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Single Object Tracking for Dynamic Programming based on Fine-grained Network

Journal of Physics: Conference Series 2020年第1期1576卷

作者： Jianguo Jiang Kaiyuan Jin Jingjing Wu Meibin Qi Qian Wang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei 230601 China

Single target tracking has always been a key and challenging research field in computer vision. Currently, an increasing number of researchers are focusing on extracting better tracking features and designing the best tracker. This paper proposes a new single target tracking network that uses fine-grained features and dynamic programming (DPFNet). In order to extract superior features, we added an attention module to the regression network enabling us to extract finer-grained and discriminative features to achieve regression. Besides, we did observe that different objects have varying moving rates; for different moving targets, the magnitude of the changes in target position within two adjacent frames is not the same either. Although an area search of 4 times the target's size can be applied to most objects, targets with large position changes may appear in other image areas outside the search area and the target would not be located as a result. Aiming at solving this problem, when designing the tracker, this paper analyzes some of the indicators for predicting the location and uses the analysis results to determine whether the search area is appropriate, so as to dynamically adjust the extent of the search area thereby significantly improving the tracking function. In other words, the size of the search area can be dynamically recalibrated for different images. Subsequent experiments prove that the method put forward in this paper achieves State-of-the-Art results.

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Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

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Journal of Physics: Conference Series 2020年第1期1437卷

作者： Yongzeng Yue Yuhong Zhang Xuegang Hu Peipei Li Key Laboratory of knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei 23061 China

Short text classification methods have achieved significant progress and wide application on text data such as Twitter and Weibo. However, the extremely short chinese texts like tax invoice data are different with traditional short texts in lackness of contextual semantic information, feature sparseness and extremely short length. The existing short text classification methods are difficult to achieve a satisfactory performance in these texts. To address these problems, this paper proposes a text classification method based on bidirectional semantic extension for extremely short texts like Chinese tax invoice data. More specifically, firstly, the Chinese knowledge graph is introduced for extending bidirectional semantic of texts and label data to expand the extremely short texts and ease the problem of feature sparseness; secondly, the hash vectorization is used to avoid the semantic problem caused by the lackness of contextual information. Experimental results conducted the real tax invoice dataset demonstrate the effectiveness of our proposed method.

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Adaptive Job-Scheduling Algorithm based on Queuing Theory in a Hybrid Cloud Environment

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International Journal of Performability engineering 2019年第6期15卷 1580-1590页

作者： Liu, Yanpei Chen, Xiaoni Hu, Ying Cai, Qiang School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450002 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business University Beijing102488 China

To resolve the problem of unreasonable resource allocations caused by the continuous arrival of different types of jobs in a hybrid cloud environment, an adaptive job-scheduling algorithm based on queuing theory is proposed. This paper analyses job load types, and the jobs are classified according to the logistic regression method. A resource utility is used to classify the nodes in a private cloud cluster by considering the heterogeneity of the private cloud resources. Based on the job classification and the resource classification, a queuing model is established, and an adaptive genetic algorithm is used to manage the job queue's arrival rate that becomes the basis of the resource allocation. The proposed algorithm is compared with some existed similar algorithms to verify its performance in terms of job response times and throughput. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Resource allocation

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Automated vision inspection of rail surface cracks: A double-layer data driven framework 48

Automated vision inspection of rail surface cracks: A double...

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48th International Conference on Computers and Industrial engineering, CIE 2018

作者： Zhuang, Li Wang, Long Zhang, Zijun School of Data Science City University of Hong Kong Hong Kong Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China

A double-layer data-driven framework for the automated vision inspection of the rail surface cracks is proposed in this paper. Based on images of rails, the proposed framework is capable to detect the location of cracks firstly and next automatically obtain the boundary of cracks via a feature-based linear iterative crack aggregation (FLICA). Extended Haar-like features are applied to develop significant features for identifying cracks in images. Built on extended Haar-like features, a cascading classifier ensemble integrating three single cascading classifiers with a major voting scheme is proposed to decide the presence of cracks in the image. Each single cascading classifier is composed of a sequence of stage classifiers trained by the LogitBoost algorithm. A scalable sliding window carrying the cascading classifier ensemble is applied to scan images of rail tracks, which is identified by the Otsu’s method, and detect cracks. After completing the crack registration in the first layer, the FLICA is developed to discover boundaries of cracks. The effectiveness of the proposed data-driven framework for identifying rail surface cracks is validated with the rail images provided by the China Railway Corporation and Hong Kong Mass Transit Railway (MRT). Six benchmarking methods, the Otsu’s method, mean shift, the visual detection system, the geometrical approach, fully convolutional networks and the U-net, are utilized to prove advantages of the proposed framework. Results of the validation and comparative analyses demonstrate that the proposed framework is most effective in the rail surface crack detection. © 2018, Curran Associates Inc. All rights reserved.

关键词： Crack detection

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Research and Implementation of Chinese Text Automatic Proofreading System 2

Research and Implementation of Chinese Text Automatic Proofr...

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2018 2nd Annual International Conference on Cloud Technology and Communication engineering, CTCE 2018

作者： Gong, Yonggang Fu, Junying Lian, Xiaoqin Li, Yuying Beijing Key Laboratory of Big Data Technology for Food Safety School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China

The news media platform has a huge amount of original news releases every day, it is impractical to use manual review of text typos. This paper designed and implemented a Chinese text automatic proofreading system for large-scale text content and high-speed processing. The proofreading content is first analyzed and classified: typos and sensitive information. Firstly, the system used the n-gram model to statistically analyze the corpus after segmentation to form a 2-gram model library and a contextual context library;secondly, builded a typo confusion set, and then calculated the probability of the target word in the knowledge base to realize automatic error detection and correction of Chinese text. The system has been successfully applied to the error of the content of many government news media platforms, each server can handle one million articles every day. The results show that the recall rate of the article is 78.9% and the accuracy rate is 85.1%. It meets the demand of high speed and accurate processing of massive text error, and has important practical significance and application fields. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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CitationAS： A Tool of Automatic Survey Generation Based on Citation Content

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Journal of data and Information Science 2018年第2期3卷 20-37页

作者： jie wang chengzhi zhang mengying zhang sanhong deng School of Information Management Nanjing University Nanjing 210023 China Department of Information Management Nanjing University of Science and Technology Nanjing 210094 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Purpose： This study aims to build an automatic survey generation tool, named CitationAS, based on citation content as represented by the set of citing sentences in the original ***/methodology/approach： Firstly, we apply LDA to analyse topic distribution of citation content. Secondly, in CitationAS, we use bisecting K-means, Lingo and STC to cluster retrieved citation content. Then Word2Vec, Word Net and combination of them are applied to generate cluster labels. Next, we employ TF-IDF, MMR, as well as considering sentence location information, to extract important sentences, which are used to generate surveys. Finally, we adopt manual evaluation for the generated ***： In experiments, we choose 20 high-frequency phrases as search terms. Results show that Lingo-Word2Vec, STC-Word Net and bisecting K-means-Word2Vec have better clustering effects. In 5 points evaluation system, survey quality scores obtained by designing methods are close to 3, indicating surveys are within acceptable limits. When considering sentence location information, survey quality will be improved. Combination of Lingo, Word2Vec, TF-IDF or MMR can acquire higher survey *** limitations： The manual evaluation method may have a certain subjectivity. We use a simple linear function to combine Word2Vec and Word Net that may not bring out their strengths. The generated surveys may not contain some newly created knowledge of some articles which may concentrate on sentences with no *** implications： CitationAS tool can automatically generate a comprehensive, detailed and accurate survey according to user’s search terms. It can also help researchers learn about research status in a certain ***/value： Citaiton AS tool is of practicability. It merges cluster labels from semantic level to improve clustering results. The tool also considers sentence location information when calculating sentence score by TF-IDF and MMR.

关键词： Automatic survey system Citation content Clustering algorithms Labelgeneration approaches Sentence extraction methods

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The Second-order h-type Indicators for Identifying Top Units

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data and Information Management 2018年第1期2卷 49-56页

作者： Ye, Fred Y. Bornmann, Lutz School of Information Management Nanjing University 210023 Nanjing China Jiangsu Key Laboratory of Data Engineering and Knowledge Service 210023 Nanjing China Administrative Headquarters of the Max Planck Society Division for Science and Innovation Studies Hofgartenstr. 8 D-80539 Munich Germany

The second-order h-type indicators are suggested to identify top units in scientometrics. Basically, the re-ranking of h-type series leads to the second-order h-type indicator. The second-order h-type indicators provide an interesting and natural method to identify top units, yielding fixed h-top. Differentiating from the series of artificially defined highly cited percentile classes, the h-top contributes a natural definite top in the series of highly cited classes. When studying theoretically, the second-order h-index concerns 3% of the h-top whereas the first-order h-index refers to 10% of the h-core. The ratio of the first- and second-order h-index, hT/h, is 30%. When studying empirically, the ratio of the first- and second-order h-index, hT/h, is © 2018 © 2018 Fred Y. Ye, Lutz Bornmann, published by Sciendo

关键词： Indexing (of information)

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Insight into disinfection byproduct formation potential of aged biochar and its effects during chlorination

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Journal of environmental management 2022年 317卷 115437页

作者： Hailan Yang Shujing Ye Han Wang Chengyun Zhou Ting Xiong Yuanyuan Deng Qianmin Fu Guangming Zeng Zhuotong Zeng Xiaofei Tan Department of Dermatology Second Xiangya Hospital Central South University Changsha 410011 PR China College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China School of Resources Environment and Materials Guangxi University Nanning 530004 PR China. Institute of Big Data and Internet Innovation Hunan University of Technology and Business Changsha 410205 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: zengzhuotong@***. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: tanxf@***.

Biochar can achieve multiple benefits including solid waste management, polluted water remediation, carbon sequestration, and emission reduction. However, various environmental factors (such as temperature variations and dry-wet alternation) and microbial activity may lead to the fragmentation, dissolution, and oxidation of biochar. These accelerate the dissolution of biochar-derived dissolved organic matter (DOM) and then influence disinfection byproducts formation potential (DBPFP) throughout the water treatment process. In this paper, biochars from six biomass feedstocks with five aging processes were prepared, and the DBPFP of biochar and its derived DOM were first studied systematically. Different aging processes might increase the DBPFP of biochar by increasing DOM content and changing the fraction distribution of DOM derived from biochar. Especially, the DBPFP of biochar increased apparently with the chemical aging process. Coexisting with the environmental concentration of humic acid, even aged biochar showed the potential to reduce DBPFP and integrated toxic risk value of the mixed system. In this study, the DBPFP of biochar-derived DOM during the disinfection process is confirmed, and the results can give information to the selection of biomass feedstocks of biochar and its service life in the water treatment process.

关键词： Aged biochar Chlorination Disinfection byproducts Dissolved organic matter Integrated toxic risk value

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A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining

A Coarse-to-Fine Multi-stream Hybrid Deraining Network for S...

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IEEE International Conference on data Mining (ICDM)

作者： Yanyan Wei Zhao Zhang Haijun Zhang Richang Hong Meng Wang Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science Harbin Institute of Technology (Shenzhen) Xili University Town Shenzhen China

Single image deraining task is still a very challenging task due to its ill-posed nature in reality. Recently, researchers have tried to fix this issue by training the CNN-based end-to-end models, but they still cannot extract the negative rain streaks from rainy images precisely, which usually leads to an over de-rained or under de-rained result. To handle this issue, this paper proposes a new coarse-to-fine single image deraining framework termed Multi-stream Hybrid Deraining Network (shortly, MH-DerainNet). To obtain the negative rain streaks during training process more accurately, we present a new module named dual path residual dense block, i.e., Residual path and Dense path. The Residual path is used to reuse com-mon features from the previous layers while the Dense path can explore new features. In addition, to concatenate different scaled features, we also apply the idea of multi-stream with shortcuts between cascaded dual path residual dense block based streams. To obtain more distinct derained images, we combine the SSIM loss and perceptual loss to preserve the per-pixel similarity as well as preserving the global structures so that the deraining result is more accurate. Extensive experi-ments on both synthetic and real rainy images demonstrate that our MH-DerainNet can deliver significant improvements over several recent state-of-the-art methods.

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An Integrated Semantic-Syntactic SBLSTM Model for Aspect Specific Opinion Extraction 15th

An Integrated Semantic-Syntactic SBLSTM Model for Aspect Spe...

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15th Web Information Systems and Applications Conference, WISA 2018

作者： Han, Zhongming Jiang, Xin Li, Mengqi Zhang, Mengmei Duan, Dagao School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing China

ISBN: (纸本)9783030029333

Opinion Mining (OM) of Internet reviews is one of the key issues in Natural Language Processing (NLP) field. This paper proposes a stacked Bi-LSTM aspect opinion extraction model in which semantic and syntactic features are both integrated. The model takes embedded vector which is composed by word embedding, POS tags and dependency relations as its input while taking label sequence as its output. The experimental results show the effectiveness of this structural features embedded stacked Bi-LSTM model on cross-domain and cross-language datasets, and indicate that this model outperforms the state-of-the-art methods. © 2018, Springer Nature Switzerland AG.

关键词： Syntactics

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