• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.730-740
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• 2006

In recent years, bullied students and rogue groups in teenagers make many serious social problems. In this paper we propose a novel approach that more objectively analyzes peer relationships among students. As the data for objective analysis, we use communication history records that are collected from various communication tools such as telephones, e-mails, and messengers. We use the simple intuition that communication history records implicitly contain peer relationship information. And, we adopt data mining techniques for the more systematic analysis. The proposed peer relationship analysis consists of the following steps. First, we formally define the notion of degree of familiarity between friends, and present mathematical equations that compute the degree based on communication history records. In the proposed method, we use the intuition that the degree of familiarity from student x to student y becomes higher as x makes the more communications with y. Second, by using the degree of familiarity between students, we find out the students who are potentially bullied. This procedure is based on the assumption that a bullied student may have a very small number of history records from other students to him. Third, we adopt the clustering technique, one of the most representative data mining techniques, to find out meaningful student groups by using the degree of familiarity. To use the clustering technique, we formally define the notion of similarity between friends based on the degree of familiarity, and perform clustering using the notion. Last, to show the practicality of the proposed method, we have implemented the method and interpreted the meaning of the experimental results. Overall, we believe that our research result provides an effective framework that analyzes peer relationships more objectively and more systematically.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.1-7
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• 1983

In spite of extensive knowledge of the surface chemistry and the transport mechanism in filtration systems, there is still insufficient understanding of the physical characteristics of suspensions and the system components. Because of this, no filtration mechanisms are mathematically generalized to the full extent. The purpose of this paper is to propose experimental equations for the filtration process. using the tracer study in filter layer. Some of results are as follows. (1) The Volume of the specific deposit (${\sigma}$) in filtration was directly measurable using the tracer study without interrupting the filtration. (2) It was also confirmed that the head loss in filtration was greatly in fluenced by the micro-air babbles. (3) The correction coefficient(f) was introduced into the Kozeny-Carman equation in order to apply it for the clogging filter media. The coefficient(f) was experimentally obtained. The total head loss of the filter media is given by next equation. $${\frac{h}{h_0}}={\frac{1}{L}}{\int}^{z=L}_{z=0}f({\sigma})g({\varepsilon}_0,{\sigma})dz$$ $$f=aexp(-b{\sigma})$$ The above equation was applicable without regard to the variation of the suspension concentration, the filter medium diameter, the filter depth, the filtration velocity, and the amount of aluminum in all continuous filtration experiments. (4) The total head loss was graphically generalized assuming mathematical filtration models I II (see fig. 7,8) (5) The total head loss was obtained from the filtration model in the field filtration conditions. (see fig. 9,10)