This special issue is partly associated with the 2010 International Work Shop on Information Security and Applications (IWISA 2010) and 2010 Symposium on Cryptography, Data mining, E-commerce and Embedded systems (CDEE 2010), which was held in Yanshan University Qinhuangdao, China in October 2010. While some other manuscripts are solicited from the authors who are not participants of the conference. The purpose of this special issue is to provide a fast publication of high-quality conference papers on computer software or related to computer software and also the papers from authors with original high-quality contributions that have neither been published in nor submitted to any journals or refereed conferences. Papers are mainly interdisciplinary research in computer software related theory and computer software related techniques to unsolved problems.
  We received 31 papers from around the world and selected 11 to be included in the special issue after a thorough and rigorous review process. The presented papers are mainly devoted to discussion on Algorithm, Knowledge Discovery, Data mining, Matlab Application, and Cloud Computing or using software related algorithms to solve problems in other area.
  In “Incremental Learning Algorithm for Support Vector Data Description”, Xiaopeng Hua et al. analyzes the possible changes of support vector set after new samples are added to training set according to the relationship between the Karush-Kuhn-Tucker (KKT) conditions of SVDD and the distribution of the training samples. Based on the analysis result, a novel algorithm for SVDD incremental learning is proposed. In this algorithm, the useless sample is discarded and useful information in training samples is accumulated. Experimental results indicate the effectiveness of the proposed algorithm.
  In “A Super Data-sharing Model in Common Platform of Geographic Information”, Xin Liu et al. put forward a data-sharing model in the common platform of geographic information. The data model architecture in the common platform is mainly compose of the entity-oriented vector data model in the three-dimensional space, the layer and tile pyramid grid data, the relationship table or WORD files and so on. The data model was realized in C/C++ development environment in Windows XP.
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