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ISSN 1004-9037
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Publication Details
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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  • Table of Content
      05 September 2014, Volume 29 Issue 5   
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    Preface
    Preface
    Ke Liu, Zhi-Yong Liu
    Journal of Data Acquisition and Processing, 2014, 29 (5): 737-739. 
    Abstract   PDF(193KB) ( 1089 )  
    Artificial Intelligence and Pattern Recognition
    Pattern Matching with Flexible Wildcards
    Xindong Wu, Ji-Peng Qiang, Fei Xie
    Journal of Data Acquisition and Processing, 2014, 29 (5): 740-750. 
    Abstract   PDF(445KB) ( 2580 )  
    Pattern matching with wildcards (PMW) has great theoretical and practical significance in bioinformatics, information retrieval, and pattern mining. Due to the uncertainty of wildcards, not only the number of all matches is exponential with respect to the maximal gap flexibility and the pattern length, but the matching positions in PMW are also hard to choose. The objective to count the maximal number of matches one by one is computationally infeasible. Therefore, rather than solving the generic PMW problem, many research efforts have further defined new problems within PMW according to different application backgrounds. To break through the limitations of either fixing the number or allowing an unbounded number of wildcards, pattern matching with flexible wildcards (PMFW) allows the users to control the ranges of wildcards. In this paper, we provide a survey on the state-of-the-art algorithms for PMFW, with detailed analyses and comparisons, and discuss challenges and opportunities in PMFW research and applications
    Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception
    Jia Jia, Wai-Kim Leung, Yu-Hao Wu, Xiu-Long Zhang, Hao Wang, Lian-Hong Cai, Helen M. Meng
    Journal of Data Acquisition and Processing, 2014, 29 (5): 751-761. 
    Abstract   PDF(1872KB) ( 1443 )  
    Computer-aided pronunciation training (CAPT) technologies enable the use of automatic speech recognition to detect mispronunciations in second language (L2) learners' speech. In order to further facilitate learning, we aim to develop a principle-based method for generating a gradation of the severity of mispronunciations. This paper presents an approach towards gradation that is motivated by auditory perception. We have developed a computational method for generating a perceptual distance (PD) between two spoken phonemes. This is used to compute the auditory confusion of native language(L1). PD is found to correlate well with the mispronunciations detected in CAPT system for Chinese learners of English, i.e., L1 being Chinese (Mandarin and Cantonese) and L2 being US English. The results show that auditory confusion is indicative of pronunciation confusions in L2 learning. PD can also be used to help us grade the severity of errors (i.e., mispronunciations that confuse more distant phonemes are more severe) and accordingly prioritize the order of corrective feedback generated for the learners.
    Protect You More Than Blank: Anti-learning Sensitive User Information in the Social Networks
    Mingxuan Yuan, Lei Chen, Philip S. YU, Hong Mei
    Journal of Data Acquisition and Processing, 2014, 29 (5): 762-776. 
    Abstract   PDF(1855KB) ( 1985 )  
    Social networks are getting more and more attention in recent years. People join social networks to share their information with others. However, due to the different cultures and backgrounds, people have different requirements on what kind of information should be published. Currently, when social network websites publish data, they just leave the information that a user feels sensitive blank. This is not enough due to the existence of the label-structure relationship. A group of analyzing algorithms can be used to learn the blank information with high accuracy. In this paper, we propose a personalized model to protect private information in social networks. Specifically, we break the label-structure association by slightly changing the edges in some users' neighborhoods. More importantly, in order to increase the usability of the published graph, we also preserve the influence value of each user during the privacy protection. We verify the effectiveness of our methods through extensive experiments. The results show that the proposed methods can protect sensitive labels against learning algorithms and at the same time, preserve certain graph utilities.
    Computer Graphics and Multimedia
    Seeing Human Weight from a Single RGB-D Image
    Tam V. Nguyen, Jiashi Feng, Shuicheng Yan
    Journal of Data Acquisition and Processing, 2014, 29 (5): 777-784. 
    Abstract   PDF(1722KB) ( 1677 )  
    Human weight estimation is useful in a variety of potential applications, e.g., targeted advertisement, entertainment scenarios and forensic science. However, estimating weight only from color cues is particularly challenging since these cues are quite sensitive to lighting and imaging conditions. In this article, we propose a novel weight estimator based on a single RGB-D image, which utilizes the visual color cues and depth information. Our main contributions are three-fold. First, we construct the W8-RGBD dataset including RGB-D images of different people with ground truth weight. Second, the novel sideview shape feature and the feature fusion model are proposed to facilitate weight estimation. Additionally, we consider gender as another important factor for human weight estimation. Third, we conduct comprehensive experiments using various regression models and feature fusion models on the new weight dataset, and encouraging results are obtained based on the proposed features and models.
    Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues
    Zhi-Neng Chen, Chong-Wah Ngo, Wei Zhang, Juan Cao, Yu-Gang Jiang
    Journal of Data Acquisition and Processing, 2014, 29 (5): 785-798. 
    Abstract   PDF(9096KB) ( 1575 )  
    Associating faces appearing in Web videos with names presented in the surrounding context is an important task in many applications. However, the problem is not well investigated particularly under large-scale realistic scenario, mainly due to the scarcity of dataset constructed in such circumstance. In this paper, we introduce a Web video dataset of celebrities, named WebV-Cele, for name-face association. The dataset consists of 75,073 Internet videos of over 4,000 hours, covering 2,427 celebrities and 649,001 faces. This is to our knowledge the most comprehensive dataset for this problem. We describe the details of dataset construction, discuss several interesting findings by analyzing this dataset like celebrity community discovery, and provide experimental results of name-face association using five existing techniques. We also outline important and challenging research problems that could be investigated in the future.
    Crowd Simulation and Its Applications: Recent Advances
    Ming-Liang Xu, Hao Jiang, Xiao-Gang Jin, Zhigang Deng
    Journal of Data Acquisition and Processing, 2014, 29 (5): 799-811. 
    Abstract   PDF(12938KB) ( 1526 )  
    This article surveys the state of the art crowd simulation techniques and their selected applications, with its focus on our recent research advances in this rapidly growing research field. We first give a concise overview on the mainstream methodologies of crowd simulation. Then, we describe our recent research advances on crowd evacuation, pedestrian crowds, crowd formation, traffic simulation, and swarm simulation. Finally, we offer our own perspectives on open crowd simulation research challenges and point out potential future directions in this area.
    Designing Motion Gesture Interfaces in Mobile Phones for Blind People
    Nem Khan Dim, Xiangshi Ren
    Journal of Data Acquisition and Processing, 2014, 29 (5): 812-824. 
    Abstract   PDF(3136KB) ( 1423 )  
    Despite the existence of advanced functions in smartphones, most blind people are still using old-fashioned phones with familiar layouts and dependence on tactile buttons. Smartphones support accessibility features including vibration, speech and sound feedback, and screen readers. However, these features are only intended to provide feedback to user commands or input. It is still a challenge for blind people to discover functions on the screen and to input the commands. Although voice commands are supported in smartphones, these commands are difficult for a system to recognize in noisy environments. At the same time, smartphones are integrated with sophisticated motion sensors, and motion gestures with device tilt have been gaining attention for eyes-free input. We believe that these motion gesture interactions offer more efficient access to smartphone functions for blind people. However, most blind people are not smartphone users and they are not aware of the affordances available in smartphones nor of the potential for interaction through motion gestures. To investigate the most usable gestures for blind people, we conducted a user-defined study with 13 blind participants. Using the gesture set and design heuristics from the user study, we implemented motion gesture-based interfaces with speech and vibration feedback for browsing phone books and making a call. We then conducted a second study to investigate the usability of the motion gesture interface and user experiences using the system.
    Assisting Visually Impaired People to Acquire Targets on a Large Wall-Mounted Display
    Kibum Kim, Xiangshi Ren
    Journal of Data Acquisition and Processing, 2014, 29 (5): 825-836. 
    Abstract   PDF(4233KB) ( 1435 )  
    Large displays have become ubiquitous in our everyday lives, but these displays are designed for the needs of sighted people. This paper addresses the need for visually impaired people to access targets on large wall-mounted displays. We developed an assistive interface which exploits mid-air gesture input and haptic feedback, and examined its potential for pointing and steering tasks in human computer interaction (HCI). In two experiments, blind and blindfolded users performed target acquisition tasks using mid-air gestures and two different kinds of feedback, (i.e., haptic feedback and audio feedback). Our results show that participants perform faster in Fitts’ law pointing tasks using the haptic feedback interface rather than the audio feedback interface. Furthermore, a regression analysis between movement time (MT) and the index of difficulty (ID) demonstrates that the Fitts’ law model and the steering law model are both effective for the evaluation of assistive interfaces for the blind. Our work and findings will serve as an initial step to assisting visually impaired people to easily access required information on large public displays using haptic interfaces.
    Encoding Spatial Context for Large-Scale Partial-DuplicateWeb Image Retrieval
    Wen-Gang Zhou, Hou-Qiang Li, Yijuan Lu, Qi Tian
    Journal of Data Acquisition and Processing, 2014, 29 (5): 837-848. 
    Abstract   PDF(7616KB) ( 2108 )  
    Many recent state-of-the-art image retrieval approaches are based on Bag-of-Visual-Words model and represent an image with a set of visual words by quantizing local SIFT (scale invariant feature transform) features. Feature quantization reduces the discriminative power of local features and unavoidably causes many false local matches between images, which degrades the retrieval accuracy. To filter those false matches, geometric context among visual words has been popularly explored for the verification of geometric consistency. However, existing studies with global or local geometric verification are either computationally expensive or achieve limited accuracy. To address this issue, in this paper, we focus on partial-duplicate Web image retrieval, and propose a scheme to encode the spatial context for visual matching verification. An efficient affine enhancement scheme is proposed to refine the verification results. Experiments on partial-duplicate Web image search, using a database of one million images, demonstrate the effectiveness and efficiency of the proposed approach. Evaluation on a 10-million image database further reveals the scalability of our approach.
    Data Management and Data Mining
    Querying Big Data: Bridging Theory and Practice
    Wenfei Fan, Jin-Peng Huai
    Journal of Data Acquisition and Processing, 2014, 29 (5): 849-869. 
    Abstract   PDF(464KB) ( 2118 )  
    Big data introduces challenges to query answering, from theory to practice. A number of questions arise. What queries are ``tractable'' on big data? How can we make big data ``small'' so that it is feasible to find exact query answers? When exact answers are beyond reach in practice, what approximation theory can help us strike a balance between the quality of approximate query answers and the costs of computing such answers? To get sensible query answers in big data, what else do we necessarily do in addition to coping with the size of the data? This position paper aims to provide an overview of recent advances in the study of querying big data. We propose approaches to tackling these challenging issues, and identify open problems for future research.
    Theory and Algorithms
    On Unknown Small Subsets and Implicit Measures: New Techniques for Parameterized Algorithms
    Jianer Chen, Qi-Long Feng
    Journal of Data Acquisition and Processing, 2014, 29 (5): 870-878. 
    Abstract   PDF(354KB) ( 1260 )  
    Parameterized computation is a recently proposed alternative approach to dealing with NP-hard problems. Developing efficient parameterized algorithms has become a very active research area in the current research in theoretical computer science. In this paper, we investigate a number of new algorithmic techniques that were proposed and initiated by ourselves in our research in parameterized computation. The techniques have proved to be very useful and promising, and have led to improved parameterized algorithms for many well-known NP-hard problems.
    On some proximity problems of colored sets
    Cheng-Lin Fan, Jun Luo, Wen-Cheng Wang, Fa-Rong Zhong, Binhai Zhu
    Journal of Data Acquisition and Processing, 2014, 29 (5): 879-886. 
    Abstract   PDF(6608KB) ( 1537 )  
    The maximum diameter color-spanning set problem (MaxDCS) is defined as follows: given n points with m colors, select m points with m distinct colors such that the diameter of the set of chosen points is maximized. In this paper, we design an optimal O(n log n) time algorithm using rotating calipers for MaxDCS in the plane. Our algorithm can also be used to solve the maximum diameter problem of imprecise points modeled as polygons. We also give an optimal algorithm for the all farthest foreign neighbor problem (AFFN) in the plane, and propose algorithms to answer the farthest foreign neighbor query (FFNQ) of colored sets in two and three-dimensional space. Furthermore, we study the problem of computing the closest pair of color-spanning set (CPCS) in d-dimensional space, and remove the log m factor in the best known time bound if d is a constant.
    Computer Networks and Distributed Computing
    Assessing Diagnosis Approaches for Wireless Sensor Networks: Concepts and Analysis
    Rui Li, Ke-Bin Liu, Xiangyang Li, Yuan He, Wei Xi, Zhi Wang, Ji-Zhong Zhao, Meng Wan
    Journal of Data Acquisition and Processing, 2014, 29 (5): 887-900. 
    Abstract   PDF(5333KB) ( 1296 )  
    Diagnosis is of great importance to wireless sensor networks due to the nature of error prone sensor nodes and unreliable wireless links. The state-of-the-art diagnostic tools focus on certain types of faults, and their performances are highly correlated with the networks they work with. The network administrators feel difficult on measuring the effectiveness of their diagnostic approaches and choosing appropriate tools so as to meet the reliability demand. In this work, we introduce the D-vector to characterize the property of a diagnosis approach. The D-vector has five dimensions, namely the Degree of Coupling, the Granularity, the Overhead, the Tool Reliability and the Network Reliability, quantifying and evaluating the effectiveness of current diagnostic tools in certain networks. We employ a skyline query algorithm to find out the most effective diagnosis approaches, i.e., skyline points (SPs), from five dimensions of all potential D-vectors. The selected skyline D-vector points can further guide the design of various diagnosis approaches. In our trace-driven simulations, we design and select tailored diagnostic tools for GreenOrbs, achieving high performance with relatively low overhead.
    Maximizing Networking Capacity in Multi-Channel Multi-Radio Wireless Networks
    Pengjun Wan, Zhi-Guo Wan
    Journal of Data Acquisition and Processing, 2014, 29 (5): 901-909. 
    Abstract   PDF(988KB) ( 1342 )  
    Providing each node with one or more multi-channel radios offers a promising avenue for enhancing the network capacity by simultaneously exploiting multiple non-overlapping channels through different radio interfaces and mitigating interferences through proper channel assignment. However, it is quite challenging to effectively utilize multiple channels and/or multiple radios to maximize throughput capacity. The NSFC Project 61128005 conducted comprehensive algorithmic-theoretic and queuing theoretic studies of maximizing wireless networking capacity in multi-channel multi-radio (MC-MR) wireless networks under the protocol interference model and fundamentally advanced the state of the art. In addition, under the notoriously hard physical interference model this project has taken initial algorithmic studies on maximizing the network capacity, with or without power control. We expect the new techniques and tools developed in this project will have wide applications in capacity planning, resource allocation and sharing, and protocol design for wireless networks, and will serve as the basis for future algorithm developments in wireless networks with advanced features, such as multi-input multi-output (MIMO) wireless networks.
    Allocating Bandwidth in Datacenter Networks: A Survey
    Li Chen, Baochun Li, Bo Li
    Journal of Data Acquisition and Processing, 2014, 29 (5): 910-917. 
    Abstract   PDF(4139KB) ( 1642 )  
    Datacenters have played an increasingly essential role as the underlying infrastructure in cloud computing. As implied by the essence of cloud computing, resources in these datacenters are shared by multiple competing entities, which can be either tenants that rent virtual machines (VMs) in a public cloud such as Amazon EC2, or applications that embrace data parallel frameworks like MapReduce in a private cloud maintained by Google. It has been generally observed that with traditional transport-layer protocols allocating link bandwidth in datacenters, network traffic from competing applications interferes with each other, resulting in a severe lack of predictability and fairness of application performance. Such a critical issue has drawn a substantial amount of recent research attention on bandwidth allocation in datacenter networks, with a number of new mechanisms proposed to efficiently and fairly share a datacenter network among competing entities. In this article, we present an extensive survey of existing bandwidth allocation mechanisms in the literature, covering the scenarios of both public and private clouds. We thoroughly investigate their underlying design principles, evaluate the tradeoff involved in their design choices and summarize them in a unified design space, with the hope of conveying some meaningful insights for better designs in the future.
    Computer Architecture and Systems
    Trusted Integrated Circuits: the Problem and Challenges
    Yong-Qiang Lv, Qiang Zhou, Yi-Ci Cai, Gang Qu
    Journal of Data Acquisition and Processing, 2014, 29 (5): 918-928. 
    Abstract   PDF(1093KB) ( 1866 )  
    Hardware security has become more and more important in current information security architecture. Recently collected reports have shown that there may have been considerable hardware attacks prepared for possible military usage from all over the world. Due to the intrinsic difference from the software security, hardware security has some special features and challenges. In order to guarantee the hardware security, academia has proposed the concept of the trusted integrated circuits, which aims at a secure circulation of IC design, manufacture and chip using. This paper reviews the main problems of the trusted integrated circuits, and concludes the four key domains of the trusted IC namely the trusted IC design, trusted manufacture, trusted IP protection and trusted chip authentication. The main challenges in those domains are also analyzed based on the current known techniques. Finally, the main limitations of the current techniques and the possible future trends are discussed at the end of the paper.
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