To study effects of wild garlic on components of lipid and protein, blood glucose level, and cholinesterase activity in rat's serum, Sprague-Dawley strain of 40 male rats are divided into 5 groups which are Normal, Control, A, B, and C group. Normal group is fed only Basal diet, and Control group is fed Basal diet and 0.5ml/day of 2.5% cholesterol solution, In addition to a diet of control group, A group is fed 25% wild garlic flour, B group 0.5ml/2day of concentratded wild garlic juice, C group 0.5ml/2day of concentrated ethanol extract of wild garlic, After 8 weesk the rats were fasted for 12 hours, and then decapitated to collect blood. The results of analysis of the rat's serum were summarized as follows, 1. Wild garlic diet, specially ethanol extract has an influence on decreasing the level of total cholesterol and blood glucose in rat's serum, 2. HDL-cholesterol and phospholipid content of rat's serum are increased by wild garlic diet. Therefore I think that wild garlic is good food for preventing development of atherosclerosis and diabetes.

본 연구의 목적은 초등교사들의 다문화교육과정 실행 유형을 분석하고 각 실행 유형에 따른 교사들의 다문화교육 관련 학습경험을 탐색하는 것이다. 이를 위해 초등교사 6명을 대상으로 심층면담을 수행한 결과, 실행 유형은 세 가지 유형으로 구분되었으며, 사회 행동적 접근의 실행 유형은 나타나지 않았다. 또한 실행 유형에 따라 다른 교사학습 경험이 도출되었다. 유형 1(교육과정 의존하나 필요에 따라 사례 추가)의 교사들은 다문화가정 학생과의 경험, 강의식 연수 경험, 동 학년 교사 간 수업 자료 공유 경험이 있었다. 유형 2(교육과정에 제시되지 않은 목표 추가)의 교사들은 토론식 연수 경험, 동 학년 간 협동적 수업 개발이나 협력적 문제해결 경험이 있었다. 유형 3(교육과정에 포함되지 않은 다양한 관점 반영)의 교사들은 다문화교육 관련 탐구 경험이 있었다. 연구결과를 토대로 교사들의 다문화교육과정 실행을 지원하는 전략들을 개발하기 위한 시사점을 제시하였다.

Recent years, there is increasing demand for seedlings of Daphniphyllum macropodum. However, the bare-root nursery of the species has been reported to be challenging due to meteorological disasters caused by climate change. The study aims to investigate the appropriate levels of shade and fertilization of container-grown D. macropodum, which has shade tolerance in seedling stage. The shading treatment was regulated with the shading level of full sun, and 35%, 55%, 75% of full sun. The fertilizing level was made by regulating Multifeed 19 (N:P:K =19:19:19, v/v) with 1000mg·L-¹, 2000mg·L-¹, 3000mg·L-¹, together with the control. The height was indicated to be the highest in 3000mg·L-¹ under 55% of shading. The root collar diameter was surveyed to be the highest in 1000mg·L-¹ and 3000mg·L-¹ of full sun. A case of the whole dry mass production was surveyed to be the highest in 3000mg·L-¹ under 55% of shading and 2000mg·L-¹ under 35% of shading. Moreover, the study is to explore the possibility of production and sound growth of D. macropodum seedlings by container nursery; consequently, the result is expected to provide the production method of the seedlings of D. macropodum that is to overcome meteorological disasters from bare-root nursery.

This paper introduces a design of multi-dimensional complex emotional model for various complex emotional expression. It is a novel approach to design an emotional model by comparison with conventional emotional model which used a three-dimensional emotional space with some problems; the discontinuity of emotions, the simple emotional expression, and the necessity of re-designing the emotional model for each robot. To solve these problems, we have designed an emotional model. It uses a multi-dimensional emotional space for the continuity of emotion. A linear model design is used for reusability of the emotional model. It has the personality for various emotional results although it gets same inputs. To demonstrate the effectiveness of our model, we have tested with a human friendly robot.

In face recognition, learning speed of face is very important since the system should be trained again whenever the size of dataset increases. In existing methods, training time increases rapidly with the increase of data, which leads to the difficulty of training with a large dataset. To overcome this problem, we propose SVDD (Support Vector Domain Description)-based learning method that can learn a dataset of face rapidly and incrementally. In experimental results, we show that the training speed of the proposed method is much faster than those of other methods. Moreover, it is shown that our face recognition system can improve the accuracy gradually by learning faces incrementally at real environments with illumination changes.