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  • Find truth in the hands of the few: acquiring specific knowledge with crowdsourcing
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Tao Han, Hailong Sun, Yangqiu Song, Yili Fang, Xudong Liu

    Crowdsourcing has been a helpful mechanism to leverage human intelligence to acquire useful knowledge. However, when we aggregate the crowd knowledge based on the currently developed voting algorithms, it often results in common knowledge that may not be expected. In this paper, we consider the problem of collecting specific knowledge via crowdsourcing. With the help of using external knowledge base

    更新日期:2020-10-02
  • A proactive secret sharing scheme based on Chinese remainder theorem
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Keju Meng, Fuyou Miao, Yu Ning, Wenchao Huang, Yan Xiong, Chin-Chen Chang

    If an adversary tries to obtain a secret s in a (t, n) threshold secret sharing (SS) scheme, it has to capture no less than t shares instead of the secret s directly. However, if a shareholder keeps a fixed share for a long time, an adversary may have chances to filch some shareholders’ shares. In a proactive secret sharing (PSS) scheme, shareholders are supposed to refresh shares at fixed period without

    更新日期:2020-10-02
  • DFD-Net: lung cancer detection from denoised CT scan image using deep learning
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Worku J. Sori, Jiang Feng, Arero W. Godana, Shaohui Liu, Demissie J. Gelmecha

    The availability of pulmonary nodules in CT scan image of lung does not completely specify cancer. The noise in an image and morphology of nodules, like shape and size has an implicit and complex association with cancer, and thus, a careful analysis should be mandatory on every suspected nodules and the combination of information of every nodule. In this paper, we introduce a “denoising first” two-path

    更新日期:2020-10-02
  • Predicting protein subchloroplast locations: the 10th anniversary
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Jian Sun, Pu-Feng Du

    Chloroplast is a type of subcellular organelle in green plants and algae. It is the main subcellular organelle for conducting photosynthetic process. The proteins, which localize within the chloroplast, are responsible for the photosynthetic process at molecular level. The chloroplast can be further divided into several compartments. Proteins in different compartments are related to different steps

    更新日期:2020-10-02
  • On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Nilesh Chakraborty, Samrat Mondal

    Unaided authentication services provide the flexibility to login without being dependent on any additional device. The power of recording attack resilient unaided authentication services (RARUAS) is undeniable as, in some aspects, they are even capable of offering better security than the biometric based authentication systems. However, high login complexity of these RARUAS makes them far from usable

    更新日期:2020-10-02
  • Ethereum smart contract security research: survey and future research opportunities
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-10-02
    Zeli Wang, Hai Jin, Weiqi Dai, Kim-Kwang Raymond Choo, Deqing Zou

    Blockchain has recently emerged as a research trend, with potential applications in a broad range of industries and context. One particular successful Blockchain technology is smart contract, which is widely used in commercial settings (e.g., high value financial transactions). This, however, has security implications due to the potential to financially benefit from a security incident (e.g., identification

    更新日期:2020-10-02
  • Evaluating the usage of fault localization in automated program repair: an empirical study
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Deheng Yang, Yuhua Qi, Xiaoguang Mao, Yan Lei

    Fault localization techniques are originally proposed to assist in manual debugging by generally producing a rank list of suspicious locations. With the increasing popularity of automated program repair, the fault localization techniques have been introduced to effectively reduce the search space of automated program repair. Unlike developers who mainly focus on the rank information, current automated

    更新日期:2020-09-29
  • Mathematical model and simulated annealing algorithm for Chinese high school timetabling problems under the new curriculum innovation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Xingxing Hao, Jing Liu, Yutong Zhang, Gustaph Sanga

    As the first attempt, this paper proposes a model for the Chinese high school timetabling problems (CHSTPs) under the new curriculum innovation which was launched in 2014 by the Chinese government. According to the new curriculum innovation, students in high school can choose subjects that they are interested in instead of being forced to select one of the two study directions, namely, Science and

    更新日期:2020-09-29
  • A survey of density based clustering algorithms
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Panthadeep Bhattacharjee, Pinaki Mitra

    Density based clustering algorithms (DBCLAs) rely on the notion of density to identify clusters of arbitrary shapes, sizes with varying densities. Existing surveys on DBCLAs cover only a selected set of algorithms. These surveys fail to provide an extensive information about a variety of DBCLAs proposed till date including a taxonomy of the algorithms. In this paper we present a comprehensive survey

    更新日期:2020-09-29
  • Determining node duty cycle using Q-learning and linear regression for WSN
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Han Yao Huang, Kyung Tae Kim, Hee Yong Youn

    Wireless sensor network (WSN) is effective for monitoring the target environment, which consists of a large number of sensor nodes of limited energy. An efficient medium access control (MAC) protocol is thus imperative to maximize the energy efficiency and performance of WSN. The most existing MAC protocols are based on the scheduling of sleep and active period of the nodes, and do not consider the

    更新日期:2020-09-29
  • Entity set expansion in knowledge graph: a heterogeneous information network perspective
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Chuan Shi, Jiayu Ding, Xiaohuan Cao, Linmei Hu, Bin Wu, Xiaoli Li

    Entity set expansion (ESE) aims to expand an entity seed set to obtain more entities which have common properties. ESE is important for many applications such as dictionary construction and query suggestion. Traditional ESE methods relied heavily on the text and Web information of entities. Recently, some ESE methods employed knowledge graphs (KGs) to extend entities. However, they failed to effectively

    更新日期:2020-09-29
  • A framework based on sparse representation model for time series prediction in smart city
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Zhiyong Yu, Xiangping Zheng, Fangwan Huang, Wenzhong Guo, Lin Sun, Zhiwen Yu

    Smart city driven by Big Data and Internet of Things (IoT) has become a most promising trend of the future. As one important function of smart city, event alert based on time series prediction is faced with the challenge of how to extract and represent discriminative features of sensing knowledge from the massive sequential data generated by IoT devices. In this paper, a framework based on sparse representation

    更新日期:2020-09-29
  • Fingerprint matching, spoof and liveness detection: classification and literature review
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Syed Farooq Ali, Muhammad Aamir Khan, Ahmed Sohail Aslam

    Fingerprint matching, spoof mitigation and liveness detection are the trendiest biometric techniques, mostly because of their stability through life, uniqueness and their least risk of invasion. In recent decade, several techniques are presented to address these challenges over well-known data-sets. This study provides a comprehensive review on the fingerprint algorithms and techniques which have been

    更新日期:2020-09-29
  • Biologically inspired visual computing: the state of the art
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Wangli Hao, Ian Max Andolina, Wei Wang, Zhaoxiang Zhang

    Visual information is highly advantageous for the evolutionary success of almost all animals. This information is likewise critical for many computing tasks, and visual computing has achieved tremendous successes in numerous applications over the last 60 years or so. In that time, the development of visual computing has moved forwards with inspiration from biological mechanisms many times. In particular

    更新日期:2020-09-29
  • Where to go? Predicting next location in IoT environment
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Hao Lin, Guannan Liu, Fengzhi Li, Yuan Zuo

    Next location prediction has aroused great interests in the era of internet of things (IoT). With the ubiquitous deployment of sensor devices, e.g., GPS and Wi-Fi, IoT environment offers new opportunities for proactively analyzing human mobility patterns and predicting user’s future visit in low cost, no matter outdoor and indoor. In this paper, we consider the problem of next location prediction in

    更新日期:2020-09-29
  • Proactive planning of bandwidth resource using simulation-based what-if predictions for Web services in the cloud
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Jianpeng Hu, Linpeng Huang, Tianqi Sun, Ying Fan, Wenqiang Hu, Hao Zhong

    Resource planning is becoming an increasingly important and timely problem for cloud users. As more Web services are moved to the cloud, minimizing network usage is often a key driver of cost control. Most existing approaches focus on resources such as CPU, memory, and disk I/O. In particular, CPU receives the most attention from researchers, but the bandwidth is somehow neglected. It is challenging

    更新日期:2020-09-29
  • Adversarial network embedding using structural similarity
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Zihan Zhou, Yu Gu, Ge Yu

    Network embedding which aims to embed a given network into a low-dimensional vector space has been proved effective in various network analysis and mining tasks such as node classification, link prediction and network visualization. The emerging network embedding methods have shifted of emphasis in utilizing mature deep learning models. The neural-network based network embedding has become a mainstream

    更新日期:2020-09-29
  • Information retrieval: a view from the Chinese IR community
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Zhumin Chen, Xueqi Cheng, Shoubin Dong, Zhicheng Dou, Jiafeng Guo, Xuanjing Huang, Yanyan Lan, Chenliang Li, Ru Li, Tie-Yan Liu, Yiqun Liu, Jun Ma, Bing Qin, Mingwen Wang, Jirong Wen, Jun Xu, Min Zhang, Peng Zhang, Qi Zhang

    During a two-day strategic workshop in February 2018, 22 information retrieval researchers met to discuss the future challenges and opportunities within the field. The outcome is a list of potential research directions, project ideas, and challenges. This report describes the major conclusions we have obtained during the workshop. A key result is that we need to open our mind to embrace a broader IR

    更新日期:2020-09-29
  • k -dominant Skyline query algorithm for dynamic datasets
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-09-29
    Zhiyun Zheng, Ke Ruan, Mengyao Yu, Xingjin Zhang, Ning Wang, Dun Li

    At present, most k-dominant Skyline query algorithms are oriented to static datasets, this paper proposes a k-dominant Skyline query algorithm for dynamic datasets. The algorithm is recursive circularly. First, we compute the dominant ability of each object and sort objects in descending order by dominant ability. Then, we maintain an inverted index of the dominant index by k-dominant Skyline point

    更新日期:2020-09-29
  • Pointwise manifold regularization for semi-supervised learning
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-08-13
    Yunyun Wang; Jiao Han; Yating Shen; Hui Xue

    Manifold regularization (MR) provides a powerful framework for semi-supervised classification using both the labeled and unlabeled data. It constrains that similar instances over the manifold graph should share similar classification outputs according to the manifold assumption. It is easily noted that MR is built on the pairwise smoothness over the manifold graph, i.e., the smoothness constraint is

    更新日期:2020-08-13
  • Improving neural sentence alignment with word translation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-08-13
    Ying Ding; Junhui Li; Zhengxian Gong; Guodong Zhou

    Sentence alignment is a basic task in natural language processing which aims to extract high-quality parallel sentences automatically. Motivated by the observation that aligned sentence pairs contain a larger number of aligned words than unaligned ones, we treat word translation as one of the most useful external knowledge. In this paper, we show how to explicitly integrate word translation into neural

    更新日期:2020-08-13
  • SSDBA: the stretch shrink distance based algorithm for link prediction in social networks
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-08-13
    Ruidong Yan; Yi Li; Deying Li; Weili Wu; Yongcai Wang

    In the field of social network analysis, Link Prediction is one of the hottest topics which has been attracted attentions in academia and industry. So far, literatures for solving link prediction can be roughly divided into two categories: similarity-based and learning-based methods. The learning-based methods have higher accuracy, but their time complexities are too high for complex networks. However

    更新日期:2020-08-13
  • 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:2020-07-11
  • 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:2020-07-11
  • 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:2020-07-11
  • 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:2020-07-11
  • 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:2020-07-11
  • 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:2020-07-11
  • 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:2020-04-19
  • 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:2020-04-19
  • 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:2020-04-19
  • 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:2020-03-16
  • 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:2020-03-16
  • 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:2020-03-16
  • 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:2020-03-13
  • 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:2020-03-13
  • Probabilistic robust regression with adaptive weights — a case study on face recognition
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-20
    Jin Li; Quan Chen; Jingwen Leng; Weinan Zhang; Minyi Guo

    Robust regression plays an important role in many machine learning problems. A primal approach relies on the use of Huber loss and an iteratively reweighted ℓ2 method. However, because the Huber loss is not smooth and its corresponding distribution cannot be represented as a Gaussian scale mixture, such an approach is extremely difficult to handle using a probabilistic framework. To address those limitations

    更新日期:2020-01-20
  • Multi-task MIML learning for pre-course student performance prediction
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-20
    Yuling Ma; Chaoran Cui; Jun Yu; Jie Guo; Gongping Yang; Yilong Yin

    In higher education, the initial studying period of each course plays a crucial role for students, and seriously influences the subsequent learning activities. However, given the large size of a course’s students at universities, it has become impossible for teachers to keep track of the performance of individual students. In this circumstance, an academic early warning system is desirable, which automatically

    更新日期:2020-01-20
  • Improving students’ programming quality with the continuous inspection process: a social coding perspective
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-20
    Yao Lu; Xinjun Mao; Tao Wang; Gang Yin; Zude Li

    College students majoring in computer science and software engineering need to master skills for high-quality programming. However, rich research has shown that both the teaching and learning of high-quality programming are challenging and deficient in most college education systems. Recently, the continuous inspection paradigm has been widely used by developers on social coding sites (e.g., GitHub)

    更新日期:2020-01-20
  • Practical continuous leakage-resilient CCA secure identity-based encryption
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Yanwei Zhou; Bo Yang

    Leakage of private information including private keys of user has become a threat to the security of computing systems. It has become a common security requirement that a cryptographic scheme should withstand various leakage attacks. In the real life, an adversary can break the security of cryptography primitive by performing continuous leakage attacks. Although, some research on the leakage-resilient

    更新日期:2020-01-03
  • Advance on large scale near-duplicate video retrieval
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Ling Shen; Richang Hong; Yanbin Hao

    Emerging Internet services and applications attract increasing users to involve in diverse video-related activities, such as video searching, video downloading, video sharing and so on. As normal operations, they lead to an explosive growth of online video volume, and inevitably give rise to the massive near-duplicate contents. Near-duplicate video retrieval (NDVR) has always been a hot topic. The

    更新日期:2020-01-03
  • Adam revisited: a weighted past gradients perspective
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Hui Zhong; Zaiyi Chen; Chuan Qin; Zai Huang; Vincent W. Zheng; Tong Xu; Enhong Chen

    Adaptive learning rate methods have been successfully applied in many fields, especially in training deep neural networks. Recent results have shown that adaptive methods with exponential increasing weights on squared past gradients (i.e., ADAM, RMSPROP) may fail to converge to the optimal solution. Though many algorithms, such as AMSGRAD and ADAMNC, have been proposed to fix the non-convergence issues

    更新日期:2020-01-03
  • Plover: parallel logging for replication systems
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Huan Zhou; Jinwei Guo; Huiqi Hu; Weining Qian; Xuan Zhou; Aoying Zhou

    Logging and replication are commonly used recovery approaches in database systems. To guarantee that the database state is not corrupted due to system crash, database systems rely on a centralized logging method to persist log entries into a stable storage device; to prevent data loss due to device failure, a primary server in the database system periodically replicates its state to backup servers

    更新日期:2020-01-03
  • A survey of current trends in computational predictions of protein-protein interactions
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Yanbin Wang; Zhuhong You; Liping Li; Zhanheng Chen

    Proteomics become an important research area of interests in life science after the completion of the human genome project. This scientific is to study the characteristics of proteins at the large-scale data level, and then gain a holistic and comprehensive understanding of the process of disease occurrence and cell metabolism at the protein level. A key issue in proteomics is how to efficiently analyze

    更新日期:2020-01-03
  • A novel classifier for multivariate instance using graph class signatures
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Parnika Paranjape; Meera Dhabu; Parag Deshpande

    Applications like identifying different customers from their unique buying behaviours, determining ratings of a product given by users based on different sets of features, etc. require classification using class-specific subsets of features. Most of the existing state-of-the-art classifiers for multivariate data use complete feature set for classification regardless of the different class labels. Decision

    更新日期:2020-01-03
  • A framework for cloned vehicle detection
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Minxi Li; Jiali Mao; Xiaodong Qi; Cheqing Jin

    Rampant cloned vehicle offenses have caused great damage to transportation management as well as public safety and even the world economy. It necessitates an efficient detection mechanism to identify the vehicles with fake license plates accurately, and further explore the motives through discerning the behaviors of cloned vehicles. The ubiquitous inspection spots that deployed in the city have been

    更新日期:2020-01-03
  • Entity-related paths modeling for knowledge base completion
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Fangfang Liu; Yan Shen; Tienan Zhang; Honghao Gao

    Knowledge bases (KBs) are far from complete, necessitating a demand for KB completion. Among various methods, embedding has received increasing attention in recent years. PTransE, an important approach using embedding method in KB completion, considers multiple-step relation paths based on TransE, but ignores the association between entity and their related entities with the same direct relationships

    更新日期:2020-01-03
  • Diversification on big data in query processing
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Meifan Zhang; Hongzhi Wang; Jianzhong Li; Hong Gao

    Recently, in the area of big data, some popular applications such as web search engines and recommendation systems, face the problem to diversify results during query processing. In this sense, it is both significant and essential to propose methods to deal with big data in order to increase the diversity of the result set. In this paper, we firstly define the diversity of a set and the ability of

    更新日期:2020-01-03
  • EMSC: a joint multicast routing, scheduling, and call admission control in multi-radio multi-channel WMNs
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Zeinab Askari; Avid Avokh

    This paper deals with the problem of joint multicast routing, scheduling, and call admission control in multiradio multi-channel wireless mesh networks. To heuristically solve this problem, we propose a cross-layer algorithm named “extended MIMCR with scheduling and call admission control phases (EMSC)”. Our model relies on the on-demand quality of service (QoS) multicast sessions, where each admitted

    更新日期:2020-01-03
  • Extracting a justification for OWL ontologies by critical axioms
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Yuxin Ye; Xianji Cui; Dantong Ouyang

    Extracting justifications for web ontology language (OWL) ontologies is an important mission in ontology engineering. In this paper, we focus on black-box techniques which are based on ontology reasoners. Through creating a recursive expansion procedure, all elements which are called critical axioms in the justification are explored one by one. In this detection procedure, an axiom selection function

    更新日期:2020-01-03
  • Adaptive sparse and dense hybrid representation with nonconvex optimization
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Xuejun Wang; Feilong Cao; Wenjian Wang

    Sparse representation has been widely used in signal processing, pattern recognition and computer vision etc. Excellent achievements have been made in both theoretical researches and practical applications. However, there are two limitations on the application of classification. One is that sufficient training samples are required for each class, and the other is that samples should be uncorrupted

    更新日期:2020-01-03
  • Efficient FPGA-based graph processing with hybrid pull-push computational model
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Chengbo Yang; Long Zheng; Chuangyi Gui; Hai Jin

    Hybrid pull-push computational model can provide compelling results over either of single one for processing real-world graphs. Programmability and pipeline parallelism of FPGAs make it potential to process different stages of graph iterations. Nevertheless, considering the limited on-chip resources and streamline pipeline computation, the efficiency of hybrid model on FPGAs often suffers due to well-known

    更新日期:2020-01-03
  • An efficient multipath routing schema in multi-homing scenario based on protocol-oblivious forwarding
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Pufang Ma; Jiali You; Jinlin Wang

    With the advent of 5G, multi-homing will be an increasingly common scenario, which is expected to increase transmission rates, improve transmission reliability, and reduce costs for users. However, the current routing methods are unable to fully utilize the resources of networks to achieve high-performance data transmission for multi-homed devices. In the current routing mechanism, there is only one

    更新日期:2020-01-03
  • Multi-task regression learning for survival analysis via prior information guided transductive matrix completion
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Lei Chen; Kai Shao; Xianzhong Long; Lingsheng Wang

    Survival analysis aims to predict the occurrence time of a particular event of interest, which is crucial for the prognosis analysis of diseases. Currently, due to the limited study period and potential losing tracks, the observed data inevitably involve some censored instances, and thus brings a unique challenge that distinguishes from the general regression problems. In addition, survival analysis

    更新日期:2020-01-03
  • An adaptive strategy for statistics collecting in distributed database
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Jintao Gao; Wenjie Liu; Zhanhuai Li

    Collecting statistics is a time- and resource-consuming operation in database systems. It is even more challenging to efficiently collect statistics without affecting system performance, meanwhile keeping correctness in distributed database. Traditional strategies usually consider one dimension during collecting statistics, which is lack of adaptiveness. In this paper, we propose an adaptive strategy

    更新日期:2020-01-03
  • Multipath affinage stacked—hourglass networks for human pose estimation
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Guoguang Hua; Lihong Li; Shiguang Liu

    Recently, stacked hourglass network has shown outstanding performance in human pose estimation. However, repeated bottom-up and top-down stride convolution operations in deep convolutional neural networks lead to a significant decrease in the initial image resolution. In order to address this problem, we propose to incorporate affinage module and residual attention module into stacked hourglass network

    更新日期:2020-01-03
  • Zero-pole cancellation for identity-based aggregators: a constant-size designated verifier-set signature
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    E. Chen; Yan Zhu; Changlu Lin; Kewei Lv

    In this paper we present a designated verifier-set signature (DVSS), in which the signer allows to designate many verifiers rather than one verifier, and each designated verifier can verify the validity of signature by himself. Our research starts from identity-based aggregator (IBA) that compresses a designated set of verifier’s identities to a constant-size random string in cryptographic space. The

    更新日期:2020-01-03
  • Benchmarking on intensive transaction processing
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Chunxi Zhang; Yuming Li; Rong Zhang; Weining Qian; Aoying Zhou

    Benchmarks play a crucial role in database performance evaluation, and have been effectively promoting the development of database management systems. With critical transaction processing requirements of new applications, we see an explosion of innovative database technologies for dealing with highly intensive transaction workloads (OLTP) with the obvious characteristics of sharp dynamics, terrificskewness

    更新日期:2020-01-03
  • A revisit to MacKay algorithm and its application to deep network compression
    Front. Comput. Sci. (IF 1.275) Pub Date : 2020-01-03
    Chune Li; Yongyi Mao; Richong Zhang; Jinpeng Huai

    An iterative procedure introduced in MacKay’s evidence framework is often used for estimating the hyperparameter in empirical Bayes. Together with the use of a particular form of prior, the estimation of the hyperparameter reduces to an automatic relevance determination model, which provides a soft way of pruning model parameters. Despite the effectiveness of this estimation procedure, it has stayed

    更新日期:2020-01-03
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