• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1245-1245
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1152-1152
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.385-392
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• 2012

Logistic regression is a well known binary classification method in the field of statistical learning. Mixed-effect regression models are widely used for the analysis of correlated data such as those found in longitudinal studies. We consider kernel extensions with semiparametric fixed effects and parametric random effects for the logistic regression. The estimation is performed through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of optimal hyperparameters, cross-validation techniques are employed. Numerical results are then presented to indicate the performance of the proposed procedure.

• Tunnel and Underground Space
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• v.14 no.2
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• pp.133-141
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• 2004

Through the many site investigations, different methods for evaluating stability of rock slopes have been proposed. Those methods, however, may lead to different results depending on the subjective judgments associated with the selection of the evaluation items and the application of weighting factor. Accordingly, binary logistic regression analysis was carried out to ensure fair appliction of the weighting factor, leading to an equation for evaluating the stability of rock slopes.

• The Journal of Korean Medicine
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• v.27 no.1 s.65
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• pp.118-129
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• 2006

Objectives : A human being is classified into 4 constitutions(Taeyangin, Soyangin, Taeumin, and Souemin) and each constitution has the different incidence, treatment and prevention of disease in Sasang Constutional Medicine[SCM], The purpose of this study is to find relative risk(RR)s of each risk factors including Sasang Constitution[SC] for incidence of ischemic stroke. Methods : In 344-case patients with ischemic stroke and 1446 healthy control subjects without ischemic stroke, we evaluated sex, age. height, weight, BMI, ECG abnormality, hypertension, diabetes mellitus, blood lipid level and SC. These data were statistically analysed to investigate the relations between risk factors and the incidence of ischemic stroke by chi-square test. And then significant factors were analysed to get each adjusted odds ratio[OR] by binary logistic regression analysis. Results : ECG abnormality, hypertension, diabetes mellitus, HDL(high density lipoprotein) cholesterol, and SC were significantly related to the incidence of ischemic stroke, while age, sex and BMI were adjusted in a binary logistic regression analysis. Especially in SC, the incidence of ischemic stoke in Tae-eumin and Soyangin were higher than that in Soeumin (Tae-eumin OR=11.68[95% CI: 6.26-21.80], Soyangin OR=4.64[95% CI: 2.66-8.10]). Conclusions : These results suggested that SC may be one of important risk factors for ischemic stroke and it should be a useful data for prediction of incidence of ischemic stroke.

• Journal of Oriental Neuropsychiatry
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• v.16 no.2
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• pp.65-72
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• 2005

Objectives : This study is for discovering the clinical Features of the sleep in ordinary symptoms based on the Sasang Constitution. The result of this study could be helpful to understand and to identify the patients as Soyangin in contrast with the other constitutions -Soeumin, Taeumin and Taeyangin. Methods : There were 1,229 patients(700 female), who answered the questionnaire about their ordinary sleeping patterns. They had been diagnosed, including their clinical Sasang Constitution, by the Sasang Constitution specialist at Bundang Oriental Hospital of Dongguk University. By applying the binary logistic regression analysis, we can measure the characteristics and the influence of ordinary sleeping patterns to the dependent variable(Sasang Constitution). Results : As a result of the binary logistic analysis on the observed questionnaire, we found the characteristics of the ordinary sleeping patterns on Soyangin in contrast with the other constitutions. Firstly, Soyangin has a tendency that he wouldn't dreams more, when he sleeps in contrast with the others. Secondly, Soyangin has a tendency that he wouldn't sleep longer than 6-7hours. Thirthly, Soyangin has a tendency that he will sleep well in contrast with the others. Conclusion : This study will be used to identify patients as Soyangin in contrast with the others-Soemin, Taeumin and Taeyangin.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.9-15
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• 2011

This study analyzed contributing factors affecting leg injury severity in pedestrian-vehicle crashes. A Binary Logistic Regression (BLR) method was used to identify the factors. Independent variables include characteristics for pedestrian, vehicle, road, and environmental conditions. The leg injury severity is classified into two classes, which are dependent variables in this study, such as 'severe' and 'minor' injuries. Pedestrian age, collision speed, and the height of vehicle were identified as significant factors for the leg injury. The probabilistic outcome of predicting leg injury severity can be effectively used in not only deriving pedestrian-related safety policies but also developing advanced vehicular technologies for pedestrian protection.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.33-40
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• 2021

The purpose of this study is to analysis the influence of personal backgrounds on the preference of fishing village experience recreation villages. As the analysis method, binary logistic regression analysis was used. Dependent variables are experience recreation villages (rural and fishing). The independent variables consist of 9 groups of people: gender, age, family type, marital status, presence of children, principal companion, fishing village image, visit experience villages, recognition of fishing village experience recreation village. As a result of the analysis, it was found that the tourist's gender, age, family type, marital status, presence of children, principal companion, fishing village image, visit experience villages, recognition of fishing village experience recreation village influence the preference of fishing village experience recreation village. By characteristics of each group, it was found that male prefer fishing village experience recreation villages 1.597 times as much as female, and those with a positive image about fishing villages prefer fishing village experience recreation villages as much as 2.644 times than those with negative images. In addition, it was found that those who visited the fishing village experience and recreation village prefer the fishing village experience village about six times more than those who have never visited.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.42-48
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• 2015

This paper has its purpose on constructing a prediction model of the arrival sequencing strategy which reflects the actual sequencing patterns of air traffic controllers. As the first step, we analyzed a pair-wise sequencing of two aircraft entering TMA from different entering points. Based on the historical trajectory data, several traffic factors such as time, speed and traffic density were examined for the model. With statistically significant factors, we constructed a prediction model of arrival sequencing through a binary logistic regression analysis. With the estimated coefficients, the performance of the model was conducted through a cross validation.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.366-374
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• 2015

This study investigated what factors would affect suicidal ideation of the people who have received public assistance. For the purpose, the survey results of the 7th year(2012) of Korea Welfare Panel Study, which were conducted by Korea Institute for health and Social Affairs and Social Welfare Research Institute of Seoul National University, were used for analysis. In order to figure out the level of influence on the suicidal ideation, a binary logistic regression analysis using a binary logistic model was used as an analysis method. As a result, it was found that when the subjects are middle school graduates, and if they are married, there are low suicidal ideation. Also, the higher their self-esteem is and the higher their satisfaction with public assistance, the lower there they have suicidal ideation. Furthermore, it was proved that if they have depression, or in middle age, they have high possibility of suicidal ideation. It was proved that satisfaction with public assistance also can have influence on the suicidal ideation of the poor class, not only physical and psychological factors. Therefore, measuring the satisfaction of the recipients with public assistance can be one of the significant factors that affects suicidal ideation.