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  • A post-processing method for true random number generators based on hyperchaos with applications in audio-based generators
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Je Sen Teh, Weijian Teng, Azman Samsudin, Jiageng Chen

    True random number generators (TRNG) are important counterparts to pseudorandom number generators (PRNG), especially for high security applications such as cryptography. They produce unpredictable, non-repeatable random sequences. However, most TRNGs require specialized hardware to extract entropy from physical phenomena and tend to be slower than PRNGs. These generators usually require post-processing

    更新日期:2020-07-13
  • Text-enhanced network representation learning
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Yu Zhu, Zhonglin Ye, Haixing Zhao, Ke Zhang

    Network representation learning called NRL for short aims at embedding various networks into low-dimensional continuous distributed vector spaces. Most existing representation learning methods focus on learning representations purely based on the network topology, i.e., the linkage relationships between network nodes, but the nodes in lots of networks may contain rich text features, which are beneficial

    更新日期:2020-07-13
  • PopFlow: a novel flow management scheme for SDN switch of multiple flow tables based on flow popularity
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Cheng Wang, Kyung Tae Kim, Hee Yong Youn

    Pipeline processing is applied to multiple flow tables (MFT) in the switch of software-defined network (SDN) to increase the throughput of the flows. However, the processing time of each flow increases as the size or number of flow tables gets larger. In this paper we propose a novel approach called PopFlow where a table keeping popular flow entries is located up front in the pipeline, and an express

    更新日期:2020-07-13
  • Properties of the satisfiability threshold of the strictly d -regular random (3,2 s )-SAT problem
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Yongping Wang, Daoyun Xu

    A k-CNF (conjunctive normal form) formula is a regular (k, s)-CNF one if every variable occurs s times in the formula, where k ⩾ 2 and s > 0 are integers. Regular (3, s)-CNF formulas have some good structural properties, so carrying out a probability analysis of the structure for random formulas of this type is easier than conducting such an analysis for random 3-CNF formulas. Some subclasses of the

    更新日期:2020-07-13
  • Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Qianchen Yu, Zhiwen Yu, Zhu Wang, Xiaofeng Wang, Yongzhi Wang

    Overlapping community detection has become a very hot research topic in recent decades, and a plethora of methods have been proposed. But, a common challenge in many existing overlapping community detection approaches is that the number of communities K must be predefined manually. We propose a flexible nonparametric Bayesian generative model for count-value networks, which can allow K to increase

    更新日期:2020-07-13
  • A computer aided design method for car form and its application based on shape parameters
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-07-11
    Fan Liu, Xiaomin Ji, Gang Hu, Jing Gao

    In the early design stage, automotive modeling should both meet the requirements of aesthetics and engineering. Therefore, a vehicle CAD (computer aided design) model that can be easily adjusted by feedbacks is necessary. Based on CE-Bézier surface, this paper presents a set of algorithms for parametric segmentation and fairing surface generation in a car model. This model is defined by a simplified

    更新日期:2020-07-13
  • PSO-ACSC: a large-scale evolutionary algorithm for image matting
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-05-06
    Yihui Liang, Han Huang, Zhaoquan Cai

    Image matting is an essential image processing technology due to its wide range of applications. Sampling-based image matting is one of the main branches of image matting research that estimates alpha mattes by selecting the best pixel pairs. It is essentially a large-scale multi-peak optimization problem of pixel pairs. Previous study shows that particle swarm optimization (PSO) can effectively optimize

    更新日期:2020-05-06
  • Matching user identities across social networks with limited profile data
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-04-19
    Ildar Nurgaliev, Qiang Qu, Seyed Mojtaba Hosseini Bamakan, Muhammad Muzammal

    Privacy preservation is a primary concern in social networks which employ a variety of privacy preservations mechanisms to preserve and protect sensitive user information including age, location, education, interests, and others. The task of matching user identities across different social networks is considered a challenging task. In this work, we propose an algorithm to reveal user identities as

    更新日期:2020-04-20
  • A behavior-aware SLA-based framework for guaranteeing the security conformance of cloud service
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-04-19
    Xiaochen Liu, Chunhe Xia, Tianbo Wang, Li Zhong, Xiaojian Li

    As cloud computing technology turning to mature, cloud services have become a trust-based service. Users’ distrust of the security and performance of cloud services will hinder the rapid deployment and development of cloud services. So cloud service providers (CSPs) urgently need a way to prove that the infrastructure and the behavior of cloud services they provided can be trusted. The challenge here

    更新日期:2020-04-20
  • Guaranteeing the response deadline for general aggregation trees
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-04-19
    Jiangfan Li, Chendie Yao, Junxu Xia, Deke Guo

    It is essential to provide responses to queries within time deadlines, even if not exact and complete. To reduce the query latency, systems usually partition large-scale data computations as a series of tasks over many processes and aggregate them to reduce the response time by using aggregation trees. An obstacle is that the involved processes of a query usually differ in their speeds, thus not all

    更新日期:2020-04-20
  • Meta-path-based outlier detection in heterogeneous information network
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Lu Liu, Shang Wang

    Mining outliers in heterogeneous networks is crucial to many applications, but challenges abound. In this paper, we focus on identifying meta-path-based outliers in heterogeneous information network (HIN), and calculate the similarity between different types of objects. We propose a meta-path-based outlier detection method (MPOutliers) in heterogeneous information network to deal with problems in one

    更新日期:2020-04-18
  • A unified latent variable model for contrastive opinion mining
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Ebuka Ibeke, Chenghua Lin, Adam Wyner, Mohamad Hardyman Barawi

    There are large and growing textual corpora in which people express contrastive opinions about the same topic. This has led to an increasing number of studies about contrastive opinion mining. However, there are several notable issues with the existing studies. They mostly focus on mining contrastive opinions from multiple data collections, which need to be separated into their respective collections

    更新日期:2020-04-18
  • Graph-ranking collective Chinese entity linking algorithm
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Tao Xie, Bin Wu, Bingjing Jia, Bai Wang

    Entity linking (EL) systems aim to link entity mentions in the document to their corresponding entity records in a reference knowledge base. Existing EL approaches usually ignore the semantic correlation between the mentions in the text, and are limited to the scale of the local knowledge base. In this paper, we propose a novel graphranking collective Chinese entity linking (GRCCEL) algorithm, which

    更新日期:2020-04-18
  • A survey on ensemble learning
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Xibin Dong, Zhiwen Yu, Wenming Cao, Yifan Shi, Qianli Ma

    Despite significant successes achieved in knowledge discovery, traditional machine learning methods may fail to obtain satisfactory performances when dealing with complex data, such as imbalanced, high-dimensional, noisy data, etc. The reason behind is that it is difficult for these methods to capture multiple characteristics and underlying structure of data. In this context, it becomes an important

    更新日期:2020-04-18
  • Real-time visual tracking using complementary kernel support correlation filters
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Zhenyang Su, Jing Li, Jun Chang, Bo Du, Yafu Xiao

    Despite demonstrated success of SVM based trackers, their performance remains a boosting room if carefully considering the following factors: first, the tradeoff between sampling and budgeting samples affects tracking accuracy and efficiency much; second, how to effectively fuse different types of features to learn a robust target representation plays a key role in tracking accuracy. In this paper

    更新日期:2020-04-18
  • A survey of autoencoder-based recommender systems
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Guijuan Zhang, Yang Liu, Xiaoning Jin

    In the past decade, recommender systems have been widely used to provide users with personalized products and services. However, most traditional recommender systems are still facing a challenge in dealing with the huge volume, complexity, and dynamics of information. To tackle this challenge, many studies have been conducted to improve recommender system by integrating deep learning techniques. As

    更新日期:2020-04-18
  • NEXT: a neural network framework for next POI recommendation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Zhiqian Zhang, Chenliang Li, Zhiyong Wu, Aixin Sun, Dengpan Ye, Xiangyang Luo

    The task of next POI recommendations has been studied extensively in recent years. However, developing a unified recommendation framework to incorporate multiple factors associated with both POIs and users remains challenging, because of the heterogeneity nature of these information. Further, effective mechanisms to smoothly handle cold-start cases are also a difficult topic. Inspired by the recent

    更新日期:2020-04-18
  • Sichuan dialect speech recognition with deep LSTM network
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Wangyang Ying, Lei Zhang, Hongli Deng

    In speech recognition research, because of the variety of languages, corresponding speech recognition systems need to be constructed for different languages. Especially in a dialect speech recognition system, there are many special words and oral language features. In addition, dialect speech data is very scarce. Therefore, constructing a dialect speech recognition system is difficult. This paper constructs

    更新日期:2020-04-18
  • iRNA-PseTNC: identification of RNA 5-methylcytosine sites using hybrid vector space of pseudo nucleotide composition
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Shahid Akbar, Maqsood Hayat, Muhammad Iqbal, Muhammad Tahir

    RNA 5-methylcytosine (m5C) sites perform a major role in numerous biological processes and commonly reported in both DNA and RNA cellular. The enzymatic mechanism and biological functions of m5C sites in DNA remain the focusing area of researchers for last few decades. Likewise, the investigators also targeted m5C sites in RNA due to its cellular functions, positioning and formation mechanism. Currently

    更新日期:2020-04-18
  • Abnormal event detection via the analysis of multi-frame optical flow information
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Tian Wang, Meina Qiao, Aichun Zhu, Guangcun Shan, Hichem Snoussi

    Security surveillance of public scene is closely relevant to routine safety of individual. Under the stimulus of this concern, abnormal event detection is becoming one of the most important tasks in computer vision and video processing. In this paper, we propose a new algorithm to address the visual abnormal detection problem. Our algorithm decouples the problem into a feature descriptor extraction

    更新日期:2020-04-18
  • Leveraging proficiency and preference for online Karaoke recommendation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Ming He, Hao Guo, Guangyi Lv, Le Wu, Yong Ge, Enhong Chen, Haiping Ma

    Recently, many online Karaoke (KTV) platforms have been released, where music lovers sing songs on these platforms. In the meantime, the system automatically evaluates user proficiency according to their singing behavior. Recommending approximate songs to users can initialize singers’ participation and improve users’ loyalty to these platforms. However, this is not an easy task due to the unique characteristics

    更新日期:2020-04-18
  • Optimized high order product quantization for approximate nearest neighbors search
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Linhao Li, Qinghua Hu

    Product quantization is now considered as an effective approach to solve the approximate nearest neighbor (ANN) search. A collection of derivative algorithms have been developed. However, the current techniques ignore the intrinsic high order structures of data, which usually contain helpful information for improving the computational precision. In this paper, aiming at the complex structure of high

    更新日期:2020-04-18
  • Real-time manifold regularized context-aware correlation tracking
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Jiaqing Fan, Huihui Song, Kaihua Zhang, Qingshan Liu, Fei Yan, Wei Lian

    Despite the demonstrated success of numerous correlation filter (CF) based tracking approaches, their assumption of circulant structure of samples introduces significant redundancy to learn an effective classifier. In this paper, we develop a fast manifold regularized context-aware correlation tracking algorithm that mines the local manifold structure information of different types of samples. First

    更新日期:2020-04-18
  • Enjoy the most beautiful scene now: a memetic algorithm to solve two-fold time-dependent arc orienteering problem
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Chao Chen, Liping Gao, Xuefeng Xie, Zhu Wang

    Traditional route planners commonly focus on finding the shortest path between two points in terms of travel distance or time over road networks. However, in real cases, especially in the era of smart cities where many kinds of transportation-related data become easily available, recent years have witnessed an increasing demand of route planners that need to optimize for multiple criteria, e.g., finding

    更新日期:2020-04-18
  • A primal perspective for indefinite kernel SVM problem
    Front. Comput. Sci. (IF 1.275) Pub Date : 2019-08-30
    Hui Xue, Haiming Xu, Xiaohong Chen, Yunyun Wang

    Indefinite kernel support vector machine (IKSVM) has recently attracted increasing attentions in machine learning. Since IKSVM essentially is a non-convex problem, existing algorithms either change the spectrum of indefinite kernel directly but risking losing some valuable information or solve the dual form of IKSVM whereas suffering from a dual gap problem. In this paper, we propose a primal perspective

    更新日期:2020-04-18
  • Solving quantified constraint satisfaction problems with value selection rules
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-03-16
    Jian Gao, Jinyan Wang, Kuixian Wu, Rong Chen

    Solving a quantified constraint satisfaction problem (QCSP) is usually a hard task due to its computational complexity. Exact algorithms play an important role in solving this problem, among which backtrack algorithms are effective. In a backtrack algorithm, an important step is assigning a variable by a chosen value when exploiting a branch, and thus a good value selection rule may speed up greatly

    更新日期:2020-04-18
  • Event detection and evolution in multi-lingual social streams
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-03-16
    Yaopeng Liu, Hao Peng, Jianxin Li, Yangqiu Song, Xiong Li

    Real-life events are emerging and evolving in social and news streams. Recent methods have succeeded in capturing designed features of monolingual events, but lack of interpretability and multi-lingual considerations. To this end, we propose a multi-lingual event mining model, namely MLEM, to automatically detect events and generate evolution graph in multilingual hybrid-length text streams including

    更新日期:2020-04-18
  • An efficient GPU-based parallel tabu search algorithm for hardware/software co-design
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-03-16
    Neng Hou, Fazhi He, Yi Zhou, Yilin Chen

    Hardware/software partitioning is an essential step in hardware/software co-design. For large size problems, it is difficult to consider both solution quality and time. This paper presents an efficient GPU-based parallel tabu search algorithm (GPTS) for HW/SW partitioning. A single GPU kernel of compacting neighborhood is proposed to reduce the amount of GPU global memory accesses theoretically. A

    更新日期:2020-04-18
  • Secure outsourcing of large matrix determinant computation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-03-13
    Jiayang Liu, Jingguo Bi, Mu Li

    Cloud computing provides the capability to connect resource-constrained clients with a centralized and shared pool of resources, such as computational power and storage on demand. Large matrix determinant computation is almost ubiquitous in computer science and requires large-scale data computation. Currently, techniques for securely outsourcing matrix determinant computations to untrusted servers

    更新日期:2020-04-18
  • Quality assessment in competition-based software crowdsourcing
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-03-13
    Zhenghui Hu, Wenjun Wu, Jie Luo, Xin Wang, Boshu Li

    Quality assessment is a critical component in crowdsourcing-based software engineering (CBSE) as software products are developed by the crowd with unknown or varied skills and motivations. In this paper, we propose a novel metric called the project score to measure the performance of projects and the quality of products for competition-based software crowdsourcing development (CBSCD) activities. To

    更新日期:2020-04-18
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