• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.67-68
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• 2017

범죄발생의 공간특성을 고려하지 않고, 방범 CCTV에 대한 체계적인 설치계획과 위치, 타당성 검증에 위한 과학적 분석은 전무한 상태에서 주민들의 민원이 빈발하는 지역 등에 CCTV를 중점적으로 설치하는 경우가 대부분인 실정이다. 본 연구는 효율적인 범죄예방을 위해 GIS 공간분석 기반의 표준화된 인위적 감시도구(CCTV) 설치위치 평가 방법론을 정립하기 위한 기초연구로서, 선행연구 및 법 가이드라인 조사를 통해 설문지를 기반으로 통계 분석 및 전문가 회의를 거쳐 CCTV 설치위치 분석을 위한 평가지표를 도출하였다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.185-194
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• 2022

The purpose of this study was to verify the effects of long-distance horseback riding on blood lipid, adipokines and inflammatory markers in obese middle-aged women. The subjects of this study were 9 obese meddle aged women and the data analysed using the paired t-test. The result of this study were as follows: First, TC(p<.01), LDL-C(p<.01), and HDL-C(p<.001) were significantly increased after long-distance horseback riding(LDHR). Second, adiponectin was significantly increased(p<.01) and also PAI-1 was significantly decreased(p<.01) after LDHR. Third, IL-6 was significantly increased(p<.01) after LDHR. These results suggest that long-distance horseback riding has positive effect on changes blood lipid, adipokines, and inflammatory markers in obese middle-aged women. Therefore we consider that effects of long-distance horseback riding has partial examine on prevention and therapy of obesity in middle-aged obese women who undergo physical and emotional big changed.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.415-421
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• 1999

Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA： multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 둥이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation )알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉충의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적 중률을 나타내었다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.415-421
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• 1999

Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA:multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 등이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적 요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation)알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉층의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.

• Journal of Applied Biological Chemistry
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• v.63 no.4
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• pp.393-399
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• 2020

Saposhnikoviae Radix (SR) and Peucedani Japonici Radix (PR) have been used as the main traditional herbal medicines in Korea, China and Japan. In this study, ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UPLC-QTOF/MS)-based metabolomics was applied to evaluate the quality of SR and PR using the marker compounds. In the S-plot of SR and PR, 5-O-methylvisammioside and peucedanol were selected as a marker compound for SR and PR, respectively. Also, an UPLC method was established and well validated for marker compounds of SR and PR. These results suggested that the established analysis method could be used one of the good methods for the classification and quality assessment of SR and PR.

• Journal of Korea Water Resources Association
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• v.44 no.7
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• pp.537-551
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• 2011

Based on optimal input data combination selected in the earlier study, Neuro-Fuzzy flood forecasting model linked Takagi-Sugeno fuzzy inference theory with neural network in Wangsukcheon and Gabcheon is established. The established model was applied to Wangsukcheon and Gabcheon and water levels for lead time of 0.5 hr, 1 hr, 1.5 hr, 2.0 hr, 2.5 hr, 3.0 hr are forecasted. For the verification of the model, the comparisons between forecasting floods and observation data are presented. The forecasted results have shown good agreements with observed data. Additionally to evaluate quantitatively for applicability of the model, various statistical errors such as Root Mean Square Error are calculated. As a result of the flood forecasting can be simulated successfully without large errors in all statistical error. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.243-255
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• 2016

The developed composite index has limits to estimate and predict economic status due to economic pattern change and the response change of explanatory variables. A higher precedence individual indicators should be selected to predict the future accurately. In this study, effectiveness of Jeju Island precedence indicators consists of constituents in the area, the consumer price index, services production index, mining and manufacturing production index. The average temperature of Seogwipo and credit card purchase amount is reviewed as an economic turning point consideration and time lag correlation analysis with real data. In addition, we suggest the proper reference cycle in Jeju composite precedence index and evaluate the configuration in leading indicators for Jeju by comparing national economic indicators. Based on the derived results, the current problems of Jeju Island precedence indicators will be illustrated and the improvement methods to estimate a regional composite index will be suggested.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.303-312
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• 2017

The central goal of Gamma Knife radiosurgery(GKRS) is to maximize the conformity of the prescription isodose surface, and to minimize the radiation effect of the normal tissue surrounding the target volume. There are the various kinds of indices related with the quality of treatment plans such as conformity index, coverage, selectivity, beam-on time, gradient index(GI), and conformity/gradient index(CGI). As the best treatment plan evaluation tool, we must check by all means conformity index, GI, and CGI among them. Specially, GI and CGI related with complication of healthy normal tissue is more indispensible than conformity index. Then author calculated and statistically analysed CGI, the newly defined conformity/gradient index as well as GI being applied widely using the treatment planning system Leksell GammaPlan(LGP) and the verification method Variable Ellipsoid Modeling Technique(VEMT). In the study 10 patients with intracranial lesion treated by GKRS were included. Author computed the indices from LGP and VEMT requiring only four parameters: the prescribed isodose volume, the volume with dose > 30%, the target volume, and the volume of half the prescription isodose. All data were analyzed by paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in GI at 10 cases was observed between LGP and VEMT. Differences in GI ranged from -0.14 to 0.01. The newly defined gradient index calculated by two methods LGP and VEMT was not statistically significant either. Author did not find out the statistical difference for the prescribed isodose volume between LGP and VEMT. CGI as the evaluation index for determining the best treatment plan is not significant statistically also. Differences in CGI ranged from -4 to 3. Similarly newly defined Conformity/Gradient index for GKRS was also estimated as the metric for the evaluation of the treatment plans through statistical analysis. Statistical analyses demonstrated that VEMT was in excellent agreement with LGP when considering GI, new gradient index, CGI, and new CGI for evaluating the best plans of GKRS. Due to the application of the fast and easy evaluation tool through LGP and VEMT author hopes CGI and newly defined CGI as well as gradient indices will be widely used.

• Korean Business Review
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• v.20 no.2
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• pp.119-133
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• 2007

The present study purposed to examine whether BSC, a management renovation method, is as effective in university hospitals, which are non-profit institutions, as it is in profit-making corporations. In order to determine causal relations among the BSC performance measurement indexes, we analyzed a case of university hospital using a structural equation model. The results of analyzing the causal relations among the BSC performance measurement indexes were all statistically significant, and therefore the research hypotheses were all accepted. Future research needs to study causal relations among the BSC performance measurement indexes from the viewpoint of the learning of financial data, growth, internal processes, and customers.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.1
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• pp.78-86
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• 2009

Recently, there seems to besome problems in the urban visual landscape as a result of continuous economic growth and industrial development. At the same time, the public has begun to be aware of the importance of visual resources, and the necessity for visual landscape conservation and improvement. Therefore, the development of evaluative indicators for systematic visual landscape planning and design is urgent. The purpose ofthis study is to discover evaluative models and indicators for the diagnosis of urban visual landscapes. This study included the selection of 18 physical indicators(statistical data) by literature reviews, adoption of field and questionnaire surveys at 12 autonomous districts in Seoul and surrounding major mountain valleys and river streams(i.e. Mt. Nam and Han-River). The content of the questionnaire is scenic beauty. Moreover, the linear regression analysis between the scenic beauty mean scores and the physical indicator scores figure out the scenic beauty prediction model. As this study suggests, the most important indicators in urban visual landscapes are 'Greens', 'Park' and 'the number of apartment buildings(higher than 20 stories).' Based on the results, greens and parks should be priority elements to considerin urban landscape planning and design. Moreover, since the number of apartment buildings that are higher than 20 stories has a negative correlation with the scenic beauty score, it can be used as basic data for landscape planning. For the scenic beauty prediction models and evaluative indicators suggest a direction of urban management, each indicator becomes basic data for visual landscape planning and design. In following studies, if physical indicators and case studies are added, the scenic beauty prediction models and evaluative indicators could be more synthetic and systematic. Moreover, the development of physical indicators in three dimensions(3D)(i.e. results from visual district analysis, view surface analysis) could be expected to obtain more general and varied results.