• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.15-17
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• 2022

In order to minimize surplus parts in ball bearing selective assembly systems, it is necessary to optimize the selection probability by grasping the dimensional distribution of each part. But the use of a complex system causes delays in the production process. In this paper, we propose cluster priority selection algorithm that can quickly and simply determine the selection priority in ball bearing selective assembly system. In addition, we assume the simulated situation with the data collected in the actual ball bearing selective assembly process, and evaluate the incidence of surplus part and runtime by simulating the cluster priority selection algorithm and the exiting algorithm. As a result of the simulation, the cluster priority selection algorithm generated 83.8% less surplus parts, and 39.7% less runtime than the existing algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.164-170
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• 2023

The purpose of this study is to analyze the big data of Adidas brand participating in the Qatar World Cup in 2022 as a FIFA partner to understand useful information, semantic connection and context from unstructured data. Therefore, this study collected big data generated during the World Cup from Adidas participating in sponsorship as a FIFA partner for the 2022 Qatar World Cup and collected data from major portal sites to understand its meaning. According to text mining analysis, 'Adidas' was used the most 3,340 times based on the frequency of keyword appearance, followed by 'World Cup', 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'Qatar', 'FIFA', 'Korea', and 'Uniform'. In addition, the TF-IDF rankings were 'Qatar World Cup', 'Soccer', 'Lionel Messi', 'World Cup', 'Uniform', 'Qatar', 'FIFA', 'Ronaldo', 'Korea', and 'Nike'. As a result of semantic network analysis and CONCOR analysis, four groups were formed. First, Cluster A named it 'Qatar World Cup Sponsor' as words such as 'Adidas', 'Nike', 'Qatar World Cup', 'Sponsor', 'Sponsor Company', 'Marketing', 'Nation', 'Launch', 'Official', 'Commemoration' and 'National Team' were formed into groups. Second, B Cluster named it 'Group stage' as words such as 'Qatar', 'Uruguay', 'FIFA' and 'group stage' were formed into groups. Third, C Cluster named it 'Winning' as words such as 'World Cup Winning', 'Champion', 'France', 'Argentina', 'Lionel Messi', 'Advertising' and 'Photograph' formed a group. Fourth, D Cluster named it 'Official Ball' as words such as 'Official Ball', 'World Cup Official Ball', 'Soccer Ball', 'All Times', 'Al Rihla', 'Public', 'Technology' was formed into groups.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.3
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• pp.254-259
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• 2013

Ball screw system is widely used as a precision mechanical linear actuator that translates rotational motion to linear motion for its high efficiency, great stiffness and long life. Recently, according to the requirements of high accuracy and stiffness, the pre-load on the ball screw which means of remove the backlash in the ball screw is usually used. Because of the preload which means the frictional resistance between the screw and nut, becomes a dominating heat source and it generates thermal deformation of ball screw which is the reason for low accuracy of the positioning decision. There are several methods to solve the problem that includes temperature control, thermal stable design and error compensation. In the past years, researchers focused on the error compensation technique for its ability to correct ball screw error effectively rather than the capabilities of careful machine design and manufacturing. Significant amounts of researches have been done to real-time error compensation. But in this paper, we developed a series of cooling methods to get thermal equilibrium in the ball screw system. So we find the optimum cooling type for improving positioning error which caused by thermal deformation in the ball screw system.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.815-827
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• 2015

This study analyzes the characteristics by age and type for middle aged and elderly women foot shapes aged 40-69 years. ANOVA, factor, and cluster analyzed middle aged and elderly women's foot shapes. The results of the study are as follows. First, higher age groups tended to have smaller foot lengths, ball/instep circumferences, circumferences, and ball heights with larger heel height values and higher degrees of gathering of toe 1 and toe 5 toward the feet reference axis. Second, foot lengths were 220 mm-240 mm and the ball circumference's size symbol in high frequency sections were distributed from E to EEEE in the 40s and 60s groups and from D to EEEE in the 50s group. Third, eight factors were extracted through the factor analyses of middle aged and elderly women's foot measurement items. Fourth, a cluster analyses classified the subjects into four types. Type 1 is a normal foot type with medium foot length and small ball circumference and type 2 is a long and flat foot type with a type with large foot length and ball circumference values as well as small ball height values. Type 3 is a thick foot type with a medium foot length, large ball circumference, large ball height and type 4 is a toe deformation foot type with medium foot length, small ball circumference, and a high degree of toe gathering toward the center.

• Journal of Powder Materials
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• v.15 no.5
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• pp.371-377
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• 2008

This paper deals with the phase analysis of $MgB_2$ bulk using spark plasma sintering process after ball milling. Mg and amorphous B powders were used as raw materials, and milled by planetary-mill for 9 hours at argon atmosphere. In order to confirm formation of $MgB_2$ phase, DTA and XRD were used. The milled powders were fabricated to $MgB_2$ bulk at the various temperatures by Spark Plasma Sintering. The fabricated $MgB_2$ bulk was evaluated with XRD, EDS, FE-SEM and PPMS. In the DTA result, reaction on formation of $MgB_2$ phase started at $340^{\circ}C$. This means that ball milling process improves reactivity on formation of $MgB_2$ phase. The $MgB_2$ MgO and FeB phases were characterized from XRD result. MgO and FeB were undesirable phases which affect formation of $MgB_2$ phase, and it's distribution could be confirmed from EDS mapping result. Spark Plasma Sintered sample for 5 min at $700^{\circ}C$ was relatively densified and it's density and transition temperature showing super conducting property were $1.87\;g/cm^3$ and 21K.

• Journal of the Korean Geosynthetics Society
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• v.9 no.1
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• pp.47-57
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• 2010

Granular soils having a large particle size have been used as a filling material in the construction of foundation, harbor, dam, and so on. Consequently, the shear behavior of this granular soil plays a key role in respect of stability of structures. For example, soil particle crushing occurring at the interface between structure and soil and/or within soil mass can cause a disturbance of ground characteristics and consequently induce issues in respect of stability of structures. In order to investigate the shear behavior according to an existence and nonexistence of particle crushing, numerical analyses were conducted by using the DEM (Discrete Element Method)-based software program PFC2D (Particle Flow Code). By dividing soil particle bonding model into crushing model and noncrushing model, total four particle bonding models were simulated and their results were compared. Noncrushing model included one ball model and clump model, and crushing model included cluster model and Lobo-crushing model. The combinations of soil particle followed the research results of Lobo-Guerrero and Vallejo (2005) which were composed of eight circles. The results showed that the friction angle was in order of clump model > cluster model > one ball model. The particle bonding model compared to one ball model and noncrushing model compared to crushing model showed higher shear strength. It was also concluded that the model suggested by Lobo-Guerrero and Vallejo (2005) is not appropriate to simulate the soil particle crushing.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.4
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• pp.293-308
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• 2012

The shear behavior at the particle/surface interface such as rock joint can determine the mechanical behavior of whole structure. Therefore, a fundamental understanding of the mechanisms governing its behavior and accurately estimation of the interface strength is essential. In this paper, PFC, a numerical analysis program of discrete element method was used to investigate the effects of the surface roughness on interface strength. The surface roughness was characterized by smooth, intermediate, and rough surface, respectively. In order to investigate the effects of particle shape and crushing on particle/surface interface behavior, one ball, clump, and cluster models were created and their results were compared. The shape of particle was characterized by circle, triangle, square, and rectangle, respectively. The results showed that as the surface roughness increases, interface strength and friction angle increase and the void ratio increases. The one ball model with smooth surface shows lower interface strength and friction angle than the clump model with irregular surface. In addition, a cluster model has less interface strength and friction angle than the clump model. The failure envelope of the cluster model shows non-linear characteristic. From these findings, it is verified that the surface roughness and particle shape effect on the particle/surface interface shear behavior.

• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.414-422
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• 2013

This study identifies the foot shapes of elderly men by classifying foot types according to the shapes of sole of foot and analyzing individual characteristics. The subjects were 269 elderly men over 60 years of age. Their right feet were measured indirectly with a 2D scanner. The anthropometric measuring items consisted of 38 items that were estimated on the right foot of each subject. The 2D scan data were analyzed by various statistical methods such as factor analysis, ANOVA and cluster analysis using the statistical program SPSS 19.0. A total of 8 factors were extracted through a factor analysis and these factors represent 77.83% of total variance. The 8 factors were: ball and lateral foot protrusion, ball gradient, medial foot protrusion, anterior and posterior foot length ratio, lateral ball length, heel size, toes breadth, and foot length, that explained 77.83% of the total variance. A total of 4 clusters (as their sole type) were categorized using 8 factor scores by cluster analysis. Type 1 was classified as H-type(toes width, foot width, heel width uniform and medial malleolus and lateral malleolus almost no protrusion). Type 2 was classified as V-type(foot width and toes width, wide and heel width narrow). Type 3 was classified as A-type(foot width and heel width, wide but toes width narrow, protruded inside). Type 4 was classified as D-type(protruded outside).

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.3
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• pp.305-320
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• 2014

This study identifies the foot shapes of elderly women by classifying foot type according to the 3D shape of the foot and 2D sole type analyzing individual characteristics. The subjects were 295 elderly women over 60 years of age who live in Gwangju. A foot scanner (K&I Technology $Nexcan^{(R)}$) was used to obtain three-dimensional shapes of feet and a flat bad scanner (HP Scanjet G2410) was used to obtain the two-dimensional shapes of soles. The anthropometric measuring items consisted of 59 items estimated on the right foot of each subject. Data were analyzed by various statistical methods such as factor analysis, ANOVA and cluster analysis using the SPSS 19.0 statistical program. To classify the side type of elderly women's feet, three-dimensional measurement data were analyzed for the 27 measurement items using factor analysis and 6 factors were extracted (inside height and side gradient, ankle thickness, toe height and midfoot size, lateral malleolus height, instep, and heel height and gradient). A cluster analysis resulted in three types: 36.5% belonged to Type 1 (high forefoot and high midfoot), 31.1% belonged to Type 2 (high forefoot and low midfoot), and 32.4% belonged to Type 3 (low forefoot and high midfoot). The distribution was relatively even. For the sole, 8 factors were extracted (ball width and medial foot protrusion, lateral foot protrusion, forefoot and hindfoot length ratio, ball gradient, heel size, toe breadth, lateral ball length, and foot length) and a cluster analysis resulted in three Types (Type H, Type D, and Type A). The largest proportion (42.7%) belonged to Type H, which is the same as the elderly men's case.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.13-19
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• 2008