• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.11-21
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• 2001

This study investigates how motivations, preferences, and past experiences vary by each hikers trail choice at the Mt.Keyryong National Park. The purpose of this study is to find out the factors influencing behavioral choice in the recreation areas, and establish the fundamental theory for the efficient management of the resource and visitors. For this study, we have collected 472 respondents by on-site self-administrated questionnaire from the hikers in the park. The collected data were analyzed by the descriptive statistics and the discriminant analysis. The motivations variable of hiking participation on mountain trail were categorized three types; close-nature, escapism, and physical improvement. The preferences for trail environment were classified as four categories by factor analysis; preference for nature, safety, use density, and facilities. In descriptive statistics, the study showed that the experienced hikers prefer natural trials and hikers who have preference for close-nature select longer and deeper forest trails. The results of discriminant analysis indicate that the level of past experience is the most affectable in classification of trail choice. Such variables as motivation for close-nature and preference for nature were also appeared as affecting factors on classification of trail choice. Two discriminant functions were available, and 90.5 percent of analysis sample were correctly classified. In the validity analysis, 89 percent of holdout sample were correctly classified. These hit ratios ensures an accuracy by Press Q test. The result of this study is to be useful knowledge of the choice of detailed use environments in the same recreation areas.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.250-255
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• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.360-368
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• 1994

To this day, a number of quantitative analytical methods have been employed in clarifying regional characteristics in the discipline of geography. This paper attempted, as a part of application of those quantitative analyses, to make clear the urban functions and consequently the urban characteristics statistically by adopting newly-introduced CHAID, a sort of discriminant analyis technique. The processing of data was sonducted in two phases. To begin with, the urban functions were classified after designating twenty cities - the population of each city counting 250, 000 or more - as predictor variable, and at the same time four major urban functions like administration, marketing, finance and production as response variable. And then, preeminent functions of individual region were discriminated and concurrently classified by treating the remaining traffic, education, medicare, culture and transportation functions as predictor variable, and the following five regions as response variable: Metropolitan Seoul Area. Pusan region, Taegu region, Kwangju region and Chungcheong region. According to the result of this analysis, marketing and administration are emereed as meaningful functions in Seoul and Taegu respectively. As for the finance function only Pusan and Pucheon can be discriminated. Seoul, Pusan and Seongnam reveal their dominancy in production function. To take a look at the result of the latter analysis, the Metropolitan Seoul area shows, among other functions, strong traffic and finance functions. When it comes fo Pusan region, adminstration, education and finance functions are recorded as a leading ones, and Taegu region is preferable in education, medicare and transportation functions. In case of Kwangju region adminstration, production and education functions are discriminated from any other functions. Chungcheong region shows similar aspect with only traffic function replacing the production function of Kwangju region. Based on aforementioned anlysis, it can be said that the CHAID technique, which is capable of processing large amount of categorical data and, by presenting its outcome in the form of dendrogram, facilitates the interpretation work, is an effective, meaningful means to classify and discriminate certain geographical regions and their characteristics.

• Journal of Sasang Constitutional Medicine
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• v.23 no.4
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• pp.458-470
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• 2011

1. Objectives Vocal characteristics are commonly considered as an important factor in determining the Sasang constitution and the health condition. We have tried to find out the classification procedure to distinguish the constitution objectively and quantitatively by analyzing the characteristics of subject's voice without noise and error. 2. Methods In this study, we extract the vocal features from voice selected with prior information, remove outliers, minimize the correlated features, correct the features with normalization according to gender and age, and make the discriminant functions that are adaptive to gender and age from the features for improving diagnostic accuracy. 3. Results and Conclusions Finally, the discriminant functions produced about 45% accuracy to classify the constitution for every age interval and every gender, and the diagnostic accuracy was meaningful as the result from only the voice.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.755-764
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• 1996

A multispectral imaging system with selected wavelength optical filter was demonstrated feasible for food safety inspection. Intensified multispectral images of carcasses were obtained with visible/near-infrared optical filters(542-847 nm wavelengths) and analyzed. The analysis of textural features based on co-occurrence matrices was conducted to determine the feasibility of a multispectral image analyses for discriminating unwholesome poultry carcasses from wholesome carcasses. The mean angular second moment of the wholesome carcasses scanned at 542 nm wavelength was lower than that of septicemic (P$\leq$0.0005) and cadaver(P$\leq$0.0005) carcasses. On the other hand, for the carcasses scanned at 700nm wavelength , the feature values of septicemic and cadaver carcasses were significantly (P$\leq$0.0005) different from wholesome carcasses. The discriminant functions for classifying poultry carcasses into three classes (wholesome, septicemic , cadaver) were developed using linear and quadr tic covariance matrix analysis method. The accuracy of the quadratic discriminant models, expressed in rates of correct classification, were over 90% for the classification of wholesome, septicemic, and cadaver carcasses when textural features from the spectral images scanned at the wavelength of 542 and 700nm were utilized.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.93-100
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• 1988

The Auto Regressive Parameter Estimation and Pattern Classification of EKG Signal for Automatic Diagnosis. This paper presents the results from pattern discriminant analysis of an AR (auto regressive) model parameter group, which represents the HRV (heart rate variability) that is being considered as time series data. HRV data was extracted using the correct R-point of the EKG wave that was A/D converted from the I/O port both by hardware and software functions. Data number (N) and optimal (P), which were used for analysis, were determined by using Burg's maximum entropy method and Akaike's Information Criteria test. The representative values were extracted from the distribution of the results. In turn, these values were used as the index for determining the range o( pattern discriminant analysis. By carrying out pattern discriminant analysis, the performance of clustering was checked, creating the text pattern, where the clustering was optimum. The analysis results showed first that the HRV data were considered sufficient to ensure the stationarity of the data; next, that the patern discrimimant analysis was able to discriminate even though the optimal order of each syndrome was dissimilar.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• Journal of Sasang Constitutional Medicine
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• v.23 no.2
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• pp.208-217
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• 2011

1. Objectives: The purpose of this study was done to compare Sasang Constitution diagnostic rate between taking Sasang Constitution herb medicine patients and non taking group. 2. Methods: We collected data from 430 patients who were visited at the Department of Sasang Constitution, College of Oriental Medicine, Dong-eui University from November 2006 to September 2010. We classified them into two group. One was taking Sasang Constitution herb medicine patients group, the other was non taking group. For Sasang Constitution Diagnosis, they all have done SSCQ-P questionnaire. and a Sasang Constitution specialist diagnosed constitution. According to reactions after taking herb medicine, the patients of taking group were confirmed their constitutions. We checked Sasang Constitution diagnostic rate from each groups'(the whole subjects, taking herb medicine patients group, non taking herb medicine patients group) discriminant function. And to find out Sasang Constitution diagnostic rate, we applied discriminant functions to each other. 3. Results and Conclusions: 1) The whole subjects' diagnostic accuracy rate was 72.07%. 2) Taking herb medicine group's diagnostic accuracy Rate was 75.08%. Non taking herb medicine group's diagnostic accuracy rate applied taking group's discriminant function was 61.60%. 3) Non taking herb medicine group's diagnostic accuracy rate was 81.06%. Taking herb medicine group's diagnostic accuracy rate applied taking group's discriminant function was 57.14%.

• Journal of Korean Society on Water Environment
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• v.34 no.6
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• pp.602-620
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• 2018

Korean benthic macroinvertebrate community from 959 sites and 14 environmental factors that could affect the biological distribution were surveyed and analyzed. The 438 taxa were divided into six groups according to TWINSPAN. Based on the environmental factor values corresponding to each taxon, the average and range of environmental factors for each biological group tended to increase or decrease in eight environmental factors (altitude, slope, current velocity, fraction of fine particles in substrates, turbidity, $BOD_5$, T-N and T-P). As a result of discriminant analysis (hit ratio: 69.6 %), environmental factors that significantly influence the distribution of each biological group were $BOD_5$, altitude, catchment area, T-N, T-P and fraction of fine particles in substrates. The discriminant functions 1 and 2 classified the existing six biological groups (clustered by TWINSPAN) into five (group 1: highland highly sensitive group; group 2: lowland sensitive group, group; 3 and 4: lowland slightly tolerant group; group 5: lowland tolerant group; group 6: lowland highly tolerant group). Most of the benthic macroinvertebrates were identified in the species level. However, a few others were identified in genus or family level, too. Even the organisms belonging to the same genus or family may prefer different environmental factors in the species level, the identification of characteristic of the habitat environment preferred by organism and species level identification of these organisms are utmost. The results of this study may be used as basic information on environmental factors which can be considered in preservation and restoration research for biodiversity.

• Journal of Preventive Medicine and Public Health
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• v.28 no.3 s.51
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• pp.640-650
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• 1995

After the introduction of National Medical Insurance in 1989, the medical demand has rapidly increased. The impact of increased medical demand was followed by an increase in the number of claims in need of review. We studied a new, fair method for reducing the number of claims reviewed. We analysed 90,583 outpatient claims submitted between September and October; claims were made for services given August of 1994. We finally suggested a screening system for claims review using a statistical method of discriminant analysis of the medical costs. The results were as follows. 1. In the cut-off group, age, days of medication, number of hospital or clinic visits, and total charge were significantly high. The cut-off rates according to the hospital-type and existence of accompanied disease were significantly different 2. According to ICD, the cut-off rate was highest in peripheral enthesopathies and allied syndromes(20.76%), lowest in acute sinusitis(0.93%). The mean charges were significantly different according to ICD and existence of cut-off. 3. We build discriminant functions by ICD with such discriminant variables as patient age, sex, existence of accompanied disease, number of hospital or clinic visits, and 9 detailed hospital or clinic charges included in claim. 4. We applied the discriminant function for screening those claims that were expected to be cut-off. The sensitivities comprised from 40% to 70%, and specificities from 70% to 95% by ICD. Acute rhinitis had highest sensitivity(100.00%) and other local infections of skin and subcutaneous tissue had highest specificity(98.45%). The expected number of cut-off was 17,762(19.61%). The total sensitivity was 49.62%, the total specificity was 82.57% and the error rate was 19.66%. We lacked economic analysis such as cost-benefit analysis. But, if the new method of screening claims using discriminant analysis were applied, the number of claims in need of review will reduce considerably.