• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5120-5126
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• 2010

ABLB(Alternate Binaural Loudness Balance) test is one of the medical assessments to diagnose detailed lesion of sensory-neural hearing loss based on a recruitment phenomenon. This paper describes an Auto ABLB test software. This software automatically decides test frequency and intensity of first test tone. And it supports an automatic algorithm that analyses the subject's reponses in the current step and then decides intensity of tone provided in next step. Also, this software supports an interface to control and monitor subject's ABLB test. The assessment result is represented by a ladder diagram. The output of this software has been verified using a digital oscilloscope.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.6
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• pp.519-524
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• 2011

ABLB (alternate binaural loudness balance) test is one of the medical assessments to diagnose detailed lesion of sensory-neural hearing loss based on a recruitment phenomenon. However, current ABLB audiometry takes an operational model, so called face-to-face model, in which model one audiometrist can assess only one subject at a time. As a result, this face-to-face model leads to expensive audiometrist's labor cost and lengthy wait when there exist many subjects. As a solution, this paper suggests an ABLB audiometry system supporting one-to-many model in which model an audiometrist enables to assess several subjects concurrently. By providing such capabilities as real-time transfer of assessment result, video monitoring of subject and video chat, this solution can provide same effect as face-to-face model but overcome weakness of the existing face-to-face model.

• Plant Resources
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• v.5 no.3
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• pp.214-223
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• 2002

The objective of this study was to understand the conservation of gene resources and provide information for mass selection' of winter bud characters among the selected populations of Kalopanax septemlobus Koidz using analysis of variance(ANOVA) tests. The obtained results are shown below; 1. Ten populations of K. septemlobus were selected for the study of the variation of winter bud characters in Korea. The results of the analysis of variance(ANOVA) tests shows that there were statistically significant differences in all of the winter bud characters among those populations. 2. Correlation analysis shows that width between Height and DBH(Diameter at breast height) characters have negative relationship with all of the characters, as ABL(Apical branch length), ABW(Apical branch width), AWBL(Apical branch winter bud length), AWBW(Apical branch winter bud width), ABT(Apical branch No. of thorns), ABLB(Apical branch No. of lateral bud) and LBL(Lateral branch length), LBW(Lateral branch width), LBT(Lateral branch No. of thorns), LBLB(Lateral branch No. of lateral bud). 3. The result of principal component analysis(PCA) for winter buds showed that the first principal components(PC' s) to the fourth principal component explains about 78% of the total variation. The first principal component(PC) was correlated with AWBW, LWBW, and LBL and the ratio of ABL/ABW and LBL/LBW out of 16 winter bud characters. The second principal component correlated with ABL, ABW, ABLB, LWBL(Lateral branch winter bud length), and LBW and the ratio of AWBL/AWBW. The third principal component correlated with ABL, ABW, LWBL, LBL, and the ratio of LBL/LBW. The fourth principal component correlated with LBL and the ratio of LWBL/LWBW(Lateral branch winter bud width), LBL/LBW. Therefore, these characters were important to analysis of the variation for winter bud characters among selected populations of K. septemlobus in Korea. 4. Cluster analysis using the average linkage method based on 10 selected populations for the 16 winter bud characters of K. septemlobus in Korea showed a clustering into two groups by level of distance 1.1(Fig. 3). As can be seen in Fig. 3, Group I consisted of three areas(Mt. Sori, Mt. Balwang and Mt. Worak) and Group Ⅱ contisted of seven areas(Suwon, Mt. Chuwang, Mt. Kyeryong, Mt. Kaji, Mt. Jiri, Muan, and Mt. Halla). The result of cluster analysis for winter bud characters corresponded well with principal component analysis, as is shown in Fig. 2.