2006, Vol.11, No.3

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

pISSN : 1598-849X / eISSN : 2383-9945
https://journal.kci.go.kr/jksci

It is widely accepted that the coverage with high user densities can only be achieved with small cell such as micro- and pico-cell. The smaller cell size causes frequent handovers between cells and a decrease in the permissible handover processing delay. This may result in the handover failure, in addition to the loss of some packets during the handover. In these cases, re-transmission is needed in order to compensate errors, which triggers a rapid degradation of throughput. In this paper, we propose a new handover scheme in the next generation mobile communication systems, in which the handover setup process is done in advance before a handover request by predicting the handover cell based on mobile terminal's current position and moving direction. Simulation is focused on the handover failure rate and packet loss rate. The simulation results show that our proposed method provides a better performance than the conventional method.

This paper describes the technique which utilizes a fuzzy neural network to sketch feature extraction in digital images. We configure an artificial neural network and make it learn fuzzy membership functions to decide a local threshold applying to sketch feature extraction. To do this, we put the learning data which is membership functions generated based on optimal feature map of a few standard images into the artificial neural network. The proposed technique extracts sketch features in an image very effectively and rapidly because the input fuzzy variable have some desirable characteristics for feature extraction such as dependency of local intensity and excellent performance and the proposed fuzzy neural network is learned from their membership functions, We show that the fuzzy neural network has a good performance in extracting sketch features without human intervention.

This study applies the cognitive apprenticeship theory, a representative learning theory of constructivism, to design and create a web courseware for data device operator license, to enable research that begins with peripheral participation in problem solving and ends with full participation and initiative, to act as a medium for assisting students in learning, to enable adaptation to actual situations through simulation studies, to allow aggressive interaction, and to help reinforce the level of data processing with regard to learning. The student was made to evaluate learning materials at real time for feedback on insufficient areas, to enable effective learning. The study was done by offering a web courseware without applying the cognitive apprenticeship theory and a web courseware with the cognitive apprenticeship theory, which was followed by an evaluation on study achievement level and learning behavior. and then a survey was done after the evaluations. The results of this study were first, the learning group with web courseware applying cognitive apprenticeship theory showed more effect in improving learning achievement than the group with web courseware without the cognitive apprenticeship theory. Secondly, learning with web courseware applying cognitive apprenticeship theory was more effective for improving learning behavior.