Home / Journals / CSSE / Vol.33, No.2, 2018
  • Open Access

    ARTICLE

    Preface of Special Issue on BigDataSE 2016

    Heng Qi1,2, Keqiu Li1
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 57-59, 2018, DOI:10.32604/csse.2018.33.057
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    An Iteration-Based Differentially Private Social Network Data Release

    Tianqing Zhu1, Mengmeng Yang1, Ping Xiong2, Yang Xiang1, Wanlei Zhou1
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 61-69, 2018, DOI:10.32604/csse.2018.33.061
    Abstract Online social networks provide an unprecedented opportunity for researchers to analysis various social phenomena. These network data is normally represented as graphs, which contain many sensitive individual information. Publish these graph data will violate users’ privacy. Differential privacy is one of the most influential privacy models that provides a rigorous privacy guarantee for data release. However, existing works on graph data publishing cannot provide accurate results when releasing a large number of queries. In this paper, we propose a graph update method transferring the query release problem to an iteration process, in which a large set of queries are used… More >

  • Open Access

    ARTICLE

    The Optimization Reachability Query of Large Scale Multi-Attribute Constraints Directed Graph

    Kehong Zhang, Keqiu Li
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 71-85, 2018, DOI:10.32604/csse.2018.33.071
    Abstract Today, many applications such as social network and biological network develop rapidly,the graph data will be expanded constantly on a large scale. Some classic methods can not effectively solve this scale of the graph data. In the reachability query, many technologies such as N-Hop, tree, interval labels, uncertain graph processing are emerging, they also solve a lot of questions about reachability query of graph. But, these methods have not put forward the effective solution for the new issues of the multiattribute constraints reachability on directed graph. In this paper, TCRQDG algorithm effectively solves this new problem. Firstly it optimizes the… More >

  • Open Access

    ARTICLE

    Tensor-Based User Trajectory Mining

    Chen Yu, Qinmin Hong, Dezhong Yao, Hai Jin
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 87-94, 2018, DOI:10.32604/csse.2018.33.087
    Abstract The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching to get the corresponding road segments, and nally apply the… More >

  • Open Access

    ARTICLE

    Research on Tourist Routes Recommendation Based on the User Preference Drifting Over Time

    Chunjing Xiao1,∗, Yongwei Qiao2, Kewen Xia1, Yuxiang Zhang3
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 95-103, 2018, DOI:10.32604/csse.2018.33.095
    Abstract Tourist routes recommendation is a way to improve the tourist experience and the efficiency of tourism companies. Session-based methods divide all users’ interaction histories into the same number sessions with fixed time window and treat the user preference as time sequences. There have few or even no interaction in some sessions for some users because of the high sparsity and temporal characteristics of tourist data. That lead to many session-based methods can not be applied to routes recommendation due to aggravate the sparsity. In order to better adapt and apply the characteristics of tourism data and alleviate the sparsity, a… More >

  • Open Access

    ARTICLE

    Automated and Precise Event Detection Method for Big Data in Biomedical Imaging with Support Vector Machine

    Lufeng Yuan, Erlin Yao, Guangming Tan
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 105-113, 2018, DOI:10.32604/csse.2018.33.105
    Abstract This paper proposes a machine learning based method which can detect certain events automatically and precisely in biomedical imaging. We detect one important and not well-defined event, which is called flash, in fluorescence images of Escherichia coli. Given a time series of images, first we propose a scheme to transform the event detection on region of interest (ROI) in images to a classification problem. Then with supervised human labeling data, we develop a feature selection technique to utilize support vector machine (SVM) to solve this classification problem. To reduce the time in training SVM model, a parallel version of SVM… More >

  • Open Access

    ARTICLE

    Effective Piecewise Linear Skeletonization of Sparse Shapes

    Wenyu Qu1, Zhiyang Li2,*, Junfeng Wu2, Yinan Wu3, Zhaobin Liu2
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 115-123, 2018, DOI:10.32604/csse.2018.33.115
    Abstract Conventional image skeletonization techniques implicitly assume the pixel level connectivity. However, noise inside the object regions destroys the connectivity and exhibits sparseness in the image. We present a skeletonization algorithm designed for these kinds of sparse shapes. The skeletons are produced quickly by using three operations. First, initial skeleton nodes are selected by farthest point sampling with circles containing the maximum effective information. A skeleton graph of these nodes is imposed via inheriting the neighborhood of their associated pixels, followed by an edge collapse operation. Then a skeleton tting process based on feature-preserving Laplacian smoothing is applied. Finally, a re… More >

  • Open Access

    ARTICLE

    MapReduce Implementation of an Improved Xml Keyword Search Algorithm

    Yong Zhang1,2, Jing Cai1, Quanlin Li1
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 125-135, 2018, DOI:10.32604/csse.2018.33.125
    Abstract Extensible Markup Language (XML) is commonly employed to represent and transmit information over the Internet. Therefore, how to effectively search for keywords of massive XML data becomes a new issue. In this paper, we first present four properties to improve the classical ILE algorithm. Then, a kind of parallel XML keyword search algorithm, based on intelligent grouping to calculate SLCA, is proposed and realized under MapReduce programming model. At last, a series of experiments are implemented on 7 datasets of different sizes. The obtained results indicate that the proposed algorithm has high execution efficiency and is applicable to keyword search… More >

  • Open Access

    ARTICLE

    Human Movement Detection and Gait Periodicity Analysis via Channel State Information

    Wenyuan Liu1,2, Zijuan Liu1,*, Lin Wang1, Binbin Li1, Nan Jing1
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 137-147, 2018, DOI:10.32604/csse.2018.33.137
    Abstract In recent years, movement detection and gait recognition methods using different techniques emerge in an endless stream. On the one hand, wearable sensors need be worn by the detecting target and the method based on camera requires line of sight. On the other hand, radio frequency signals are easy to be impaired. In this paper, we propose a novel multi-layer filter of channel state information (CSI) to capture moving individuals in dynamic environments and analyze his/her gait periodicity. We design and evaluate an efficient CSI subcarrier feature difference to the multi-layer filtering method leveraging principal component analysis (PCA) and discrete… More >

  • Open Access

    ARTICLE

    A Dynamic Online Protection Framework for Android Applications

    Junfeng Xu, Linna Zhou
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 149-155, 2018, DOI:10.32604/csse.2018.33.149
    Abstract At present, Android is the most popular Operating System (OS) which is widespreadly installed on mobile phones, smart TVs and other wearable devices. Due to its overwhelming market share, Android attracts the attentions from many attackers. Reverse Engineering technology plays an important role in the field of Android security, such as cracking applications, malware analysis, software protection, etc. In order to prevent others from obtaining the real codes and tampering them, this paper designs and implements a online dynamic protection framework by deploying dynamic anti-debugging technology for Android application with comprehensive utilization of encryption, dynamic loading and shell technologies. Evaluated… More >

  • Open Access

    ARTICLE

    Online And Offline Scheduling Schemes to Maximize the Weighted Delivered Video Packets Towards Maritime Cpss

    Tingting Yang1, Hailong Feng1, Chengming Yang2, Ge Guo3, Tieshan Li1
    Computer Systems Science and Engineering, Vol.33, No.2, pp. 157-164, 2018, DOI:10.32604/csse.2018.33.157
    Abstract In this paper, the online and offline scheduling schemes towards maritime Cyber Physical Systems (CPSs), to transmit video packets generating from the interior of vessel. During the sailing from the origin port to destination port, the video packets could be delivered via the infostations shoreside. The video packets have their respective release times, deadlines, weights and processing time. The video packets only could be successfully transmitted before their deadlines. A mathematic job-machine problem is mapped. Facing distinguished challenges with unique characteristics imposed in maritime scenario, we focus on the heterogeneous networking and resource optimal scheduling technology to provide valuable insights… More >

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