• Animal Systematics, Evolution and Diversity
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• v.2 no.2
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• pp.1-12
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• 1986

Genetic and morphological variation among seven populations of two species of the genus Liobagrus that had been collected from six separate river systems in Korea were analyzed by means of starch electrophoreiss and discriminant function analysis . The degree of genic variation among three population of L.andersoni was P=21.3%, H=0.068 , and that of four population of L.mediadiposalis was P=16.3%, H=0.560. Rogers' gentic similarity coefficient (S) of L.andersoni and L.mediadiposalis were S=0.592 , S=0.675 respectively. In morphometric characters of L. andersoni, the population from Kum River was distinctly different from other conspecific populations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1D
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• pp.45-51
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• 2010

Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Korean Journal of Food Science and Technology
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• v.43 no.4
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• pp.419-425
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• 2011

Changes in the flavor of muskmelons stored at different temperatures were examined to judge aroma patterns during storage. A mass-spectrometry based electric nose was used to distinguish the subtle differences in the muskmelon's volatile compounds. The data were used for a discriminant function analysis (DFA), and then the partial least square algorithm was used for a quantitative analysis. Volatile components in the muskmelons increased with storage, and the first discriminant function score (DF1: $r^2$=99.88%, F=3072.5) moved from a positive position to a negative position as the storage period increased. The proper point of maturity was anticipated as the $28^{th}$ day at 0$^{\circ}C$, $21^{st}C$ day at 4 and 7$^{\circ}C$, and $14^{th}$ day at 10$^{\circ}C$. Also, using the DF1 score we could predict the general tendency (vitamin C, stem moisture, acidity) of the muskmelons. The electronic nose revealed that the major volatile compounds that changed during storage of the melons were ethyl ethyl acetate, butyl acetate, nonanol, dodecanoic acid, hexadecanoic acid and tricosane. The amount of volatile compounds detected increased during storage.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.163-171
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• 2016

We investigated the intensity and pattern of the scent produced by diploid and tetraploid Cymbidium flowers, using an electronic nose with 6 metal oxide sensors (MOS). The MOS responses were evaluated by principal component analysis, discriminant function analysis, and sensor data. These analyses revealed that tetraploid flowers had a stronger scent than diploid flowers in Cymbidium Golden Elf 'Sundust'. Furthermore, among the different flower parts-column, lip, and petals-the column produced the strongest scent. There was no significant difference between the flowering periods of diploid and tetraploid potted Cymbidium Golden Elf 'Sundust' and Cymbidium Elma 'Orient Toyo' grown in a greenhouse. Moreover, there were no significant differences between the number of flowers per flower stem and the length of flower stems on the diploid and tetraploid plants of these two Cymbidium cultivars. This study provides potentially useful information for the breeding of polyploidy Cymbidium in the floriculture industry.

• Natural Product Sciences
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• v.24 no.3
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• pp.164-170
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• 2018

Rapid geographical classification of Bupleuri Radix is important in quality control. In this study, near infrared spectroscopy (NIRS) combined with supervised pattern recognition was attempted to classify Bupleuri Radix according to geographical origins. Three supervised pattern recognitions methods, partial least square discriminant analysis (PLS-DA), quadratic discriminant analysis (QDA) and radial basis function support vector machine (RBF-SVM), were performed to establish the classification models. The QDA and RBF-SVM models were performed based on principal component analysis (PCA). The number of principal components (PCs) was optimized by cross-validation in the model. The results showed that the performance of the QDA model is the optimum among the three models. The optimized QDA model was obtained when 7 PCs were used; the classification rates of the QDA model in the training and test sets are 97.8% and 95.2% respectively. The overall results showed that NIRS combined with supervised pattern recognition could be applied to classify Bupleuri Radix according to geographical origin.

• Journal of Families and Better Life
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• v.6 no.1
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• pp.71-93
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• 1988

The purpose of this study is to investigate the realities of the husband's violence, to develop a scale to identify women who are victims of wife abuse and to provide evidence of the scale's validity. The Instrument entitled the Wife Abuse Inventory (WAI) and conflict Tactics Scale(CTS), are administered to 511 women who lives in Taegu area. The main results are as follows; 1) The CTS analysis shows the 42.5% of the sampled house wives are suffered minor violence and 9/0% are suffered violence form husband. 2) The WAI is factor analyzed to examine factor components within the scale. An examination of the rotated solutions suggested that WAI is composed 10 factors. These factor is labeled men's conception of supremency and aggression propensity, communication, economic difficulties and frustration, social activities, jealousy, children rearing, intimacy, family relationships in laws , affection, difference of culture. 3) an analysis of variance show the group mean score of the violence group and the mean score of the non-violence group on the WAI to be significantly different(P<.001). A discriminant analysis produce a significant discriminant function (P<.001). Using WAI scores as the discriminating variable, 81,15% of the violence and non-violence subjects are classified into their appropriate groups. This finding indicates that the WAI is a reliable device for screening violence and nonviolence group.

• Journal of Animal Science and Technology
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• v.47 no.1
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• pp.133-140
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• 2005

The aim of this study was to divide vocalizations of sows into general(GVs) and estrus-related vocalizations( EVs) and to find out their phonetic characteristics. Ten sows(Landrace) were recorded using digital video recorders twice daily(06: 00 - 08 : 00h and 17: 00 - 19 : 00h) during the anestrus and estrus periods. The GVs and EVs were divided based on the shapes of spectrum and spectrogram. The GVs and EVs were identified as 5 and 3 types, respectively. Pitch, formant I, formant 2, and formant 3 between GVs and EVs were not significantly different(P> 0.05), whereas intensity(P < 0.001), duration(P < 0.05), and formant 4(P < 0.01) were significantly different. Three parameter groups(Group I : Formant vector alone, Group II: Formant veetor+ parameters from time signal, Group III: Formant vector+parameters from time signal-parameters eliminated by stepwise discriminant analysis backward) were compared by discriminant function analysis. The classification system adopted in the Group II represented the higher discrimination rate than those in other groups(Group I : 76.1 0/0, Group II : 88.1 0/0, Group Ill: 87.3 %). These results suggest that EVs are present and intensity, formant 2, and formant 4 are available parameters for discrimination of EVs in sows.

• Journal of Sasang Constitutional Medicine
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• v.21 no.1
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• pp.99-126
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• 2009

1. Objective TS-QSCD (The Two-Step Questionnaire for the Sasang Constitution Diagnosis) is one of the self-reporting Sasang-Constitutional diagnosis questionnaires and one constituted by a two-step discriminant function. The process of TS-QSCD is as follows. During the first step, the testers are classified into two groups: the Yangin(陽人) group and Eumin(陰人) group. Following this, the Yangin group is divided into the Soyangin group and Taeyangin group likewise the Eumin group is divided into the Taeumin group and Soeumin group. This questionnaire has the merits of an ordinary questionnaire with four discriminant functions and a decision tree method. The purpose of this study is to evaluate and standardize TS-QSCD 2. Materials and Methods TS-QSCD was administered to 352 random informants who were examined by professionals. Reliability was tested by inter-item consistency using cronbach's ${\alpha}$, and validity was tested by a two step discriminant function. Cross tabulation Analysis was also used to look into the distribution of responses among the groups. 3. Result 1) The reliability of TS-QSCD was relatively valid. The internal consistency of TS-QSCD (AB) was cronbach's ${\alpha}$= 0.815, and TS-QSCD (AC) was cronbach's ${\alpha}$= 0.832. 2) There was a significant difference in points between Eumin group teens and other age groups, between those of Soeumin teens and other age groups. 3) TS-QSCD corresponded with the real Sasang constitution at the rate of 65.0%. When using 61 questions and four discriminant function as with ordinary methods, TS-QSCD corresponded with the real Sasang constitution at the rate of 74.9%. 4. Conclusion 1) TS-QSCD that complements the merits of existing questionnaires is effective in diagnosing Sasang constitutions. 2) Deleting duplicate questions is thought to be one of the reasons for the decreased validity rate. 3) The lower the validity of the first step, the more we should build up at each second steps a way to rescue the groups which were assigned wrongly during the first steps. 4) This standardization of TS-QSCD would be helpful in making a program for diagnosing the Sasang Constitution

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.133-142
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• 2002

This is a fundamental study to develop a sensor to detect weeds in paddy field using machine vision adopted spectralphotometric technique in order to use the sensor to spread herbicide selectively. A set of spectral reflectance data was collected from dry and wet soil and leaves of rice and 6 kinds of weed to select desirable wavelengths to classify soil, rice and weeds. Stepwise variable selection method of discriminant analysis was applied to the data set and wavelengths of 680 and 802 m were selected to distinguish plants (including rice and weeds) from dry and wet soil, respectively. And wavelengths of 580 and 680 nm were selected to classify rice and weeds by the same method. Validity of the wavelengths to distinguish the plants from soil was tested by cross-validation test with built discriminant function to prove that all of soil and plants were classified correctly without any failure. Validity of the wavelengths for classification of rice and weeds was tested by the same method and the test resulted that 98% of rice and 83% of weeds were classified correctly. Feasibility of CCD color camera to detect weeds in paddy field was tested with the spectral reflectance data by the same statistical method as above. Central wavelengths of RGB frame of color camera were tried as tile effective wavelengths to distingush plants from soil and weeds from plants. The trial resulted that 100% and 94% of plants in dry soil and wet soil, respectively, were classified correctly by the central wavelength or R frame only, and 95% of rice and 85% of weeds were classified correctly by the central wavelengths of RGB frames. As a result, it was concluded that CCD color camera has good potential to be used to detect weeds in paddy field.