• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.270-278
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• 2000

A machine vision system using charge coupled device(CCD) camera for the weed detection in a radish farm was developed. Shape features were analyzed with the binary images obtained from color images of radish and weeds. Aspect, Elongation and PTB were selected as significant variables for discriminant models using the STEPDISC option. The selected variables were used in the DISCRIM procedure to compute a discriminant function for classifying images into one of the two classes. Using discriminant analysis, the successful recognition rate was 92% for radish and 98% for weeds. To recognize radish and weeds more effectively than the discriminant analysis, an artificial neural network(ANN) was used. The developed ANN model distinguished the radish from the weeds with 100%. The performance of ANNs was improved to prevent overfitting and to generalize well using a regularization method. The successful recognition rate in the farms was 93.3% for radish and 93.8% for weeds. As a whole, the machine vision system using CCD camera with the artificial neural network was useful to detect weeds in the radish farms.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.735-740
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• 2012

In this paper, we introduce design methodologies of polynomial radial basis function neural network classifier with the aid of Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA). By minimizing the information loss of given data, Feature data is obtained through preprocessing of PCA and LDA and then this data is used as input data of RBFNNs. The hidden layer of RBFNNs is built up by Fuzzy C-Mean(FCM) clustering algorithm instead of receptive fields and linear polynomial function is used as connection weights between hidden and output layer. In order to design optimized classifier, the structural and parametric values such as the number of eigenvectors of PCA and LDA, and fuzzification coefficient of FCM algorithm are optimized by Artificial Bee Colony(ABC) optimization algorithm. The proposed classifier is applied to some machine learning datasets and its result is compared with some other classifiers.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.22-26
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• 2018

The goal of this study was to find out whether early maladaptive schemas (EMS) can be differentiated between the gifted adolescents and delinquent adolescents. Two groups of adolescents were recruited as participants to be surveyed. 144 gifted adolescents were taken from a gifted science and math education center, and 115 delinquent adolescents who had committed crime were taken from 4 police stations in the area of Gyungnam province in Korea. The Korean version of the Schema Inventory for Children was used to measure the level of the early maladaptive schemas (EMS). Stepwise discriminant function analysis yielded a function containing 5 maladaptive schemas (failure, unrelenting standards, vulnerability to harm and illness, loneness/mistrust/abuse, and subjugation), classifying 75.29 accurately into either gifted adolescents or delinquent adolescents. These results suggested that the types of adolescents (gifted adolescents, and delinquent adolescents) can be predicted based on early maladaptive schemas. The findings are discussed from the perspective of Schema Therapy and school counseling.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.691-696
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• 2022

This study explored the lexical sophistication features to distinguish the group membership of English proficiency, using the automatic analysis program of lexical sophistication. A total of 600 essays written by 300 Korean college students were extracted from the ICNALE (International Corpus Network of Asian Learners of English) corpus and a discriminant function analysis was performed using SPSS program. Results showed that the lexical features to distinguish three groups of English proficiency are SUBTLEXUS frequency content words, age of acquisition content words, lexical decision mean reaction time function words, and hypernymy verbs. High-level Korean students used frequent content words from SUBTLEXUS corpus to a lesser degree and produced more sophisticated words that can be learned at a later age and take longer reaction time in lexical decision task, and more concrete verbs.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.168-189
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• 1996

In order for the corporation to get a good image from the customers it should consider several variables, but especially important are corproate ethics and customer satisfaction through quality improvement. Standard multivariate data analysis can be applied to find out the importance of customer satisfaction and corporate ethics as influence factors in the corporate competitive strategy. When applying this Methodology, multivariate normal distributions density function and the identical covariance between groups assumptions have to be satisfied. By using the evaluation result from a small number of specialists in an attempt to decide on the strategical factors that will create a better company image than its competitor, if it chooses to use statistical discriminant analysis method, it would be difficult to satisfy the two assumptions mentioned above. This thesis introduces discriminant analysis method that uses LP/GP effectively which is applicable to this particular situation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• Journal of Korean Society of Forest Science
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• v.58 no.1
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• pp.48-53
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• 1982

This experiment was carried out to distinguish between picea abies (L.) Karsten and Picea koraiensis Nak by the method of discriminant analysis which is used the metrical continuous characteristic on current inorphological plant taxanomy. The results are summarized as follows 1) The discriminant function and discriminant region from the experiment are Z(x)=Z($x_1,\;x_2$)=$0.000379x_1+0.004354x_2-0.311061$ or Z(x)=Z($x_1,\;x_2$=$0.000379(x_1-60.442800)+0.004354(x_2-66.185100)$, $$R_1=(x{\mid}0.000379x_1+0.004354x_2-0.311061{\geq_-}0)$$, $R_2$=($x{\mid}0.000379x_1+0.004354x_2-0.311061$ <0). 2) The probability of misclassification based on the above discriminant region is P($2{\mid}1$)=$P(1{\mid}2)$=0.444 therefore the probability of simultaneous misclassification of P($2{\mid}1$) and $P(1{\mid}2)$ is about 44.4%. 3) the probability of misclassification by the discriminant function resulted from the experiment if recorded as high but it is thought that there is a considerable meaning to perceive the probability of confidence about the discrimination better than its precision.

• Journal of Sasang Constitutional Medicine
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• v.23 no.2
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• pp.194-207
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• 2011

1. Objectives: This study is about a development of Sasang constitutional classification algorithm using facial information. 2. Methods: We analysed the datum of middle aged (20~48) women collected by multi-center researchers in 2007. And this study analysed the data of the measurement of the face by 3D-AFRA (3-Dimensional Automatic Face Recognition Apparatus) and the items of impression by SDQ. We used multiple comparison, exploratory discriminant analysis and clinical decision to select optimal 3D facial variables which will be input in discriminant analysis model. And we used univariate F values and stepwise discriminant function analysis to choose best impression variables. 3. Results and Conclusions: In this study, derived discriminant function's explanation power was 39% in female group. Diagnostic accuracy rate was 66.0% in female group. And in test sample, Sasang constitutional diagnostic accuracy rate was 56.9%. In this process we could help improve the objectification of Sasang constitution diagnosis.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.127-134
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• 2016

PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.

• Health Policy and Management
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• v.5 no.1
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• pp.132-160
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• 1995

This study purported to acquire information necessary to improve the management of general hospitals. It tried to determine major indices which represent managerial performance of general hospitals and to identify the managerial characteristics of general hospitals which affect the major financial indices. Eighty-eight hospitals were chosen from 188 hospitals which were subject to standardization audit by the Korean Hospital Association. The results of a discriminant analysis are summarized as followings. First, when a single index was used to measure managerial performance of the sample hospitals, the ration of net profit to total capital was the best index and its discriminant power was 58.14%. The ratio of the number of boardmen((M. D.) and average daily medical cost were highly related to this index. Second, when two indices were used, income growth rte and the ration of net profit to total capital had the highest discriminant distinction ability. Their discriminant power was 61.9%. In this case, the ratio of the number of boardmen(M. D.) was significantly and highly related to the indices. Third, when all three indices-income growth rate, the ration of net profit to total capital and quick ratio - were used together, a discriminant function was statistically insignificant. Therefore, using all three indices was not useful in measuring managerial performance of the sample hospitals. In conclusion, using two indices-income growth rate and the ration of net profit to total capital-was better in measuring manegerial performance of general hospitals than using a single index. The independent variable which affected these indices was the ration of the number of boardmen. The discriminant function was : $D_{GI}=2.77+4.832\times(the ratio of the number of boardmen)$ *G=growth index(income growth rate) *I=profit index(the ration of net profit to total capital)