• Clinical and Experimental Pediatrics
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• v.48 no.8
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• pp.826-831
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• 2005

Purpose : This study is directed to evaluate standardized developmental test performances of infants and children who, as fetuses, had mild isolated cerebral ventriculomegaly diagnosed by ultrasound. Methods : All prenatal sonographic findings from 2001 to 2002 were evaluated. Live isolated mild ventriculomegaly(IMVM) of 10-15 mm were observed in 95 cases(1.1 percent). Standardized developmental testing of 40 cases of IMVM and 36 cases in a comparison group were offered to parents Both groups of children were adjusted to normal antepatum subjects with respect to sex, race, indication for ultrasound and gestational age at the time of ultrasound. Test of cognitive and motor development(Bayley Scales of Infant Development, Second Edition; BSID-II) were administered by developmental examiners. Results : Forty cases and 34 comparison sujects completed the testing. The IMVM and comparison groups were similar with respect to parental age, gestational age, birth weight, familial socioeconomic status. The IMVM subjects scored lower than the comparison group on both the BSID-II, but there was not statistically significant. differences; metal development index(MDI)($92.7{\pm}12.9$ vs $94.7{\pm}14.1$, P=0.47) and psychomotor development index(PDI)($100.3{\pm}14.1$ vs $101.3{\pm}10.7$, P=0.75). Eleven cases(27.5 percent) of IMVM group and five cases(14.7 percent) of the comparison group were developmentally delayed, but most cases in both groups showed mild delays. Resolution or lack of progression, lateral ventricle diameter ${\leq}12mm$ and females were associated with better scores, but there were not statistically significant. Polarity, and head circumference were not related to later development. Conclusion : This study show children with MIVM did not delay performance in the developmental test, but we might suggest a tendency to increase the risk of mild developmental delay.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.