of 915 MHz reader, and has properties of reliability, efficiency and flexibility in configuration and maintenance. © 2014 Springer International Publishing Switzerland.

关键词： Radio waves

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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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Multiple description coding with randomly and uniformly offset quantizers

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IEEE Transactions on Image processing 2014年第2期23卷 582-595页

作者： Meng, Lili Liang, Jie Samarawickrama, Upul Zhao, Yao Bai, Huihui Kaup, Andre Institute of Information Science Beijing Jiaotong University Beijing 100044 China School of Information Science and Engineering Shandong Normal University Jinan 730050 China School of Engineering Science Simon Fraser University Burnaby BC V5A 1S6 Canada Microsoft Corporation Redmond WA 98052 United States State Key Laboratory of Rail Traffic Control and Safety Beijing 100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100011 China Department of Multimedia Communications and Signal Processing University of Erlangen-Nuremberg Erlangen 91058 Germany

In this paper, two multiple description coding schemes are developed, based on prediction-induced randomly offset quantizers and unequal-deadzone-induced near-uniformly offset quantizers, respectively. In both schemes, each description encodes one source subset with a small quantization stepsize, and other subsets are predictively coded with a large quantization stepsize. In the first method, due to predictive coding, the quantization bins that a coefficient belongs to in different descriptions are randomly overlapped. The optimal reconstruction is obtained by finding the intersection of all received bins. In the second method, joint dequantization is also used, but near-uniform offsets are created among different low-rate quantizers by quantizing the predictions and by employing unequal deadzones. By generalizing the recently developed random quantization theory, the closed-form expression of the expected distortion is obtained for the first method, and a lower bound is obtained for the second method. The schemes are then applied to lapped transform-based multiple description image coding. The closed-form expressions enable the optimization of the lapped transform. An iterative algorithm is also developed to facilitate the optimization. Theoretical analyzes and image coding results show that both schemes achieve better performance than other methods in this category. © 1992-2012 IEEE.

关键词： Image coding

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A Two-stage CMOS Integrated Highly Efficient Rectifier for Vibration Energy Harvesting Applications

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Journal of International Council on Electrical Engineering 2014年第4期4卷 336-340页

作者： Qiang Li Jing Wang Dan Niu Graduate School of Information Production and Systems Waseda University Key Laboratory of Measurement and Control of CSE Southeast University

– We report, in this paper, a highly efficient CMOS rectifier for low power energy harvesting system. By using two-stage structure and a novel active diode, the rectifier can work at a wide range of input voltage amplitudes of 0.45V up to 1.8V under a standard 0.18um CMOS process. A comparator that consists of common-gate stage and control stage is designed to control the switch of the active diode. The proposed rectifier can achieve a peak voltage conversion efficiency of over 96% and a power efficiency over 90%. Simulated power consumption of the rectifier is 197nW at 450mV, which is about 30% smaller than the best recently published results.

关键词： Negative voltage converter Wide range Rectifier

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Robust visual tracking based on local kernelized representation

Robust visual tracking based on local kernelized representat...

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IEEE International Conference on Robotics and Biomimetics

作者： Qiaozhe Li Yu Qiao Jie Yang Key Laboratory of Ministry of Education for System Control and Information Processing Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479973989

Visual tracking, when regarded as a classification problem, usually need sufficient amount of data for online learning. Current approaches usually employ multiple binary labeled samples to train or update the appearance model at each frame. However, most positive samples collected by perturbation of the target location are equally treated as the estimated target when used for updating. The exact target information might be ambiguous. In this paper, we propose a robust visual tracking algorithm based on local kernelized representation. The use of kernels incorporates the target information to better represent each samples. Local kernel scores, which measure the similarity between samples and target templates in specific feature space, are used to form feature vector to represent the entire region. A neural network is then deployed into the particle Alter framework to estimate target location. Experimental results on a variety of challenging sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.

关键词： Conferences Robots Biomimetics

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An information Diffusion Model Based on Individual Characteristics

An Information Diffusion Model Based on Individual Character...

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第三十三届中国控制会议

作者： Jun Hua Lin Wang Xiaofan Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education

ISBN: (纸本)9781479947249

We proposes a model of information diffusion over social networks, in which individuals can be classified into innovative ones and conformable ones according to their reactions to new information. By simulations over various networks,we find that both the network structure and the composition of population have apparent effect on the extent of information diffusion. We also find that, in different stages of diffusion, innovative individuals and conformable individuals play different roles to promote the spread of information. Furthermore, initial conditions such as which kind of individual is initially activated also has impact on the diffusion.

关键词： Complex networks,information diffusion,Individual characteristics

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Structure reconstruction for linear network systems with dynamical structure functions

Structure reconstruction for linear network systems with dyn...

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第三十三届中国控制会议

作者： Tongcai Wang Lin Wang Xiaofan Wang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education

ISBN: (纸本)9781479947249

The state-space model for linear network systems which represents the structure information, in general, cannot be recovered from the dynamical input-output data, since typically the realization problem does not have a unique *** structure functions have been introduced to represent the structural information only between the *** though, it has shown that for a given network composed of p measured individuals, in order to completely recover the relationships between the measurements, p experiments with each experiment independently controlling a measured individual must be performed. This paper will investigate the structure reconstruction for a kind of linear networks, in which all states are measurable, but only partial states can be directly controlled by external inputs. Therefore, the network structure cannot be inferred directly by making use of the dynamical structure function. A new algorithm is proposed, in which the relations between the nodes with input are obtained from the dynamical structure function;and then, the influences from the nodes with control input to the nodes without are deduced;and finally, a convex optimization algorithm with a sparsity assumption is used to infer the full structure information.

关键词： Network reconstruction,Linear systems,Dynamical structure function,Transfer function,Convex optimization

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Station-keeping control method for GEO satellite based on relative orbit dynamics

Station-keeping control method for GEO satellite based on re...

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World Congress on Intelligent control and Automation (WCICA)

作者： Wenbo Yang Shaoyuan Li Ning Li Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai CN

Based on the analysis of relative orbit dynamics for GEO (geostationary orbit, GEO) satellite and LQG (Linear Quadratic Gaussian, LQG) algorithm, this paper proposed a station-keeping control method for GEO satellite, which realized north-south station-keeping and west-east station-keeping simultaneously. To further verify the effectiveness of the proposed method, corresponding mathematical simulation is carried out. Simulation results show that the proposed method can obtain good control precision compared with conventional station-keeping control method of GEO satellite. Thus, the proposed method is suitable for station-keeping control of GEO satellite.

关键词： Satellites Orbits Equations Mathematical model Acceleration Vectors control systems

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A Noise Removal Approach for Object-based Classification of VHR Imagery via Post-classification

A Noise Removal Approach for Object-based Classification of ...

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International Conference on Audio, Language and Image processing

作者： Laiwen Zheng Lihong Wan Hong Huo Tao Fang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781479939046

The pixel-based classification of remotely sensed images always produces a large amount of "speckled" or "salt and pepper" noises. Both post-classification smoothing and object-based classification techniques have been proposed to tackle this problem. However, most of them are not adequate to deal with the noises in object-based classification of very high resolution (VHR) remote sensing imagery, because a lot of noisy regions will be produced by image segmentation and the existing post-classification approaches generally are tailored towards pixel-based classification. This paper proposes a novel noise removal approach for object-based classification of VHR imagery via post-classification. It includes four phases: firstly, an image is segmented into homogeneous regions;secondly, all regions are classified according to their spectral and texture features;thirdly, noisy regions are distinguished by using shape features. Finally, the noisy regions are removed by using contextual features. Experimental results show the proposed approach is effective and can improve the overall accuracy of classification of VHR remote sensing imagery.

关键词： VHR Remote Sensing Imagery Object-based Classification Noise Removal Post-classification

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