This survey on control Configuration Selection (CCS) includes methods based on relative gains, gramian-based interaction measures, methods based on optimization schemes, plantwide control, and methods for the reconfig...
Under real driving conditions, the fatigue monitoring system based on drivers' video is highly affected by light environment, which deteriorates the registration of facial information and thus the accuracy of surv...
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The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when user...
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The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when users are searching for specific information on a given topic. Another problem is the massive increase in the number of pages to be indexed by Web search systems. In this research, two steps for Web Crawling are used to decrease these difficulties. First step is the feature selection for the datasets used. A proposed algorithm of feature selection, which uses the Document Frequency technique for the term in the category, is presented. Second step is Web page classification. Two famous techniques of Web page classification are used: (i) Support Vector Machine and (ii) Naïve Bayes Classifier. It is concluded that the proposed algorithm, using Document Frequency technique, reduces the redundancy during feature selection and increases accuracy during Web page classification. Complete evaluation is performed, in JAVA, to indicate the effectiveness of our proposed algorithm.
Traditionally in Web crawling, the required features are extracted from the whole contents of HTML pages. However, the position which a word is located inside the HTML tags indicates its importance in the web page. Th...
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Traditionally in Web crawling, the required features are extracted from the whole contents of HTML pages. However, the position which a word is located inside the HTML tags indicates its importance in the web page. This research proposes two ideas concerning the Feature Selection stage in HTML web pages. The first idea reduces the features by simply extracting them from the important tags in an HTML page in order to achieve faster classification. The second idea gives weights for each of the important tags. Two algorithms are presented in this paper based on these ideas: i) Important HTML tags only algorithm, ii) Weighted Important HTML tags only algorithm. The selected features are classified using two famous classifiers in the literature: Support Vector Machine (SVM) and Naïve Bayes classifier (NBC). The accuracy of each algorithm is computed. Comparison between the accuracies of traditional feature selection method, which uses the whole contents of HTML page, and the proposed algorithms is performed. Complete evaluation is performed which indicates the effectiveness of using our technique. The experimental results show improved precision and recall with the proposed algorithms with respect to keyword-based search. The algorithms are implemented in JAVA and its extended packages.
The autonomous operation of an intelligent service robot in practical applications requires that the robot builds up a map of the environment by itself. A prerequisite for building large scale consistent maps is that ...
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Image security is essential, topic through the increase of the image usage in most of communications besides assures information security which is hidden in these images such as military and medical images. Blowfish i...
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Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship r...
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The paper presents a new modeling framework enabling to evaluate the cyclic steady state of a given system of concurrently flowing cyclic processes (SCCP) on the base of the assumed topology of transportation routes, ...
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Laser powder bed fusion (L-PBF) is the most popular Additive Manufacturing (AM) process for metals. It builds a 3D object layer-by-layer, by spreading metal powder on top of the previous layer and selectively melting ...
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