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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Wei Li Sixin Liang Ang Bian Guodong Du College of Computer Science Sichuan University Chengdu China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao P.R. China

Video person re-identification is receiving academic interest. However, the practical application of the algorithm is hardly supported because of prohibitive annotated data. Hence, the study for unlabeled data will lead to an attractive alternative. This work explores an innovative strategy, namely, learning to cluster unlabeled person in the video through graph convolutional networks. In this paper, we find that the possibility of inter-frame linkage can be inferred from context. Therefore, a pose-guided topology linkage clustering framework is proposed. Our framework consists of three modules: (i) a pose-guided representation module; (ii) a pose-guided embedding module; (iii) a link prediction module. Firstly, the representation coding alone is performed at the level of relational induction bias, embedding the implicit pose structure information in image features. Then, based on the consideration of the topology relationship between adjacent and cross-frame, graph convolutional network is introduced to infer the likelihood of linkage between frame nodes. Experiments show that the method demonstrates excellent scalability in addition to being an effective response to person clustering in case of changes, and does not need the number of clusters as a prior.

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An improved algorithm for detecting community structure based on node similarity

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Journal of Computational Information systems 2014年第9期10卷 3805-3813页

作者： Guo, Jingfeng Wei, Aiying Lv, Jiaguo Liu, Zhen College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China College of Information Science and Engineering Zaozhuang University Zaozhuang 277100 China

Detecting community structure based on node similarity cost lower time complexity, but they ignore the indirect relationships of nodes. We proposed an improved algorithm for detecting community structure based on node similarity (AINS). The algorithm presents a neighbor subgraph model based on akincore node pair, considering the direct and indirect relations between nodes. It introduced node indirect similarity to solve the problem which only pay attention to direct relationships, ensuring that the results meet the common definition of community structure (the number of edges between community is greater than that within community). The experimental results show that the AINS algorithm can obtain better community classification result effectively. © 2014 Binary Information Press.

关键词： Information systems

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Mining critical nodes in software execution network based on complex network

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ICIC Express Letters, Part B: Applications 2016年第9期7卷 1879-1884页

作者： Wang, Lei Dong, Jun Ren, Jiadong College of Information Science and Engineering Yanshan University No. 360 Hebei Ave Qinhuangdao066004 China E & A College Hebei Normal University of Science and Technology No. 360 Hebei Ave Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave Qinhuangdao066004 China

It is significant for measuring the importance of nodes accurately to improve software stability and robustness in software network. A software execution directed network takes function as a node and relationship of function as an edge in this paper. To nd the critical nodes in the network, a novel method is proposed to measure the nodes' importance by means of depth search mining in software execution. According to the principle of cascading failure, a novel critical nodes metrics FID is dened for nodes measuring and sorting. Critical nodes mining (CNM) algorithm is put forward for calculating FID value of each node and sorting. We choose top-ranking nodes as critical nodes which play an important role in software execution process. Experimental results show that CNM algorithm can measure the critical nodes accurately in software network. © 2016 ICIC International.

关键词： Complex networks

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A hierarchical residual network with compact triplet-center loss for sketch recognition

arXiv

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arXiv 2021年

作者： Wang, Lei Zhang, Shihui He, Huan Zhang, Xiaoxiao Sang, Yu School of Information Science and Engineering Yanshan University Hebei Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei Qinhuangdao066004 China School of Mathematics and Information Science and Technology Hebei Normal University of Science and Technology Qinhuangdao066004 China

With the widespread use of touch-screen devices, it is more and more convenient for people to draw sketches on screen. This results in the demand for automatically understanding the sketches. Thus, the sketch recognition task becomes more significant than before. To accomplish this task, it is necessary to solve the critical issue of improving the distinction of the sketch features. To this end, we have made efforts in three aspects. First, a novel multi-scale residual block is designed. Compared with the conventional basic residual block, it can better perceive multi-scale information and reduce the number of parameters during training. Second, a hierarchical residual structure is built by stacking multi-scale residual blocks in a specific way. In contrast with the single-level residual structure, the learned features from this structure are more sufficient. Last but not least, the compact triplet-center loss is proposed specifically for the sketch recognition task. It can solve the problem that the triplet-center loss does not fully consider too large intra-class space and too small inter-class space in sketch field. By studying the above modules, a hierarchical residual network as a whole is proposed for sketch recognition and evaluated on Tu-Berlin benchmark thoroughly. The experimental results show that the proposed network outperforms most of baseline methods and it is excellent among non-sequential models at present. Copyright © 2021, The Authors. All rights reserved.

关键词： Touch screens

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A Practical Cloud API Complementary Recommendation Service for Mashup Creation

A Practical Cloud API Complementary Recommendation Service f...

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International Conference on computer Supported Cooperative Work in Design

作者： Xiaowei Liu Wenhui Chen Mengmeng Sun Yali Si Zhen Chen School of Information Science and Engineering Yanshan University Qinhuangdao China School of Computer Science and Engineering Changshu Institute of Technology Changshu China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

With the popularity of the service-oriented development paradigm in the cloud era, numerous cloud APIs have been developed. The continuous proliferation of cloud APIs has submerged developers in a sea of options, bringing the need for cloud API recommendation techniques. Most existing cloud API recommendation methods focus on theoretical studies and neglect practical applications. As a result, these methods face several challenges, such as covering recommendation scenarios, generating real-time responses, and handling concurrent requests. In this paper, we propose and implement a practical cloud API complementary recommendation service for mashup creation. To address the above challenges, we first propose a cloud API complementary recommendation framework named FICR, which exploits feature interactions to mine implicit complementarity and models complementarity from the mashup side and the target cloud API side for scenario coverage. Then, we conduct performance optimization via precoding and batch size tuning to optimize FICR for real-time responses. Finally, we design a minimum-connection load balancing algorithm with resource early warning and build a distributed system for concurrent requests. Experiments conducted on real-world datasets show that FICR outperforms state-of-the-art baseline models in complementary recommendation scenarios, and demonstrate that the implemented service meets the real-time and concurrency requirements. The service will serve as a practical tool to help developers during mashup creation.

关键词： Concurrent computing Federated learning Mashups Precoding Load management Real-time systems Tuning

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RNA secondary structure prediction based on density-based clustering

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ICIC Express Letters 2015年第7期9卷 1965-1970页

作者： Wang, Changwu Wang, Xiuqin Wang, Baowen Liu, Wenyuan Wei, Zhenzhen Li, Yongqiang School of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao China Department of Information The First Hospital of Qinhuangdao No. 258 Hebei Ave Qinhuangdao China

The ribonucleic acid (RNA) secondary structure prediction has designed to characterize the ensemble of structures, instead of only computing the minimum free energy structure. Clustering methods are brought to aid in the characterization of the structure ensemble. These methods group the structures into a small number of clusters. A representative structure for each cluster is computed to characterize the central tendency for the structures in each cluster and used to predict the true secondary structure. This paper introduces a density based clustering with extensible radius dubbed ER-DBSCAN for handling varying density clustering. The basic idea of ER-DBSCAN is to use different values of radius for different densities. It starts from the highest density object towards the lowest density object, and the radius of the cluster is automatically adjusted during cluster expansion according to the density distribution and density variation. Our results indicate that ER-DBSCAN can detect and handle clusters of varying density, and cluster RNA secondary structures effectively. © 2015, ISSN 1881-803X.

关键词： RNA

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Dynamic spectrum allocation scheme with real-time traffic and its performance optimization

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ICIC Express Letters, Part B: Applications 2015年第8期6卷 2243-2250页

作者： Shi, Guoying Jin, Shunfu Li, Yongqiang School of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Avenue Qinhuangdao China The First Hospital of Qinhuangdao No. 258 Wenhua Road Qinhuangdao China

Aiming at relieving the shortage problem of wireless frequency resource, sec- ondary users in cognitive radio networks occupy the spectrum hole opportunistically. In cognitive radio networks, primary users have preemptive priority for the licensed spectrum, and the data transmission of a secondary user is possible to be interrupted by a primary user at any time. For the applications with real-time traffic, the interrupted data is supposed to be discarded by the system. A continuous time queueing model with potential transmission interruption is established accordingly. By using the Laplace transform, the performance measures, such as the average latency, the normalized throughput and the spectrum switching ratio, are presented. The individually and socially optimal strategies are investigated with a non-cooperative game theory, and then a pricing policy for the secondary users is proposed. Experimental results show that the dynamic spectrum allocation scheme with real-time traffic can be optimized socially. © 2015, ICIC International.

关键词： Laplace transforms

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BAT: Mining Binary-API Topic for Multi-service Application Development

BAT: Mining Binary-API Topic for Multi-service Application D...

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International Conference on computer Supported Cooperative Work in Design

作者： Pengfei He Linlin Liu Dianlong You Limin Shen Zhen Chen School of Information Science and Engineering Yanshan University Qinhuangdao China National Science Libraries Chinese Academy of Sciences Beijing China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

With the growing popularity of API-driven multiservice application (mashup) development, the burgeoning web APIs have left developers drowning in the sea of web API selections. Matching developers with the most appropriate APIs is the key to improving user satisfaction and promoting more popular web applications. As a result, more and more researchers pay attention to web API recommender systems based on collaborative filtering. However, employing collaborative filtering to recommend APIs is challenging due to the severe sparsity of mashup and API interactions. To address this problem, we propose a probabilistic generative model, called the Binary-API Topic model (BAT), to parameterize mashups and APIs. Technically, BAT is equipped with a mechanism to extract binary-APIs and predict unknown pairwise interactions. To improve generality and capture more relevance from a limited number of interactions, we learn binary-API topics by directly modeling the generation of API co-occurrence patterns across the repository (all mashup collections from ***). The main advantage of BAT is that it preserves API co-occurrence patterns in model learning and exploits the rich global relevance. Finally, through extensive experiments, we demonstrate that BAT can achieve the highest performance on the sparse real-world data set.

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A DAG-based algorithm of mining frequent closed itemsets in high dimensional datasets

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International Journal of Advancements in Computing technology 2012年第19期4卷 213-222页

作者： Dong, Jun Chen, Shuai Chen, Jing Huang, Guoyan Ren, Jiadong College of Information Science and Engineering Yanshan University 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China Production Management Department Shanghai Aircraft Manufacturing Co.Ltd 200436 China

Algorithms based on row enumeration always scan and construct conditional transposed tables, which increases the execution time and space cost. To address this problem, we adopt the DAG (Directed Acyclic Graph) to compress the dataset to save the memory space. In DAG, each node is related to a rowid, and each two nodes have a corresponding directed edge which stores the common items of the two rowids. Each row is given an integer according to its coming order and the DAG follows that order. A directed acyclic graph records the relation between rows and items by doing AND(&) operation with the nodes' binary code of the edges. We also present DAGHDDM which is a new approach for mining frequent closed itemsets in high dimensional datasets. In this algorithm, we adopt the BitTable to compress the dataset firstly, and then construct DAG according to the BitTable. We increase the same items of the adjacent edges to implement pattern growth, traverse the DAG in reversal way and adopt a close-checking method to generate all frequent closed itemsets. It scans the dataset only once and does not generate candidate itemsets. The experimental results show that the proposed DAGHDDM algorithm can decrease the cost of time.

关键词： Directed graphs

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Redundant filter-based efficient Minkwoski sum computation of polyhedra

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ICIC Express Letters 2014年第10期8卷 2939-2944页

作者： Zhang, Jianfei Guo, Xijuan Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province College of Information Science and Engineering Yanshan University No. 438 West Section of Hebei Avenue Haigang District Qinhuangdao 066004 China College of Computer and Control Engineering Qiqihar University No. 42 Wenhua Street Qiqihar 161006 China

On the basis of the introduction to basic theory of Minkowski sum, we analyze the procedure of constructing the boundary of Minkowski sum and present a new method that can compute Minkowski sum of the polyhedra based on redundant information filtering. The method can filter the edges and facets that can be processed in the next computational stage, and reduce the number of the edges and facets that must be computed to improve the computing performance. The experiments show that the presented method has better performance including computing efficiency, accuracy and degeneration problems and fits for application domains that require high efficient and accurate computation. © 2014 ICIC International.

关键词： Information filtering

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