• Human Ecology Research
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• v.54 no.4
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• pp.427-440
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• 2016

This study uses comparison tests of bodice basic patterns to research improvements in wearing evaluation methods based on differences in bodice basic patterns and body size. As study methods, we calculated body sizes for six types by selecting four types of bodice basic pattern and utilized bodice basic pattern size measurement tools. The study result are as follows. First, as the result of analyzing bodice basic patterns per each part and body size difference by bodice basic pattern size measurement tool, shoulder angle cover rate was J&K type 57.57%~68.41%, N type 53.13%~65.57%, L type 51.87%~63.73%, and H type 59.03%~68.20%. In the item of neck base circumference, it was J&K type 6.4~-16 mm, N type 10.7~-31.9 mm, L type -5.2~-13.4 mm, and H type -6.2~-15.4 mm. In the item of armscye circumference, it was J&K type -18.9~-59.4 mm, N type -15.2~-51.3 mm, L type -38.9~-52.7 mm, and H type -17~-42.2 mm. In the item of biacromion length, it was J&K type 23.2~-4.7 mm, N type 18.4~-10.4 mm, and H type 3.5~-5.7 mm. In the item of interscye back, it was J&K type and N type 17.6~-13.6 mm, L type 11.9~-13.6 mm, and H type 3.2~-11.8 mm. The item of interscye front was found in the sequences of study type and L type. Second, the Kruskal-Wallis test result (according to bodice basic pattern) indicated meaningful differences in items of shoulder angle cover rate, neck point to breast point, bust point-bust point, biacromion length and armscye circumference and H type had an overall higher rank.

• Journal of Korean Medicine for Obesity Research
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• v.14 no.1
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• pp.36-45
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• 2014

Objectives: The purpose of this studay was to compare the eating-related index and the patterns of pre- and post-prandial gut hormone level in normal-overweight and obese subjects of Taeemin population. Methods: We enrolled healthy male participants who were diagnosed with Taeeumin by Sasang Constitutional diagnosis and who were normal-overweight ($18.5kg/m^2{\leq}$body mass index [BMI)< $25kg/m^2$) or obese ($25.0kg/m^2{\leq}$BMI< $30kg/m^2$). Eating behavior and gastrointestinal problems were assessed by using standardized scale. Subjective appetite ratings using visual analogue scales and the profiling of serum levels of ghrelin and peptide YY (PYY) were assessed before and after a standard meal (6 time points: 30 minutes pre-prandial, immediately before meal, 15, 30, 60, and 120 minutes post-prandial). Results: Tewnty two healthy Taeeumin people classified as normal-overweight group or obese group are the final subjects. External eating score of Dutch eating behavior questionaire scores is higher in normal-overweight group than in obese group. The variations of subjective appetite ratings in obese group are smaller than in normal-overweight group. The pattern of ghrelin in normal-overweight group shows a high peak at 30 minutes post-prandial point, which is contrary to existing studies. The pattern of PYY in obese group decreases from 15 minutes post-prandial point and shows lower peak level, whereas in normal-overweight group shows increasing tendency from pre-prandial point until 30 minutes post-prandial point. Conclusions: There are differences in the eating-related index and the gut hormone patterns related to obesity.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.285-292
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• 2004

The objective of this paper is to develop a simplified method to determine yield line patterns of reinforced concrete floor slabs based on the elastic fields. Unlike other methods mainly focused on the plasticity theory, this paper emphasizes the elastic fields, especially principal moments and maximum shears and shows a link between elasticity field and yield line patterns. General criteria on both positive and negative yield lines are suggested in terms of principal moments and maximum shear forces. The proposed method can predict starting point (or regions) of yielding and the further development of yield lines on whole structures. The yield line patterns determined by the proposed method are shown to be coincident with the classical yield line theory. Furthermore, orthotropy in reinforced concrete slab is investigated and yield line patterns for different type of flat slab with non-isotropic strip are studied broadly.

• The Korean Journal of Community Living Science
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• v.15 no.1
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• pp.57-65
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• 2004

The purposes of this study are to identify types of fathers who engaged in different patterns of interaction with their children and to examine the characteristics by different fathering patterns. Data are collected from 323 married men with the oldest child under 12 years old, using the structured questionnaire survey method. The major findings of the study are as follows: First, the fathering activities are composed of four factors, which are affective involvement, caretaking, social involvement and discipling. The respondents tend to exhibit the level of fathering activities higher than middle point. Second, using cluster analysis, three types of fathers are categorized: The affective type fathers scored significantly high on dimensions of affective involvement. Whereas the engaged fathers scored the highest on all domains of fathering, the disengaged fathers demonstrated significantly limited involvement. Third, the characteristics which are associated with fathering activities patterns are father's age, job type, work hour, frequency of meetings after work hour, job satisfaction and child rearing attitude. The results of this study suggest several implications to develop parent education program for fathers and their children.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.161-164
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• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• Archives of design research
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• v.13 no.1
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• pp.199-207
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• 2000

The planning of large department store is differ from designing other spaces because it holds items to sell. To make effective selling area, those items are to be showed enough to attract potential customers. In well planned space, customers would enjoy shopping convenientiy and comfortably. There are some requirements to make those kind of space. First, the design must consider customers needs. Second. the design must show items own values effectively. And third is identity of the store. At this point entrance or lobby area would possibly take major role to imprint identity and store concept. The purpose of study is to make well planned lobby area in order to lead customers traffic patterns to effective selling spaces. The method of this study is establishing hypothesis about interior and exterior aspects which effect to traffic patterns. And build condition that helps testing the hypothesis. Through the processes mentioned above, we would possibly reach the result like, First, It is important to reserve enough lobby space to prevent oversizing of selling space and advise effective traffic patterns. Second, Organize the aspects that could cause the change of customers traffic patterns and bring those customers selling point. Third, Make useful context which can attract customers passing by.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.1
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• pp.97-113
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• 2016

This study develops pant patterns using body shape, measurement and shell mesh data to decide optimal women's pants according to styles with excellent size, fit and shape for different individuals and silhouettes. Standard landmarks, lines, triangles and structures were set on a 3D scanned lower body shell to represent women in their twenties and flattened as a 2D pattern. Patterns were created and analyzed according to culotte, formal, slacks and tight type considering crotch shape, location of the crotch point, and adjusting waist darts. Flattened patterns were rotated to compare existing methods. The crease lines were then set through the hip protrusion point and compared. The main factor of the pant pattern were extracted, total rise, crotch depth, crotch width, angle of center line, shape of the center line curve, the thigh width, the amount of waist dart, and crease line position. With going tight style from the culotte, the fits are closer to the figure with minimized thigh circumference, the dart amount decreases, the crotch depth increases, the crotch extensions were shorter, and the angle of the center back increased. The total rise is U shape for culotte and is closer to V shape as the silhouette tightens. T-test of appearance evaluation of the developed pant pattern were conducted after analyzing measurements and shapes of each styles. The results of the developed patterns were superior to existing patterns in accordance to hip line between body and pants as well as appearance evaluation. We found systematic mechanisms among pattern factors that create various pant silhouettes. Evidence on classification of the silhouettes of traditional types of pants were explained objectively through the process of playing out 3D forms.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.127-136
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• 2009

This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.247-254
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• 2018

Purpose: Although previous studies have performed on-farm evaluations for the control of airborne diseases such as foot-and-mouth disease (FMD) and influenza, disease control during the process of livestock and manure transportation has not been investigated thoroughly. The objective of this study is to predict common patterns of livestock-vehicle movement. Methods: Global positioning system (GPS) data collected during 2012 and 2013 from livestock vehicles on Jeju Island, South Korea, were analyzed. The GPS data included the coordinates of moving vehicles according to the time and date as well as the locations of livestock farms and manure-keeping sites. Data from 2012 were added to Esri software ArcGIS 10.1 and two approaches were adopted for predicting common vehicle-movement patterns, i.e., point-density and Euclidean-distance tools. To compare the predicted patterns with actual patterns for 2013, the same analysis was performed on the actual data. Results: When the manure-keeping sites and livestock farms were the same in both years, the common patterns of 2012 and 2013 were similar; however, differences arose in the patterns when these sites were changed. By using the point-density tool and Euclidean-distance tool, the average similarity between the predicted and actual common patterns for the three vehicles was 80% and 72%, respectively. Conclusions: From this analysis, we can determine common patterns of livestock vehicles using previous year's data. In the future, to obtain more accurate results and to devise a model for predicting patterns of vehicle movement, more dependent and independent variables will be considered.

• Proceedings of the CALSEC Conference
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• 2005.11a
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• pp.147-153
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• 2005

When a customer wants to buy an item at the Internet shopping mall, one of the difficulties is to decide when to buy the item because its price changes over time. If the shopping mall can be able to recommend appropriate buying points, it will be greatly helpful for the customer. Therefore, in this presentation, we propose a method to recommend buying points based on the time series analysis using a database that contains past prices data of items. The procedure to provide buying points for an item is as follows. First, we search past time series patterns from the database using normalized similarity, which are similar to the current time series pattern of the item. Second, we analyze the retrieved past patterns and predict the future price pattern of the item. Third, using the future price pattern, we recommend when to buy the item.