• Journal of the Korean Society of Costume
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• v.57 no.3 s.112
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• pp.1-13
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• 2007

The Purpose of this study is to analyze the kinds and positions of tattoo patterns on the body in tattoo-related internet communities and professional web sites. for this purpose, 1,892 tattoo patterns were analyzed by sex(man and woman). The results were as fellows; First, animal patterns(30.2%) occupied most, followed by character patterns(24.1%), geometric patterns(13.0%), natural patterns(10.3%), plant patterns(4.7%), mixed patterns(2.5%), and artificial patterns(2.2%). In patterns, dragon(10.3%) occupied most, followed by star(8.7%), trival(8.6%), woman(7.6%), skeleton(4.9%), and letter(4.8%). Second, men's preference to pattern groups included animal patterns(30.8%), character patterns (28.3%), geometric patterns (14.6%), and natural patterns(6.0%). Among patterns, dragon(13.4%) was the most frequent, followed by trival(10.9%), woman(10.7%), and skeleton(7.1%). Women's preference to patterns groups included animal patterns(31.4%), natural patterns(17.3%), character patterns(17.2%), geometric patterns(10.5%), and plant patterns(10.0%). Among patterns, star(15.3%) was the most frequent, followed by butter- fly(10.5%), elf(9.2%), and dragon(9.2%). Third, the positions of tattoos on the body included upper arm(26.6%), shoulder(10.8%), back(10.5%), the wrist(10.0%), the calf(7.5%), back bottom(7.0%) and the breast(6.3%). While men's preference to pattern positions included upper arm(38.2%), the wrist(13.7%), back(10.5%), the calf(9.4%), and shoulder(8.0%), women's preference to positions included back bottom(17.7%), shoulder(15.5%), back(10.5%), front bottom(8.2%), and the breast(7.8%).

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.11-26
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• 2009

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern- based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3%.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.18-21
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• 2001

The change of sleep pattern is one of the most often altered normal physiological functions in elderly people. Besides normal change of sleep, insomnia and sleep apnea syndrome (SAS) are (one of) the main complaints. In addition, parasomnia is also frequent in this age group. Several parasomnias frequently found in the elderly are reviewed. Periodic limb movements in sleep (PLMS), restless legs syndrome (RLS), and REM sleep behavior disorder are the most frequent parasomnias in old age. Most parasomnias could be diagnosed by polysomnography, and be treated easily. Therefore, early and precise diagnosis and management for parasomnia in aging people are needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• The Journal of the Society of Stroke on Korean Medicine
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• v.10 no.1
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• pp.47-53
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• 2009

Objectives : This study was aim to investigate the relationship between NIHSS and distribution of pattern identification in stroke patients. Methods : 1471 participants from the patients hospitalized for stroke within 4 weeks from April 2007 to August 2009 were included. They were grouped according to the NIHSS score; group 1 for the participants whose NIHSS were less than six, group 2 for seven to fifteen, and group 3 for over than sixteen. And the patients were re-divided into two groups according to their post-onset interval. The difference of distribution of five pattern identification for each group were investigated. And five pattern identification were re-analyzed according to the deficiency-excess pattern identification. K-W test was used for statistical synthesis, and the result was regarded as significant one, if its p-value was below 0.05. Results : Dampness-phelegm pattern was the most frequent out of five patterns in total participants as well as all the subgroups. In group 3 with more serious neurological deficit, larger proportion of patients in early acute stage was diagnosed as excess pattern including Fire-Heat pattern. On the other side the proportion of Deficiency of Qi and Yin was larger in late convalescent stage of group 3 than in other groups. But nothing was statistically significant. Conclusions : Further study including patients with more variant classification with follow-up evaluation is needed to reflect the real characteristics of stroke population.

• The Korean Journal of Cytopathology
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• v.11 no.2
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• pp.83-88
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• 2000

This study presents the cytologic features of peritoneal washings, with particular emphasis on the cytologic discrimination among serous, mucinous, and endometrioid adenocarcinoma of the ovary. We selected histologically confirmed 27 cases of peritoneal washing : 8 cases of serous cystadenocarcinomas, 5 cases of mucinous cystadenocarcinomas, and 14 cases of endometrioid adenocarcinomas. The most frequent cytologic pattern of three tumors was clusters. Ball pattern was found in serous cystadenocarcinoma(36%) and acinar pattern in endometrioid adenocarcinoma(36%). Mucinous adenocarcinoma showed mucoid background(100%) and endometrioid adenocarcinoma revealed inflammatory background(43%). The cytoplasmic vacuoles were noted in 80%, 13%, and 43% of mucinous, serous, and endometriold adenocarcinoma, respectively. The endometrioid adenocarcinoma showed prominent nucleoli(64%). In conclusion, the cytologic findings of mucinous cystadenocarcinoma were different from that of serous and endometrioid carcinomas, such as mucoid background, abundant cyytoplasm with vacuolated cytoplasm, and peripherally located cytoplasm. Although endometriold carcinoma showed acinar pattern and prominent nucleoli, the differential diagnosis between serous cystadenocarcinoma and endometrioid adenocarcinoma in peritoneal washing cytology was was always possible.

• Korean Journal of Community Nutrition
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• v.4 no.2
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• pp.157-165
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• 1999

This study was conducted to identify the determinants of regional body fat distribution of obesity(upper body obesity and lower body obesity) for adolescents. The macronutrient consumption pattern utilized the most important variables to test for potential determinants. A total of 726 adolescents living in rural areas in Korea had been observed for four years from 1992 to 1996 about their diet, sexual maturation, serum components and physical growth. The study design was similar to that of a case control study. Logistic regression analysis were used as an analytical method to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the risk factors. Fat consumption pattern was the most frequent one among the three macronutrient consumption pattern of carbohydrate, fat and protein. Prevalence of obesity for the subjects was 9.5%. Prevalence of upper body obesity was higher in malestudents than in female students. On the other had, prevalence of lower body obesity was higher in females. The results of the logicstic regression analysis showed that the risk factor for upper body obesity was sexual maturity rather than dietary factors. None of the factors included in the analysis for lower body obesity appear to be the risk factor. The result may suggest that to develop a determinant model for obesity of adolescents, the model should include a wider range of variables other than diet, sexual maturity and changes in blood serum.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.599-617
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• 2006

Recently many LBS(Location Based Service) systems are issued in mobile computing systems. Spatial-Temporal Moving Sequence Pattern Mining is a new mining method that mines user moving patterns from user moving path histories in a sensor network environment. The frequent pattern mining is related to the items which customers buy. But on the other hand, our mining method concerns users' moving sequence paths. In this paper, we consider the sequence of moving paths so we handle the repetition of moving paths. Also, we consider the duration that user spends on the location. We proposed new Apriori_msp based on the Apriori algorithm and evaluated its performance results.

• Korean Journal of Clinical Pharmacy
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• v.16 no.1
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• pp.46-51
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• 2006

Dyslipidemia is an important CHD risk factor in diabetic patients. We conducted this study to assess the pattern of dyslipidemia in type 2 diabetes patients, to examine the demographic and clinical factors associated with dyslipidemia and to evaluate attaining within the lipid target goals and treatment strategies. A retrospective analysis was conducted among patents diagnosed type 2 diabetes at outpatient clinic in endocrinology between January 2003 and December 2004. Clinical history and physical examination were reviewed and laboratory data including blood glucose, HbAlc, lipid levels were recorded sequentially at least 1 year. In 882 patients with type 2 diabetes, 437 patients (49.6%) have dyslipidemia and 73% of them (319 patients) received lipid-lowering agents. 244 patients (94 males, 150 females, mean age 60 years old) were susceptible to analyses. The most frequent pattern of dyslipidemia is high LDL level and high TG levels (28%). Metabolic syndrome and macrovascular complication were significant negative independent association with lipid levels within the target goals (p<0.05). Only 15.2% (19 males, 18 females) attained within the lipid tar- get goals. Patients with diabetic dyslipidemia need maximization of lipid-lowering agents, increasing the fibric acid derivatives prescription and the effort to correction of low HDL and/or high TG.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.