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Special section guest editorial: Optical and hybrid imaging and processing for big data problems

Optical engineering 2014年第1期53卷 011001-011001页

作者： Iftekharuddin, Khan M. Awwal, Abdul A. S. Susan Young, S. Abdulla, Ghaleb M. Old Dominion University Electrical and Computer Engineering Department 231 Kaufman Hall Norfolk VI 23529 United States Lawrence Livermore National Laboratory L-395 P.O. Box 808 Livermore CA 94551-0808 United States U.S. Army Research Laboratory 2800 Powder Mill Road Adelphi MD 20783 United States Lawrence Livermore National Laboratory Center for Applied Scientific Computing United States

The scientific community has been dealing with big data for a long time. Due to advancement in sensing, networking, and storage technology, other domains such as business, health, and social media followed. Data are considered the gold of the 21st century and are being collected, stored, and analyzed at a rapid pace. The amount of data being collected creates a compelling case for investing in hardware and software research to support generating even more data from new sensors and with better quality. It also creates a compelling case for investing in research and development of new hardware and software for data analytics. This special section of Optical engineering explores the optical and hybrid imaging and processing technology that will enable capturing and analyzing large amounts of data or help stream the data for further exploration and analysis.

关键词： Algorithms Data acquisition Data analysis Image analysis computer hardware Optical engineering Sensors Scanning Graphics processing units Holograms Software computing systems Near field diffraction Near infrared Networks Optical imaging Optical systems Optics Remote sensing Transform theory Water Web 2.0 technologies Hough transforms Image acquisition Image encryption Image transmission LIDAR Light wave propagation Liquid crystals Data mining Data storage Gold Analytics Anisotropy Astronomy

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Local linear spectral hashing

Local linear spectral hashing

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Kang Liu, Dengxiang Lu, Hongtao MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

Hashing for large scale image retrieval has become more and more popular because of its improvement in computational speed and storage reduction. Spectral Hashing (SH) is a very efficient unsupervised hashing method through mapping similar images to similar binary codes. However, it doesn't take the non-neighbor points into consideration, and its assumption of uniform data distribution is usually not true. In this paper, we propose a local linear spectral hashing framework that minimizes the average Hamming distance with a new local neighbor matrix, which can guarantee the mapping not only from neighbor images to neighbor codes, but also from non-neighbor images to non-neighbor codes. Based on the framework, we utilize three linear methods to handle the proposed problem, including orthogonal hashing, non-orthogonal hashing, and sequential hashing. The experiments on two huge datasets demonstrate the efficiency and accuracy of our methods. © Springer-Verlag 2013.

关键词： Hamming distance

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Image classification based on weight adjustment before feature pooling

Image classification based on weight adjustment before featu...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Feng, Shaokun Lu, Hongtao Huang, Lei MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

In image classification based on Bag-of-Features(BoF), the Locality-constrained Linear Coding (LLC) is a successful implementation, which is a more effective coding scheme compared with the traditional vector quantization(VQ) coding. Although, to achieve the best performance, max pooling scheme is chosen in the SPM layer, much of the spatial information is still lost during the pooling step, because all the coded descriptors are given the same importance to obtain the final representation. In this paper, we propose a new scheme that makes full use of spatial structure information to readjust their relative weights red and thus give some descriptors more chances to appear in the final feature vector more than others. Experiments of image classification on benchmark datasets show that the proposed method outperforms the LLC method. © Springer-Verlag 2013.

关键词： Image classification

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Stretchable Electronics: Epidermal Electronics with Advanced Capabilities in Near-Field Communication (Small 8/2015)

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Small 2015年第8期11卷

作者： Jeonghyun Kim Anthony Banks Huanyu Cheng Zhaoqian Xie Sheng Xu Kyung-In Jang Jung Woo Lee Zhuangjian Liu Philipp Gutruf Xian Huang Pinghung Wei Fei Liu Kan Li Mitul Dalal Roozbeh Ghaffari Xue Feng Yonggang Huang Sanjay Gupta Ungyu Paik John A. Rogers Department of Materials Science and Engineering Frederick Seitz Materials Research Laboratory University of Illinois at Urbana-Champaign Urbana IL 61801 USA Department of Materials Science and Engineering Department of Energy Engineering Hanyang University Seoul 133–791 Republic of Korea Department of Mechanical Engineering Civil and Environmental Engineering Center for Engineering and Health and Skin Disease Research Center Northwestern University Evanston IL 60208 USA Department of Engineering Mechanics Center for Mechanics and Materials Tsinghua University Beijing 100084 China Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 USA Institute of High Performance Computing 1 Fusionopolis Way #16–16 Connexis Singapore 138632 Singapore Functional Materials and Microsystems Research Group School of Electrical and Computer Engineering RMIT University Melbourne VIC 3000 Australia MC10 Inc. Cambridge Massachusetts 02140 USA Department of Engineering Mechanics Tsinghua University Beijing 100084 China

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Protection design and coordination of DC Distributed Power systems Architectures

Protection design and coordination of DC Distributed Power S...

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2013 IEEE Power and Energy Society General Meeting, PES 2013

作者： Vanteddu, Sri Raju Bushanam Mohamed, Ahmed Mohammed, Osama Energy Systems Research Laboratory Department of Electrical and Computer Engineering Florida International University Miami FL 33174 United States

ISBN: (纸本)9781479913039

In this paper, a complete protection system for a DC distribution system was developed and presented. The developed protection scheme was designed to be implemented on the laboratory-based DC Distributed Power systems Architecture (DPSA) testbed setup. This system consists of four AC generators in addition to a DC microgrid involving photovoltaic generation and battery storage. The total capacity of the DPSA is 72 kW. The developed protection scheme targets faults on the AC side as well as faults on the DC sides. Moreover, the coordination scheme between different types of faults was designed. The challenges associated with protecting DC systems such as arcing and system time constant were investigated. The results obtained verify the validity of the developed protection system. © 2013 IEEE.

关键词： Electric equipment protection

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An evaluation framework for software crowdsourcing

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Frontiers of computer Science 2013年第5期7卷 694-709页

作者： Wenjun WU Wei-Tek TSAI Wei LI State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ85281 USA Department of Computer Science and Technology INLIST Tsinghua University Beijing 100084 China

Recently software crowdsourcing has become an emerging area of software engineering. Few papers have pre- sented a systematic analysis on the practices of software crowdsourcing. This paper first presents an evaluation frame- work to evaluate software crowdsourcing projects with re- spect to software quality, costs, diversity of solutions, and competition nature in crowdsourcing. Specifically, competi- tions are evaluated by the min-max relationship from game theory among participants where one party tries to minimize an objective function while the other party tries to maximize the same objective function. The paper then defines a game theory model to analyze the primary factors in these min- max competition rules that affect the nature of participation as well as the software quality. Finally, using the proposed eval- uation framework, this paper illustrates two crowdsourcing processes, Harvard-TopCoder and AppStori. The framework demonstrates the sharp contrasts between both crowdsourc- ing processes as participants will have drastic behaviors in engaging these two projects.

关键词： crowdsourcing software engineering competi-tion rules game theory

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A frequency boosting method for motor imagery EEG classification in BCI-FES rehabilitation training system

A frequency boosting method for motor imagery EEG classifica...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Liang, Jianyi Zhang, Hao Liu, Ye Wang, Hang Li, Junhua Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390678

Common Spatial Pattern (CSP) and Support Vector Machine (SVM) are usually adopted for feature extraction and classification of two-class motor imagery. However, in a motor imagery based BCI-FES rehabilitation system, stroke patients usually are not able to conduct correct motor imagery like healthy people due to the injury of motor cortex. Therefore, motor imagery EEG of stroke patients lacks of specific discriminant features as appearances of healthy people, which significantly blocks CSP to seek the optimal projection subspace. In this paper, a method, which filters EEG into a variety of bands and improves performance through boosting principle based on a set of weak CSP-SVM classifiers, was proposed to solve the problem mentioned above and was evaluated on the EEG datasets of three stroke subjects. The proposed method outperformed the traditional CSP-SVM method in terms of classification accuracy. From data analysis, we observed that optimal spectral band for classification had been changing along with rehabilitation training, which may reveal mechanisms that dominant frequency band may be changed along with rehabilitation training and spectral power distribution may be changed in different stages of rehabilitation. In addition, this work also demonstrated the feasibility of our SJTU-BCMI BCI-FES rehabilitation training system. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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Hidden Markov model for action recognition using joint angle acceleration

Hidden Markov model for action recognition using joint angle...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Huang, Sha Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

This paper proposes a recognition method of human actions in video by adding new features, the joint angle acceleration to the feature space. In this method, human body is described as three-dimensional skeletons. The features consist of vectors of several important joint angles on the human body and the joint angle accelerations are also considered as a part of features. Hidden Markov Model (HMM) is used as classification scheme. The HMM models are trained by sequences extracted from the CMU graphics lab motion capture database 1. This method is invariant to scale, coordinate system and transition. A system is implemented to recognize 4 different types of actions (walk, run, jump and jumping jack) both on the dataset of CMU and Weizmann[7]. Each video clip contains a single action type. The experimental results show excellent performance of the proposed approach. A maximum 10.3% accuracy gain can be achieved by our method compared with the method without considering acceleration. © Springer-Verlag 2013.

关键词： Hidden Markov models

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UMPCA based feature extraction for ECG

UMPCA based feature extraction for ECG

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10th International Symposium on Neural Networks, ISNN 2013

作者： Li, Dong Huang, Kai Zhang, Hanlin Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390647

In this paper, we propose an algorithm for 12-leads ECG signals feature extraction by Uncorrelated Multilinear Principal Component Analysis(UMPCA). However, traditional algorithms usually base on 2-leads ECG signals and do not efficiently work out for 12-leads signals. Our algorithm aims at the natural 12-leads ECG signals. We firstly do the Short Time Fourier Transformation(STFT) on the raw ECG data and obtain 3rd-order tensors in the spatial-spectral- temporal domain, then take UMPCA to find a Tensor-to-Vector Projection(TVP) for feature extraction. Finally the Support Vector Machine(SVM) classifier is applied to achieve a high accuracy with these features. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Tensors

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Optimal calculation of tensor learning approaches

Optimal calculation of tensor learning approaches

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10th International Symposium on Neural Networks, ISNN 2013

作者： Huang, Kai Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390647

Most algorithms have been extended to the tensor space to create algorithm versions with direct tensor inputs. However, very unfortunately basically all objective functions of algorithms in the tensor space are non-convex. However, sub-problems constructed by fixing all the modes but one are often convex and very easy to solve. However, this method may lead to difficulty converging;iterative algorithms sometimes get stuck in a local minimum and have difficulty converging to the global solution. Here, we propose a computational framework for constrained and unconstrained tensor methods. Using our methods, the algorithm convergence situation can be improved to some extent and better solutions obtained. We applied our technique to Uncorrelated Multilinear Principal Component Analysis (UMPCA), Tensor Rank one Discriminant Analysis (TR1DA) and Support Tensor Machines (STM);Experiment results show the effectiveness of our method. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Tensors

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