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An Improvement in Lossless Data Compression via Substring Enumeration 基于子串枚举的无损数据压缩改进
2011 10th IEEE/ACIS International Conference on Computer and Information Science Pub Date : 2011-05-16 DOI: 10.1109/ICIS.2011.41
K. Iwata, M. Arimura, Yuki Shima
{"title":"An Improvement in Lossless Data Compression via Substring Enumeration","authors":"K. Iwata, M. Arimura, Yuki Shima","doi":"10.1109/ICIS.2011.41","DOIUrl":"https://doi.org/10.1109/ICIS.2011.41","url":null,"abstract":"Dube ´ and Beaudoin proposed a new technique of loss less data compression called compression via sub string enumeration (CSE) in 2010. It has been indicated that the compression ratio of CSE achieves competitive performance for ones of the best PPM variants and BZIP2 from the viewpoint of experimental results. We refine the technique of CSE to reduce the candidate value of range to encode, and make the compression performance of our improvement clear analytically for some input strings, which have zero entropy rate. We show that the performance of compression ratio of the improved CSE never becomes worse than one of the original CSE for any source string in linear-time and linear-space complexity for the length of string.","PeriodicalId":256762,"journal":{"name":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127426455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Evaluation of Social Stability Based on Multi-class Support Vector Machine 基于多类支持向量机的社会稳定性评价
2011 10th IEEE/ACIS International Conference on Computer and Information Science Pub Date : 2011-05-01 DOI: 10.1109/ICIS.2011.26
Qianqian Li, Yijun Liu, Wenyuan Niu
{"title":"Evaluation of Social Stability Based on Multi-class Support Vector Machine","authors":"Qianqian Li, Yijun Liu, Wenyuan Niu","doi":"10.1109/ICIS.2011.26","DOIUrl":"https://doi.org/10.1109/ICIS.2011.26","url":null,"abstract":"In the relationship of \"Reform, Development, Stability\", social stability is the foundation of making a nation work well. Therefore, this paper gets into the in-depth source on why the society shows unstable sometimes and establishes an index system for evaluating the social stability trend from the perspective of social combustion theory which is the kernel component of social physics. Furthermore, we construct a mathematical model to assess the social stability by applying multi-class support vector machine. By result analysis, the prediction of multi-class support vector machine is much identical to the reality, which is significant to construct a harmony society.","PeriodicalId":256762,"journal":{"name":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting of Oxidoreductase and Lyase Subclasses by Using Support Vector Machine 用支持向量机预测氧化还原酶和裂解酶亚类
2011 10th IEEE/ACIS International Conference on Computer and Information Science Pub Date : 2011-05-01 DOI: 10.1109/ICIS.2011.13
Y. Wang, Xiuzhen Hu
{"title":"Predicting of Oxidoreductase and Lyase Subclasses by Using Support Vector Machine","authors":"Y. Wang, Xiuzhen Hu","doi":"10.1109/ICIS.2011.13","DOIUrl":"https://doi.org/10.1109/ICIS.2011.13","url":null,"abstract":"Based on enzyme sequence, using composite vector with amino acid composition, low frequency of power spectral density, predicted secondary structure, value of autocorrelation function and motif frequency to express the information of sequence, an approach of support vector machine (SVM) for predicting 18 subclasses of oxidoreductases and 6 subclasses of lyases is proposed. By the Jackknife test, the overall success rates are 89. 9% and 95.1%, our predictive results are better than pervious results Keywords-enzyme, ¦Â-hairpin motif, ligand binding site, support vector machine, minimum redundancy maximum relevance.","PeriodicalId":256762,"journal":{"name":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127006060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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