The most important thing for learners in Programming Language subject is problem solving. During ... more The most important thing for learners in Programming Language subject is problem solving. During the practical programming project, various problems may occur and learners usually need consultation from the senior programmers (i.e. the experts) to assist them in solving the problems. Thus, the inquiry-based learning with learning forum is applied to assist the programming problem solving. However, even if the learning community of the forum is provided, the finding of trustworthy and available experts for improving the quality of social interactions is still difficult for students. Therefore, the idea of applying the social network service of Web 2.0 with the trustworthy experts finding service is proposed to actively consult the experts based on their topic of interest, trustworthiness, and availability. The experts' topic interest and trustworthy degree are obtained from the experts' posting documents on the forum. To maintain the dynamic discussion topics and avoid the synonym problem on the forum, the Programming Capability Ontology is constructed as the consensus taxonomy by the distributed clustering algorithm. The self-organized ontology maintenance scheme is also proposed to maintain and update the new topic keywords in the ontology. The availability of experts can be approximately calculated from their online presence log. Moreover, the updating of the experts' presence value is modeled by the fading probability function of the Ant Colony Algorithm. Finally, the quality of the expert finding service and learners' satisfaction with the expert finding service has been evaluated. The experimental result shows that the feasibility and the effectiveness of the proposed approach are satisfactory.
Short term electricity load forecasting is nowadays, of paramount importance in order to estimate... more Short term electricity load forecasting is nowadays, of paramount importance in order to estimate next day electricity load resulting in energy save and environment protection. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior to modeling. This identification, known as day-type identification, must be included in the modeling stage either by segmenting the data and modeling each day-type separately or by including the day-type as an input. This paper investigates day-type identification approach for Algerian electricity load. Kohonen maps are used to identify daytypes. The K-Means clustering method will be used as a complementary method to precisely identify the obtained classes. Clustering validity is done by using a criteria measurement of quality. This work has allowed the identification of six different classes.
The most important thing for learners in Programming Language subject is problem solving. During ... more The most important thing for learners in Programming Language subject is problem solving. During the practical programming project, various problems may occur and learners usually need consultation from the senior programmers (i.e. the experts) to assist them in solving the problems. Thus, the inquiry-based learning with learning forum is applied to assist the programming problem solving. However, even if the learning community of the forum is provided, the finding of trustworthy and available experts for improving the quality of social interactions is still difficult for students. Therefore, the idea of applying the social network service of Web 2.0 with the trustworthy experts finding service is proposed to actively consult the experts based on their topic of interest, trustworthiness, and availability. The experts' topic interest and trustworthy degree are obtained from the experts' posting documents on the forum. To maintain the dynamic discussion topics and avoid the synonym problem on the forum, the Programming Capability Ontology is constructed as the consensus taxonomy by the distributed clustering algorithm. The self-organized ontology maintenance scheme is also proposed to maintain and update the new topic keywords in the ontology. The availability of experts can be approximately calculated from their online presence log. Moreover, the updating of the experts' presence value is modeled by the fading probability function of the Ant Colony Algorithm. Finally, the quality of the expert finding service and learners' satisfaction with the expert finding service has been evaluated. The experimental result shows that the feasibility and the effectiveness of the proposed approach are satisfactory.
Short term electricity load forecasting is nowadays, of paramount importance in order to estimate... more Short term electricity load forecasting is nowadays, of paramount importance in order to estimate next day electricity load resulting in energy save and environment protection. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior to modeling. This identification, known as day-type identification, must be included in the modeling stage either by segmenting the data and modeling each day-type separately or by including the day-type as an input. This paper investigates day-type identification approach for Algerian electricity load. Kohonen maps are used to identify daytypes. The K-Means clustering method will be used as a complementary method to precisely identify the obtained classes. Clustering validity is done by using a criteria measurement of quality. This work has allowed the identification of six different classes.
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Papers by Ramadhan Hsu