• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.434-440
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• 2024

SIZE KOREA updates body measurement data every five years, providing essential information for the fashion industry. This anthropometric data is widely used to diagnose consumer body shapes and develop optimal clothing sizes. Artificial intelligence, particularly machine learning, excels in predicting such body shape classifications. This study seeks to enhance the suitability of clothing design by applying the new analytical methodology of machine learning techniques to better capture and classify the unique body shapes of Korean women. In this study, machine learning techniques such as K-means clustering, Silhouette analysis, and Decision Tree analysis were used to classify the lower body shapes of Korean women in their twenties and identify standard body shapes useful for slacks design. The results showed that the lower body of the age group could be classified into three categories: 'small stature' (the majority), 'tall with an average lower body volume,' and 'medium height with a fuller lower body' (the smallest share). The three-cluster approach is validated through Silhouette analysis, which minimizes misclassification. Decision Tree analysis then further defines the criteria for these clusters, highlighting waist height and hip depth as the most significant factors, achieving a classification accuracy of 90.6%. While this study is not directly related to Robotic Process Automation, its detailed analysis of body shapes for slacks patterns can aid RPA in clothing production. Future research should continue integrating machine learning in human body and fashion design studies.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.3
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• pp.199-213
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• 2020

Grain size and shape are the two important components contributing to rice yield and quality. To analyze traits related to grain-shape, a total of 272 varieties derived from japonica, japonica black and Tongil-type rice accession in Korea were evaluated in this study. The traits, grain length (GL), grain width (GW), grain thickness (GT), length to width ratio (RLW), and 1000-grain weight (TGW) were measured and replicated 10 times. Genes (GW2, GS3, qGL3, qSW5, GS5, TGW6, GW7, and GW8) related to grain-shape were validated in the accessions using specific DNA marker sets. K-mean clustering of the accession based on phenotypic data revealed three groups: group 1 was classified by GW and GT and included most of japonica type, group 2 was classified by RLW and GL reached a medium size and possessed a half spindle-shaped type, and group 3 was classified by TGW, reached a long size and possessed a semi-round shape. In validation tests using the marker sets, both gw2 and tgw6 were validated in less than 1% of the tested accessions and two allelic types, qgl3 and gw8, were only verified in Tongil-type accessions. For GW8 and GW2, any different amplicons were not amplified in any japonica or Tongil-type accessions, respectively. In order to suggest the representative grain-shape gene combinations for each ecotype, the allelic combinations were evaluated by PCR analysis. Cj1 and 2 in japonica (Cj1-7), Cj_b1 and 2 in japonica-black (Cj_b1-3), and CT3 in Tongil-type (CT1-13) turned out to be the dominant combination in each ecotype, respectively. In addition, the results revealed that introgression of four genes (gw2, gs3, qSW5, and GS5) would expand the diversity of grain shape in Korean japonica varieties. The gene combinations information could be utilized practically to understand or enhance grain shape in japonica rice breeding program.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.111-128
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• 2020

This study presents a possibility of intensification of fine dust mass concentration due to the complex urban structure using data mining technique and clustering analysis. The data mining technique showed no significant correlation between fine dust concentration and regional-use public urban data over Seoul. However, clustering analysis based on nationwide-use public data showed that building heights (floors) have a strong correlation particularly with PM₁₀. The modeling analyses using the single canopy model and the micro-atmospheric modeling program (ENVI-Met. 4) conducted that the controlled atmospheric convection in urban area leaded to the congested flow pattern depending on the building along the distribution and height. The complex structure of urban building controls convective activity resulted in stagnation condition and fine dust increase near the surface. Consequently, the residual effect through the changes in the thermal environment caused by the shape and structure of the urban buildings must be considered in the fine dust distribution. It is notable that the atmospheric congestion may be misidentified as an important implications for providing information about the residual probability of fine dust mass concentration in the complex urban area.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.337-349
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• 2020

In this study, Helikite, Low Altitude Remote Sensing (LARS) platform, was used to acquire coastal images. In the obtained image, the land and water masses were divided using four types of region clustering algorithms, and then waterline was extracted using edge detection. Quantitative comparisons were not possible due to the lack of in-situ waterline data. But, based on the image of the infrared band where water masses and land are relatively clear, the waterlines extracted by each algorithm were compared. As a result, it was found that each algorithm differed significantly in the part where the distinction between water masses and land was ambiguous. This is considered to be a difference in the process of selecting the threshold value of the digital number that each algorithm uses to distinguish the regions. The extraction of waterlines through various algorithms is expected to be used in conjunction with a Low Altitude Remote Sensing system that can be continuously monitored in the future to explain the rapid changes in coastal shape through several years of long-term data from fixed areas.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.

• Transactions of Materials Processing
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• v.28 no.6
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• pp.361-367
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• 2019

Microstructure evolution and tensile properties of Al-8mass%Mg alloy casting billet by biaxial alternative forging were investigated in this study. An alternative forging system tailored in this study was used to allow continuous strain accumulations on the alloy workpiece. A finite element (FE) simulation results revealed that the strain was mainly concentrated in the core and that the shear bands developed into a form with an X shape in the cross-section of workpiece after the alternative forging using octangular rod shaped dies. With increasing the forging passes, it was observed that the Al-8mass%Mg alloy workpieces were significantly deformed, and cracks began to form and propagate on the both ends of the forged workpieces after five passes at room temperature. In as-forged microstructures taken by microscopes, twins, clustering of dislocations, and fine subgrains were found. Tensile strengths of the forged specimens showed significant increases depending on the number of forging passes, and a trade-off relationship was observed between the elongation and strength. At room temperature and 100℃ the workpieces showed similar behaviors in microstructural evolution and tensile properties depending on forging passes, while the increase range in strength was reduced at 200℃.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.44-51
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• 2009

Text understand in natural images has become an active research field in the past few decades. In this paper, we present an automatic recognition system in Korean signboards with a complex background. The proposed algorithm includes detection, binarization and extraction of text for the recognition of shop names. First, we utilize an elaborate detection algorithm to detect possible text region based on edge histogram of vertical and horizontal direction. And detected text region is segmented by clustering method. Second, the text is divided into individual characters based on connected components whose center of mass lie below the center line, which are recognized by using a minimum distance classifier. A shape-based statistical feature is adopted, which is adequate for Korean character recognition. The system has been implemented in a mobile phone and is demonstrated to show acceptable performance.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.120-129
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• 2016

This study aimed to develop an optimal sizing system and a draping pattern for hip protector based on an analysis of anthropometric characteristics of Korean older women. A hip protector is a specialized form of pants or underwear containing pads along the outside of each hip. The 3D body scan data of Korean older women were analyzed to identify their anthropometric characteristics and a four-size system with 93% of population accommodation was developed by clustering analysis based on key dimensions derived from factor analysis. The sizing system consists of small/short, large/short, small/tall, and large/tall. A 3D physical model and hip pads were fabricated; then, a hip protector was draped on the 3D model and hip pads. The sizing system of hip protector was analyzed in terms of size and shape and a draping pattern was compared on back center, back side, front side, front center and pad. Lastly, the pattern deformation and clothing pressure were analyzed using the virtual clothing system CLO. Virtual system have disadvantage of not to suggest the objective value. In the future research the wearing comfort and impact absorption of the hip protector needs to be tested and then a hip protector design will be finalized by considering the hip protector's size, material, comfort testing results, aesthetic appeal, protection effectiveness, and practical utility of everyday use.