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The 5th International Conference on Biomedical engineering and Biotech.ology (ICBEB 2016) Abstracts

BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Learning transferable features with deep adaptation networks 32

Learning transferable features with deep adaptation networks

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32nd International Conference on Machine Learning, ICML 2015

作者： Long, Mingsheng Cao, Yue Wang, Jianmin Jordan, Michael I. School of Software TNList Lab for Info. Sci. and Tech. Institute for Data Science Tsinghua University China Department of Electrical Engineering and Computer Science University of California BerkeleyCA United States

ISBN: (纸本)9781510810587

Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation Network (DAN) architecture, which generalizes deep convolutional neural network to the domain adaptation scenario. In DAN, hidden representations of all task-specific layers are embedded in a reproducing kernel Hilbert space where the mean embeddings of different domain distributions can be explicitly matched. The domain discrepancy is further reduced using an optimal multi-kernel selection method for mean embedding matching. DAN can learn transferable features with statistical guarantees, and can scale linearly by unbiased estimate of kernel embedding. Extensive empirical evidence shows that the proposed architecture yields state-of-the-art image classification error rates on standard domain adaptation benchmarks.

关键词： Network architecture

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Survey on Privacy Protection of Android Devices 2

Survey on Privacy Protection of Android Devices

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2nd IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2015

作者： Liang, Hongliang Wu, Dongyang Xu, Jiuyun Ma, Hengtai School of Computer Science Beijing University of Posts and Telecommunications Beijing China School of Computer and Communication Engineering China University of Petroleum Qingdao China Sci. and Tech. on Integrated Info. System Lab Institute of Software CAS Beijing China

ISBN: (纸本)9781467392990

Nowadays, the ubiquity of smart phones make them carry large amounts of personal sensitive information, but at the same time, there are also many Apps in Android APP market that target to collect users' sensitive data. So it becomes quite important to prevent users from the threat of privacy leakage. In this paper, we analyze the Android's privacy protection mechanism, and describe various threats to users' different types of privacy data. After that, we enumerate two ways that can leak sensitive information, and discuss the current solutions and tech.iques from aspects of privacy protection enhancement and privacy leakage detection. We also make a fine-grained classification for these two aspects, and study the difference between solutions in each category. Finally, we summarize the deficiency of existing research of Android privacy protection and propose the future research direction. © 2015 IEEE.

关键词： Surveys

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MM3C: Multi-Source Mobile Streaming in Cache-enabled Content-Centric Networks

MM3C: Multi-Source Mobile Streaming in Cache-enabled Content...

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IEEE Global Communications Conference

作者： Dung Ong Mau Tarik Taleb Min Chen School of Computer Science and Technology Huazhong University of Sci. & Tech. School of Electrical Engineering Aalto University

ISBN: (纸本)9781479959532

Along with an ever-growing demand for rich video applications by a rapidly increasing population of mobile users, it is becoming difficult for the Internet backbone to cope with a constantly increasing mobile traffic. Though multi-source mobile streaming (MS~2) was proposed to solve the bottleneck issue of the Internet backbone considering simultaneous multiple low streaming rate transmissions to mobile users, it does not consider redundant transmissions of popular contents. Recently, Content Centric Networking (CCN) is proposed as a content name-oriented approach to disseminate content to edge gate-ways/routers. In CCN, if the content is popular, the previously queried content can be reused for multiple times to save band-width capacity, reduce overall energy consumption, and improve users' Quality of Experience (QoE). Inheriting all advantages of CCN, a novel architecture "MM3C", which integrates CCN with MS~2, is proposed as a better solution to the problem. Using OPNET, the performance of MM3C is evaluated. Compared to MS~2 under the same network configuration, the simulation results show that MM3C exhibits less bottleneck links, shorter round trip times, and better performance in terms of traffic offloading.

关键词： Internet Backbone Mobile Streaming network configuration Transmissions energy consumption Consumers CCNL2 gene Traffic Bottlenecks

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Fast ℓ0-norm-based single image blind deblurring: A comparative study

Fast ℓ0-norm-based single image blind deblurring: A compara...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Wen-Ze Shao Shi-Peng Xie Qi Ge Hai-Bo Li Li-Li Huang Zhi-Hui Wei College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications China Nanjing Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Sci. & Tech. China Nanjing School of Science Guangxi University of Science and Technology China Liuzhou School of Computer Science and Technology Nanjing University of Science and Technology China Nanjing

ISBN: (纸本)9781467376839

Single image blind deblurring has been intensively studied since Fergus et al.'s variational Bayes method in 2006. It is now commonly believed that the blur-kernel estimation accuracy is highly dependent on the pursed salient edge information from the blurred image, which stimulates numerous ℓ 0 -approximating blind deblurring methods via kinds of tech.iques and tricks. This paper, however, focuses on the four recent daring attempts which are all based on the simple and direct ℓ 0 -norm. A systematic comparative analysis is made towards those methods, clarifying their similarities and differences, and providing a benchmark evaluation on both the deblurring quality and computational efficiency. Results have demonstrated that the ℓ 0 -norm alone is far enough to achieve top blind deblurring performance. Instead, details are to be paid with fairly more attention as working on the problem formulation as well as the algorithmic deduction. Besides, three possible extensions are analyzed on the most leading bi-ℓ 0 -ℓ 2 -norm regularization-based blind deblurring method.

关键词： Estimation Image edge detection Kernel Deconvolution Minimization Image restoration Benchmark testing

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Head detection based on convolutional neural network with multi-stage weighted feature

Head detection based on convolutional neural network with mu...

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IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)

作者： Ting Rui Jian-chao Fei Peng Cui You Zhou Hu-sheng Fang College of Field Engineering PLA Univ. of Sci. & Tech. Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China Jiangsu Institute of Commerce Nanjing China

ISBN: (纸本)9781479919499

Human head detection is an important means of pedestrian detection and counting. By now, head detection is mainly based on outline, color and template which have low recognition rate and error tolerance. Recently, deep learning has become a research hotspot in the field of pattern recognition. As a model of deep learning, convolutional neural network (CNN) performs well in the areas of image recognition and speech analysis. In this paper, a new method based on CNN was proposed. This method uses a few new twists, such as multi-stage weighted feature and connections that skip layers to integrate global shape information and local motif information. The experimental results show that the proposed method performs a higher accuracy on head detection compared with the traditional ones'.

关键词： convolutional neural network deep learning human head detection multi-stage feature Head Machine Learning Neural network Speech analysis Image recognition shape information Pattern recognition Head Louse Connections

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High gain low-profile circularly polarized Fabry-Perot Resonator array with linearly polarized feed

High gain low-profile circularly polarized Fabry-Perot Reson...

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Asia-Pacific Conference on Microwave

作者： Zhen-Guo Liu Zhen-Xin Cao Le-Nan Wu Tian-Zhong Zhu School of Information Science and Engineering Southeast University Nanjing China Zhangjiagang Free Trade Zone Canqin Sci. & Tech. Co. Ltd Zhangjiagang China

ISBN: (纸本)9781479987689

A novel low profile circularly polarized Fabry-Perot Resonator (CP-FPR) array of 2×2 elements consisting of the CP-FPR antenna with a linearly polarized feed is presented. The proposed CP-FPR antenna consists of a primary radiator aligned along 45° with linear polarization, a partially reflective surface formed by cross-slot FSS and a nonstandard AMC acting as reflective ground plane. The profile of antenna can also be reduced to a quarter of a wavelength. The array with a compact sequential rotation feeding scheme was optimized to minimize grating lobes and reduce the sidelobe level, even though the element spacing was about two wavelengths. The measured common bandwidth is about 7.4%.

关键词： Frequency measurement Frequency selective surfaces Decision support systems Polarization Scattering parameters

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Survey on Privacy Protection of Android Devices

Survey on Privacy Protection of Android Devices

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Hongliang Liang Dongyang Wu Jiuyun Xu Hengtai Ma School of Computer Science Beijing University of Posts and Telecommunications Beijing China School of Computer & Communication Engineering China University of Petroleum Qingdao China Sci. & Tech. on Integrated Info. System Lab Institute of Software CAS Beijing China

关键词： Privacy Androids Humanoid robots Smart phones Data privacy Security

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Robust Transceiver Design for MISO Interference Channel with Energy Harvesting

Robust Transceiver Design for MISO Interference Channel with...

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IEEE Vehicular tech.ology Conference

作者： Ming-Min Zhao Yunlong Cai Qingjiang Shi Benoit Champagne Min-Jian Zhao College of Information Science and Electronic Engineering Zhejiang University Hangzhou China 310027 School of Info. Sci. & Tech. Zhejiang Sci-Tech University Hangzhou China 310018 Department of Electrical and Computer Engineering McGill University Montreal QC Canada H3A 0E9

ISBN: (纸本)9781479980925

In this paper, we consider the power splitting tech.ique for multiple-input single-output (MISO) interference channel where the received signal is divided into two parts for information decoding and energy harvesting (EH) respectively. Specifically, assuming norm-bounded errors (NBE) in the channel state information (CSI), we study the robust joint beamforming and power splitting (JBPS) design problem, where the total transmission power is minimized subject to both signal-to-interference-plus-noise ratio (SINR) and EH constraints. We first propose an efficient approximation method based on semidefinite relaxation (SDR) for solving the highly non-convex JBPS problem, where the latter can be formulated as a semidefinite programming (SDP) problem. Then, a low complexity algorithm is proposed using EH relaxation and cutting-set philosophy, which partitions the original problem into an alternating sequence of optimization and worst-case analysis subproblems with guaranteed convergence. Finally, simulation results are presented to validate the robustness and efficiency of the proposed algorithms.~1

关键词： MISO interference channel beamforming power splitting semidefinite programming second-order cone programming cutting-set method power splitting Interference channels Beamforming energy harvesting multiple-input single-output Approximation method power transmission OFFICE OF THE ASSISTANT SECRETARY FOR ENVIRONMENT, ET. AL.

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REED: A Reliable Energy-Efficient RAID

REED: A Reliable Energy-Efficient RAID

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International Conference on Parallel Processing (ICPP)

作者： Shu Yin Xuewu Li Kenli Li Jianzhong Huang Xiaojun Ruan Xiaomin Zhu Wei Cao Xiao Qin School of Information Science & Engineering National Supercomputing Center in Changsha Changsha China Dept. of Computer Science Huazhong Univ. of Sci. and Tech. Wuhan China Dept. of Computer Science West Chester Univ. of Pennsylvania PA Sci. & Tech. on Information System Eng. Lab National University of Defense Technology Changsha China Hubei Meteorological Information. & Technology Support Center Wuhan China Dept. of Compter Sci. & Software Eng. Auburn University AL

ISBN: (纸本)9781467375887

Recent studies indicate that the energy cost and carbon footprint of data centers have become exorbitant. It is a demanding and challenging task to reduce energy consumption in large-scale storage systems in modern data centers. Most energy conservation tech.iques inevitably have adverse impacts on parallel disk systems. To address the reliability issues of energy-efficient parallel disks, we propose a reliable energy-efficient RAID system called REED, which aims at improving both energy efficiency and reliability of RAID systems by seamlessly integrating HDDs and SSDs. At the heart of REED is a high-performance cache mechanism powered by SSDs, which are serving popular data. Under light workload conditions, REED spins down HDDs into the low-power mode, thereby offering energy conservation. Importantly, during an I/O access turbulence (i.e., I/O load is dynamically and frequently changing), REED is conducive to reducing the number of disk power-state transitions by keeping HDDs in the low-power mode while serving requests with SSDs. We build a model to quantitatively show that REED is capable of improving the reliability of energy-efficient RAIDs. We implement the REED prototype in a real-world RAID-0 system. Our experimental results demonstrate that REED improves the energy-efficiency of conventional RAID-0 by up to 73% while maintaining good reliability.

关键词： Reliability Solids Electronic mail Energy consumption Energy conservation Energy storage Power demand

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