Existing information systems often lack support to crisis and emergency situations. In such scenarios, the involved actors often engage in ad hoc collaborations necessary to understand and respond to the emerging even...
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(纸本)9783540928300
Existing information systems often lack support to crisis and emergency situations. In such scenarios, the involved actors often engage in ad hoc collaborations necessary to understand and respond to the emerging events. We propose a collaboration model and a prototype aiming to improve the consistency and effectiveness of emergent work activities. Our approach defends the requirement to construct shared situation awareness (SA). To support SA, we developed a collaborative artifact named situation matrixes (SM), which relates different situation dimensions (SD) of the crisis/emergency scenario. A method was also developed to construct and evaluate concrete SM and SD. This method was applied in two organizations' IT service desk teams, which often have to deal with emergency situations. The target organizations found our approach very relevant in organizing their response to emergencies.
E-Learning is increasingly being integrated into universities as a new means of learning and teaching. The web-based learning system can increase the learning efficiency. This paper presents the design and implementat...
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We exhibit an explicit list of nine graphs such that a graph drawn in the Klein bottle is 5-colorable if and only if it has no subgraph isomorphic to a member of the list. This answers a question of Thomassen [J. Comb...
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In the design process of a reconfigurable accelerator employing in an embedded system, multitude parameters may result in remarkable complexity and a large design space. Design space exploration as an alternative to t...
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Web mining is an intensive task which may yield significant insights that may revolutionise business and marketing by using effective information distribution, entertainment and communication techniques. For instance,...
Web mining is an intensive task which may yield significant insights that may revolutionise business and marketing by using effective information distribution, entertainment and communication techniques. For instance, corporations can optimise their eCommerce Websites to maximize impact and personalise the online content of their Websites. Corporations can use Web mining techniques for better understanding about their customers and thus will gain competitive edge by delivering the right information and services. This paper concentrates on reconstruction of visited session which was recorded in a Web log server. Existing approaches for reconstruction of users' session deal only with the time when a user accesses every page, whereas, in this paper, each visited page is incorporated with a pair of ordered time points, which we call biTemporal. Re-produced sessions can be used latter in different ways such as personalization, sequential pattern discovery, etc.
Clustering is a data mining technique that allows the grouping of data points on the basis of their similarity with respect to multiple dimensions of measurement. It has also been applied in the software engineering d...
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Clustering is a data mining technique that allows the grouping of data points on the basis of their similarity with respect to multiple dimensions of measurement. It has also been applied in the software engineering domain, in particular to support software quality assessment based on source code metrics. Unfortunately, since clusters emerge from metrics at the source code level, it is difficult to interpret the significance of clusters at the level of the quality of the entire system. In this paper, we propose a method for interpreting source code clusters using the ISO/IEC 9126 software product quality model. Several methods have been proposed to perform quantitative assessment of software systems in terms of the quality characteristics defined by ISO/IEC 9126. These methods perform mappings of low-level source code metrics to high-level quality characteristics by various aggregation and weighting procedures. We applied such a method to obtain quality profiles at various abstraction levels for each generated source code cluster. Subsequently, the plethora of quality profiles obtained is visualized such that conclusions about different quality problems in various clusters can be obtained at a glance.
This paper outlines how Semantic Web technologies are being adopted, specialized, and put in practice in order to set up a technical infrastructure that will facilitate sharing and reusing of learning resources. The c...
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This paper outlines how Semantic Web technologies are being adopted, specialized, and put in practice in order to set up a technical infrastructure that will facilitate sharing and reusing of learning resources. The case study is a federation of learning repositories with learning resources on agricultural topics, which is being developed in the context of the *** European initiative.
The construction of a wordnet from scratch requires intelligent software support. An accurate measure of semantic relatedness can be used to extract groups of semantically close words from a corpus. Such groups help a...
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The construction of a wordnet from scratch requires intelligent software support. An accurate measure of semantic relatedness can be used to extract groups of semantically close words from a corpus. Such groups help a lexicographer make decisions about synset membership and synset placement in the network. We have adapted to Polish the well-known algorithm of Clustering by Committee, and tested it on the largest Polish corpus available. The evaluation by way of a plWordNet-based synonymy test used Polish WordNet, a resource still under development. The results are consistent with a few benchmarks, but not encouraging enough yet to make a wordnet writer's support tool immediately useful.
One of the Internetpsilas hallmark is the rapid spread of the use of information and communication technology. This has boosted methods for hiding stego information inside digital cover content images which is a conce...
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One of the Internetpsilas hallmark is the rapid spread of the use of information and communication technology. This has boosted methods for hiding stego information inside digital cover content images which is a concerning issue in information security. On the other hand, attack of steganographic schemes has leveraged methods for steganalysis which is a challenging problem. In this paper, first we look at the design of classifiers, such as, support vector machines (SVM) and neural networks (RBF and MLP) which are able to detect the presence of least significant bit (LSB) matching steganography of gray scale images. Second, by combining with feature ranking methods (SVM-recursive feature elimination, Kruskal Wallis) and reduction techniques (PCA) pattern classification of stego is successfully achieved. It is of utmost importance to look at the large set of features extracted from images and find ranking methods able, namely, to exclude correlated and redundant features, avoid the curse of dimensionality or circumvent the need of the steganalyzer to be re-designed. Results show that desirable properties of robustness and resilience are attained by designing classifiers able to deal with redundancy and noise. Moreover, comparison of classifiers performance emphasizes the chosen model for the steganalyser.
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