• Journal of Information Technology Services
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• v.14 no.4
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• pp.159-169
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• 2015

Customer reviews are one of the important sources for purchase decision makings in online stores. Online stores have tried to provide useful reviews in product pages to customers. To assess the usefulness of customer reviews before other users have voted enough on the reviews, diverse aspects of reviews were utilized in prevous studies. Style and semantic information were utilized in many studies. This study aims to test diverse alogrithms and datasets for identifying a proper classification method and threshold to classify useful reviews. In particular, most researches utilized ratio type helpfulness index as Amazon.com used. However, there is another type of usefulness index utilized in TripAdviser.com or Yelp.com, count type helpfulness index. There was no proper threshold to classify useful reviews yet for count type helpfulness index. This study used reivews and their usefulness votes on restaurnats from Yelp.com to devise diverse datasets and applied text mining approaches to classify useful reviews. Random Forest, SVM, and GLMNET showed the greater values of accuracy than other approaches.

• Journal of the Korean Society of Costume
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• v.53 no.6
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• pp.145-159
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• 2003

The purpose of this study was to classify body type for ready-to-wear sizes. The subjects were 300 women ages of 18-24. they were measured direct anthropometry. The body types for sizing system were divided by Rohrer Index. KS drop value and ISO drop value. The results of this study were as follows. 1. By adapting the Rohrer Index. we classify 3 types from anthropometric measurements. The thin type covered 39.3%, the standard type 51.0% and the obesity type 18.7%. The characteristics of clusters were as follows. Thin type was characterized by tall. slender type and slim. The standard type was characterized by middle sized. The obesity type was characterized by short. fat type. and large bust. 2. By adapting the KS system drop value. we classify 3 types from anthropometric measurements. The H type(drop 0) covered 25.6%. the N type(drop 6) 65.2% and the A type(drop 12) 9.2%. Type H was slightly tall large bust. and curved from waist to hip. Type A was slightly thin. large hip and smaller bust than type N. Principal factor components were bust size. The height could be divided into three groups. The Petite(l50cm) covered 5.5%. the Regular(l60cm) 64.7% and the Tall(l70cm) 29.8%. Through the crosstab of height and body type. we extracted regular height by N type 46.2% the largest cell. The body type was the higher order of N type. H type and A type. The tall was the higher order of Regular. Tall and Petite. 3. By adapting the ISO system drop value. we classify 3 types from anthropometric measurements. The H type(drop 0) covered 15.0%. the M type(drop 6) 41.0% and the A type(drop 12) 44.0%. Type H was slightly short. slightly fat and large bust. Type A was slightly tall. slight thin than type M. The height could be divided into three groups. We adjust the height section after allow for height distribution. The Short(152cm) covered 12.8%. the Regular(160cm) 66.9% and the Long(168cm) 20.3%. Through the crosstab of height and body type, we extracted regular height by M type 29.3% the largest cell. The body type was the higher order of M type, A type and H type. The tall was the higher order of Regular, Long and short.

• Atmosphere
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• v.23 no.1
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• pp.103-112
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• 2013

In this study, we developed a fog classification algorithm to classify fog type based on fog generation mechanism. For the analysis period of 1986-2005, 15,748 fog events had been reported from the 40 observational sites in South Korea. Thus, practically, it is almost impossible to individually classify the fog type of the whole fog events occurred in South Korea manually. In this study, the characteristics of fog during the research period were investigated and the fog classification flowchart were developed base on the analysis, and the fog classification algorithm was applied for the classification of fogs occurred at the observational sites. Finally, the classified fog-type and hindcasted fog occurance results obtained from the flowchart were evaluated for verification.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.3
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• pp.345-352
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• 2000

The purpose of this study was to classify lower body types of elementary school girls. The subjects for anthropometric study were 368 girls aged from 10 to 11. Factor analysis, cluster analysis, discriminant analysis, and analysis of variance were performed for statistical analysis of the data. Four lower body construction factors were extracted by the factor analysis of antropometric measurements. The factors extracted were lower body fatness factor, lower body height factor, lower body length from the waist to the crotch factor, and lower body configuration factor. On the basis of the cluster analysis, three different lower body types were categorized. Type 1 was short and small sized type and 42.4% of subjects belonged under this type. Type 2 was tall and fat type and 22.3% of subjects belonged under this type. Type 3 was the most similar to the average type having the largest waist-hip drop value and 35.3% of subjects belonged under this type. Discriminant analysis showed 7 discriminant factors that can classify the children's lower body type were Rohrer's index, height, fibulae length, waist girth, ilio cristale girth, trochanter girth, and weight.

• Journal of The Korean Association For Science Education
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• v.33 no.3
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• pp.679-693
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• 2013

The purpose of this study is to develop an inventory to classify task commitment types of science learning and to classify highschool students' task commitment types. Firstly, inventory questions were designed following the literature analysis on the task commitment components which involve self confidence, high goal setting, and focused attention. Prototype inventory underwent the content validity test, pilot test, and reliability test. Through these steps, final inventory was input to 462 high school students and underwent the factor analysis and cluster analysis. Factor analysis confirmed three components of task commitment as the three factors of inventory questions. In order to find how many clusters exist, factors of developed inventory became new variables. Each factor's factor mean was calculated and served as the new variable of the cluster analysis. Cluster analysis extracted five clusters as task commitment types. The 5 clusters were suggested by the agglomarative schedule and dendrogram gained from a hierarchical cluster analysis with the setting of the Ward algorithm and Squared Euclidean distance. Based on the factor mean score, traits of each cluster could be drawn out. Inventory developed by this study is expected to be used to identify student commitment types and assess the effectiveness of task commitment enhancement programs.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.1-19
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• 1993

A simple bispectral threshold technique which reflects the temporal and spatial characteristics of the analysis area has been developed to classify the cloud type and estimate the cloud cover from GMS/S-VISSR(Stretched Visible and Infrared Spin Scan Radiometer) imagery. In this research, we divided the analysis area into land and sea to consider their different optical properties and used the same time observation data to exclude the solar zenith angle effects included in the raw data. Statistical clear sky radiance(CSRs) was constructed using maximum brightness temperature and minimum albedo from the S-VISSR imagery data during consecutive two weeks. The CSR used in the cloud anaysis was updated on the daily basis by using CSRs, the standard deviation of CSRs and present raw data to reflect the daily variation of temperature. Thresholds were applied to classify the cloud type and estimate the cloud cover from GMS/S-VISST imagery. We used a different thresholds according to the earth surface type and the thresholds were enough to resolve the spatial variation of brightness temperature and the noise in raw data. To classify the ambiguous pixels, we used the time series of 2-D histogram and local standard deviation, and the results showed a little improvements. Visual comparisons among the present research results, KMA's manual analysis and observed sea level charts showed a good agreement in quality.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.4
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• pp.165-179
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• 2019

This study used 3D body scan data to classify body shapes according to the torso shape of adult males aged 20-75 years. This data will be provided so that the apparel industry can make apparel products corresponding to body characteristics by age. The study used 1,796 adult males between the ages of 20 and 75 and the 3D body shape data of the '5th Research on National Standard Anthropometry'. For data analysis, the program SPSSWIN Ver. 17.0 was used to calculate the mean and frequency allowing for a factor analysis, cluster analysis, analysis of variance, and Duncan test. To classify body shape according to the torso shape of adult males, this study considered nine factors: 'horizontal size of torso,' 'vertical size of body,' 'curve of torso and waist-abdomen flatness ratio,' 'length of torso,' 'shape of neck area,' 'degree of lateral curve,' 'difference between front and back interscye length,' 'shoulder armscye shape,' and 'chest flatness ratio.' Based on the results of the factor analysis, the torso shapes of adult males were classified into five types. Type 1 is "upright body with flat, curvy shape", Type 2 is "curve sway back body type", Type 3 is "flat, abdominally obese body", Type 4 is "obese, crooked body" and Type 5 is "thick sway front body type." named.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.33.3-33.3
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• 2019

Automatic, yet reliable methods to find and classify barred galaxies are going to be more important in the era of large galaxy surveys. Here, we introduce a new approach to classify barred galaxies by analyzing the butterfly pattern that Buta & Block (2001) reported as a bar signature on the potential map. We make it easy to find the pattern by moving the ratio map from a Cartesian coordinate to a polar coordinate. Our volume-limited sample consists of 1698 spiral galaxies brighter than Mr = -15.2 with z < 0.01 from the Sloan Digital Sky Survey/DR7 visually classified by Ann et al. (2015). We compared the results of the classification obtained by four different methods: visual inspection, ellipse fitting, Fourier analysis, and our new method. We obtain, for the same sample, different bar fractions of 63%, 48%, 36%, and 56% by visual inspection, ellipse fitting, Fourier analysis, and our new approach, respectively. Although automatic classifications detect visually determined, strongly barred galaxies with the concordance of 74% to 86%, automatically selected barred galaxies contain different amount of weak bars. We find a different dependence of bar fraction on the Hubble type for strong and weak bars: SBs are preponderant in early-type spirals, whereas SABs are in late-type spirals. Moreover, the ellipse fitting method often misses strongly barred galaxies in the bulge-dominated galaxies. These explain why previous works showed the contradictory dependence of the bar fraction on the host galaxy properties. Our new method has the highest agreement with visual inspection in terms of the individual classification and the overall bar fraction. In addition, we find another signature on the ratio map to classify barred galaxies into new two classes that are probably related to the age of the bar.

• Kyungpook Mathematical Journal
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• v.60 no.4
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• pp.821-830
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• 2020

The object of the present paper is to classify a special type of spacetime, called Lorentzian para-Sasakian type spacetime (4-dimensional LP-Sasakian manifold with a coefficient α) satisfying certain curvature conditions.

• Journal of the Korean Home Economics Association
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• v.41 no.5
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• pp.89-97
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• 2003

Fitness of clothes becomes a major concern in apparel industry. But high-school boys had difficulties to buy ready-made clothes of good fit. To solve this problem, it is necessary to classify boys' upper body into several kinds of somatotypes. The purpose of this study was to classify upper body types of high school boys based on the analysis of their upper body types. The subjects for anthropometric measurement were 99 high school boys of 16 to 18 year-old. The result of factor analysis indicated that 5 factors were extracted from anthropometric measurements through analysis and those factors comprise 68.44% of total variance. 3 clusters were categorized using 5 factor scores by cluster analysis. Type 1 was taller than other types and was bending somatotype. Type 2 was straight somatotype and had average size. Type 3 was characterized by short and small figure and had bending somatotype.