• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1487-1499
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• 2007

In this study, photographs of 600 Korean females aged from 20 to 50years old were indirectly measured in Venus face 2D program. The measurements were analyzed by statistical methods. The purpose of this study was to differentiate the facial types of adult women for the beauty industry. As a result of factor analysis, 6 factors were selected the key factors of facial shape: head height(factor 1), head width(factor 2), side face width(factor 3), head width and circumference(factor 4), face length(factor 5), and side face width(factor 6). We categorized facial type into 5 groups with the previous 6 factor. 5 types were most common facial shapes: Oblong face(type 1), Square face(type 2), Oval face(type 3), Round face(type 4), Triangle face(type 5). The results of facial type analysis were showed that Round face(26.6%), Triangle face(25.3%), Oval face(22.3%), Square face(20.0%), Oblong face(5.7%).

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.45-50
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• 2007

In this paper, the FEM(Finite Element Method) has been applied to understand the geometrical characteristics and to analyze the stress of a helical gear. The helical gear is simulated and analyzed by adding many thin spur gear with helix angles and twist angles. Helical gears with different helix angle and face width have been studied. The results show that the root fillet stress is increased proportionally to helix angle and face width. Namely, as the face width increases, root fillet stress decreases, and as helix angle gets bigger, root fillet stress increases.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.521-524
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• 2003

In this paper, we propose a face region extraction algorithm using color information and projection. After the extraction of face candidate image using adaptive color information, we project it into vertical direction to estimate the width of the face. Then the redundant parts of the face are efficiently removed by using the estimated face width. And the width information of the face is used at the horizontal projection step to extract the height of the face, and non-face region such as the neck and some background regions, which are represented as the similar skin color, effectively eliminated. From the experiment results for the various images, the proposed algorithm shows more accurate results than the conventional algorithm.

• Journal of Fashion Business
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• v.8 no.1
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• pp.76-90
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• 2004

The purpose of this study was to classify women's face types and to analyze the measurement of face types. For study, 180 adult women(aged between 20 and 29) in Pusan and Ulsan area was sampled to be measured for facial types. Data were analyzed by Frequencies, Means, Duncan's Multiple Range Test, Distinction analysis. The major results were as followed. Women's face types were classified by 6 types and there were round shape(29.4%), oblong shape(18.9%), inverted triangle shape(16.1%), square shape(13.9%), egg shape(11.7%), diamond shape(10.0%) in the subject. Phyiognomic facial height was 182.38mm, the upper face length was 59.82mm, the middle face length 60.82mm, the lower face length 61.76mm, and the index of face length to face breadth was 1.35. The face width was 134.90mm, interocular distance 34.75mm, the nose width 33.93mm, and mouth width was 43.87mm. And also, differences from those measurements like forehead breadth, face length/bizygion breadth, forehead slopper, bigonion breadth, bignathion breadth, bignathion slopper.

• The Research Journal of the Costume Culture
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• v.12 no.5
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• pp.757-768
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• 2004

This study was aimed to provide the fundamental and various measurement data of the head and face for Korean children. Two hundred sixty nine female children, aged nine to twelve years, participated for this study. The 28 regions on the head and face of the subjects were directly measured by the expert experimenters. Factor analysis, cluster analysis, GLM analysis and Tukey HSD test were performed' using these data. Through factor analysis, six factors were extracted upon factor scores and those factors comprised 71.42% for the total variances. Four clusters as their head and face shape were categorized using six factor scores by cluster analysis. Type 1 was characterized by the shorter head & face length and width and the lowest position from forehead to nose. Type 2 had the longer head & face length and width and the highest ear position and the largest mouse width. Type 3 was characterized by the longest and head & face type and the widest head & face girth. Type 4 was characterized by shortest head & face length the lower ear and lips position.

• The korean journal of orthodontics
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• v.13 no.1
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• pp.105-114
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• 1983

the author studied the corelativity between the head and face and the maxillary arch in Korean. This study was undertaker in 336 persons at age from 9 to 19 years who had normal occlusion by means of angle's classification. The following results were obtained. 1. The corelative coefficient between the Height of Head and Face (H.H.F.) and the Arch Length (A.L.) was 0.203-0.543, 2. The corelative coefficient between the Bizygomatic width (Z.W.) and the Bicanine width (C-C) was 0.203-0.543. 3. The corelative coefficient between the Bizygomatic width (Z.W.) and the Bimolar width (M-M) was 0.206-0.600. 4. The corelative coefficient between the Face shape (Index a) and Maxillaxy arch shape (In-dex c) was 0.232-0.404. 5. The corelative coefficient between the Face shape (Index a) and Maxillary arch shape (Index d) was 0.221-0.401. 6. There was no corelativity between the Anterior-posterior width of head (A.P.W.) and Arch Length A.L.), Head shape (Index b) and Maxillary arch shape (Index c, Index d).

• The Research Journal of the Costume Culture
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• v.12 no.6 s.53
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• pp.933-944
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• 2004

This study was aimed to provide the fundamental and various measurement data of the head and face for male children. Two hundred forty one male children, aged nine to twelve years, participated for this study. The 31 regions on the head and face of the subjects were directly measured by the expert experimenters. Through factor analysis, the six factors were extracted upon factor scores and those factors comprised $67.47\%$ for the total variances. The first factor was described the general height elements for the mouth and the environs of the mouth. The second factor was described the general height around the nose, forehead and eyes. The third factor was described the height of the ear environs. The forth factor contained the length around the sinciput to the occiput, the head thick and the head circumstance. The fifth factor was described the general width of the outer head and the corner of the eyes. The last factor contained the depth of the mouth and nose. Four clusters as their head and face shape were categorized using six factor scores by cluster analysis. Type 1 was characterized by the shortest head and face width, surface length and girth, and the shorter length of head, but the highest position of chin, philtrum, upper lip. Type 2 was characterized by the shortest head and face length and thickness, and the lowest position of the forehead, eye, nose, mouth, ear environs, but that had wider width of head and face. Type 3 was characterized by the longest and the widest head and face type, and the highest position of the mouth. Type 4 was characterized by longer length of head and face, and the widest head girth and largest head thickness, and the highest position of the forehead, eye, nose environs. And this type had the widest width of nose and mouth, and the longest head surface length.

• Archives of Plastic Surgery
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• v.35 no.5
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• pp.514-520
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• 2008

Purpose: Many attempts have been made to describe ideal facial proportions for over two thousands year and constantly lasted till now. Dr. Marquardt has derived supposedly ideal facial proportions from the facial golden mask using golden ratio of 1 : 1.618. On the other hand, facial reducing surgeries such as mandible angle reduction are popularized in Asia because the width of mid and lower face of Korean is recognized to be wider. The purpose is to analyze characters of Korean university students' faces in horizontal plane and establish the objective data for facial width distributions and clinical applications. Methods: We applied the facial golden mask to the photographs in 1000 cases, compared the width of mid and lower face between the facial golden mask and Korean university students' faces. And we first calculated the horizontal ratio(HR) of middle and lower face each for using comparative scale of width, facial golden mask. We divided 1,000 cases into 3 groups by degrees of HR and analyzed data of HR on each groups. Using calculated horizontal ratio, we newly invented the cumulative frequency of distribution graphs in Korean university students' faces. Results: Mean data of HR were over 1.0 in all groups, which means that Korean university students' faces are typically wider than facial golden mask in horizontal planes. And this study was statistically significant(p- value < 0.05). Clinically using the cumulative frequency distributions of Korean university students' face width, we can easily explain changes of facial width to patient after facial reducing surgery and describe the changes into objective data. Conclusion: This study concludes thatKorean university students' faces are wider than facial golden mask is significantly true and the cumulative frequency of distribution graphs are expected to be widely used for comparison of results in facial reducing surgery.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.6
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• pp.930-940
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• 2019

This study analyzes the facial data required for sheet design in order to pursue the facial compatibility of disposable sheets used in facial mask products that are increasing in popularity as self-care methods. The subjects of the study were 23 facial measurements of 1,001 women in their 20s to 60s from Size Korea's 6th 3D data. Through factor analysis, sheet-related facial measurements were collected into six factors included in the vertical length of each part of the face: length of face surface from the ear to each part of the face, width of eyes, nose, lips, length of nose, vertical length of lower face, width of the head and width of chin. Three sheet face types were classified using six factor scores as variables, and the characteristics of each type differed according to age group. As a result of the discriminant analysis to identify the dimension items that classify the three cluster types, 12 contributing items were extracted out of 23 items. This study provides useful information and data for further studies of products requiring facial fitness.

• Korean Journal of Agricultural Science
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• v.45 no.2
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• pp.283-289
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• 2018

Agricultural gear reducers are used in a variety of agricultural machinery designs such as in agricultural tractors and transport cars, and even greenhouses. For greenhouses, a gear reducer is used to control windows on the side and the roof. Gear reducers for agricultural applications are designed using the empirical method because of the lack of a standard for experimentation. Simulation is necessary for the optimal design of an agricultural gear reducer. There are many advantages to this optimization such as low-cost maintenance, reduced size, and weight. In this study, bending and contact safety factor simulation for the gear reducer of a greenhouse was conducted by decreasing the face widths of helical gear shaft 2 and shaft 3 from 30.8 and 30 mm, respectively, at an interval of 4 mm. The bending and contact safety factors were calculated using AGMA standard. Simulation results showed that bending and contact safety factors decreased rapidly when the face width of the helical gear on shaft 2 was 30 mm and the face width of helical gear on shaft 3 decreased from 30.8 mm to 26.8 mm, suggesting that it would be safe to reduce the face width of the helical gear on shaft 3 to 26.8 mm. The reduction of the face width also reduced the weight of the agricultural gear. This study suggests that the agricultural gear reducer safety factor decreases as the face width decreases.