• Korean Journal of Applied Biomechanics
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• v.18 no.3
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• pp.1-10
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• 2008

One of the major factors affecting maneuverability of an athlete is frictional force caused at an outsole of his shoe. The magnitude of the frictional force is closely related to pattern and hardness of outsole and roughness of ground or floor. This study then focuses on the effect of outsole pattern of sports shoes on the frictional force. After surveying outsole patterns of sports shoes in markets, we select 4 types of outsole patterns, such as straight, W, O, and wave as primary outsole patterns of sports shoe and we also select depth, pitch and slope as design parameters of each pattern. Corresponding to those patterns and design parameters, various outsole specimen are prepared for frictional experiments. After performing frictional tests with those specimen, coefficients of friction(COF) are collected and analyzed with a statistical tool to draw useful conclusion.

• Journal of Obesity & Metabolic Syndrome
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• v.27 no.4
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• pp.254-261
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• 2018

Background: The most beneficial dietary pattern in managing metabolic syndrome (MetS) in the elderly has not been ascertained. The aim of this study is to classify dietary patterns and to examine associations between dietary pattern, MetS and body composition in elderly Koreans. Methods: This study was conducted among Koreans 65 years or older using data from the Korea National Health and Nutrition Examination Survey in 2009. A total of 1,567 study subjects were included. All statistical analyses were conducted using SPSS version 20.0 and dietary patterns were classified by cluster analysis. Results: There were three dietary patterns derived by cluster analysis in this study. We observed that most South Korean elderly still maintain a traditional dietary pattern. Dietary patterns were classified as balanced (31%), imbalanced (40%), or very imbalanced (30%), with the majority of subjects having an unbalanced diet pattern in which their total energy and nutrient intake was insufficient compared with the Dietary Reference Intake for Koreans. Those in the very imbalanced group had a ratio of macronutrients (carbohydrates:fats:protein) of 81.15:7.18:11.50 and a 54% higher likelihood of having hypertriglyceridemia (P=0.025) compared with those in the balanced group. Conclusion: The current findings indicate that the diets of South Korean elderly are nutritionally imbalanced, including high carbohydrate consumption, which confers a high risk hypertriglyceridemia. These findings highlight the effect of nutritional imbalance in elderly with MetS.

• The Journal of Korean Medicine
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• v.30 no.2
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• pp.152-165
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• 2009

Objectives: We intended to identify differences of general symptoms related to existence & nonexistence of uterine myoma. Methods: We surveyed 948 women from 35 to 45 years old who had received Korean oriental medical questionnaires about general symptom patterns and abdominal & pelvic ultrasonography at Kyung-Hee University medical center from May 2007 to October 2008. After we divided the women into two (uterine myoma or normal) groups by ultrasonography result, we compared general symptom patterns of the uterine myoma group with those of the normal group. Results: In relation to digestion pattern, appetite showed statistically significant difference between the normal and uterine myoma groups. In relation to evacuation pattern, stool frequency showed statistically significant difference between the normal and uterine myoma groups. In relation to psychologic pattern, difference in oppression in the chest & palpitation showed statistical significance between the groups. In relation to the other patterns, differences in throat discomfort & hypertonicity of nape neck showed statistical significance between the normal and uterine myoma groups (p<0.05). Conclusions: The result showed that prevalence of uterine myoma should be considered in respect to digestion pattern, evacuation pattern, and psychologic pattern. We need further study after increasing the size of the uterine myoma group and improvement of general symptom questionnaires.

• Smart Structures and Systems
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• v.13 no.3
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• pp.453-471
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• 2014

The fault diagnosis of rolling element bearings has drawn considerable research attention in recent years because these fundamental elements frequently suffer failures that could result in unexpected machine breakdowns. Artificial intelligence algorithms such as artificial neural networks (ANNs) and support vector machines (SVMs) have been widely investigated to identify various faults. However, as the useful life of a bearing deteriorates, identifying early bearing faults and evaluating their sizes of development are necessary for timely maintenance actions to prevent accidents. This study proposes a new two-layer structure consisting of support vector regression machines (SVRMs) to recognize bearing fault patterns and track the fault sizes. The statistical parameters used to track the fault evolutions are first extracted to condense original vibration signals into a few compact features. The extracted features are then used to train the proposed two-layer SVRMs structure. Once these parameters of the proposed two-layer SVRMs structure are determined, the features extracted from other vibration signals can be used to predict the unknown bearing health conditions. The effectiveness of the proposed method is validated by experimental datasets collected from a test rig. The results demonstrate that the proposed method is highly accurate in differentiating between fault patterns and determining their fault severities. Further, comparisons are performed to show that the proposed method is better than some existing methods.

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.858-868
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• 2016

This study aims to examine the formative characteristics of seniors' fashion in overseas social media, and look into the psychological characteristics of seniors by analyzing the emotions and the characteristics of psychological mechanism in seniors' fashion. The study methods include statistical analysis and content analysis for literary study and data analysis. For data analysis, statistical and content analyses were conducted to analyze 992 data collected from Advanced style, Facebook, and Instagram for 4 years from 2013 to 2016. In formative features shown at overseas social media, circle and square silhouette, achromatic color and warm color, showy tone color, soft material, horizontal details, plain and natural patterns, cap and sunglasses production, and sophisticated elegance styles appeared high. The emotional characteristics in senior's fashion had a silhouette that expressed stability, color that expressed passion, love, happiness, joy, hope and comfort. Materials were expressed by the emotions of dependence and attachment, details were expressed by stable, maternal, calm, comfortable and harmonious emotions. Patterns were expressed by the images of beauty, love, fruit and psychological stability. Accessories were expressed by young and characterful images. Style expressed the emotions of trust, pride, longing, intoxication and ecstasy. The characteristics of psychological mechanism used such shapes and patterns as flower, heart and lips to symbolize the emotions of love, humor, and fun. Young and trendy fashion were expressed in compensation for aging. Kitsch and kidult style was expressed by regression. Elegance fashion was expressed by the sublimation of pride, trust and intoxication.

• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.485-491
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• 2022

Objectives: Tuberculosis (TB) is a major public health concern worldwide. Social contact patterns can affect the epidemiology and risk of airborne diseases such as TB. This study was designed to investigate the social contact patterns associated with TB. Methods: In this case-control study, groups of participants with and without TB were matched by age and sex. Participants reported the nature, location, frequency, and average duration of social contacts over 1 month. The duration and number of social and spatial contacts were compared between groups using the chi-square test and the t-test. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to quantify the relationship between social contact time and TB status. Data were analyzed using Stata version 11 statistical software. A p-value of <0.05 was considered to indicate statistical significance. Results: In this study, 80 patients with TB and 172 control participants were included, and a total of 3545 social contacts were registered. Social contact with family members (OR, 1.72; 95% CI, 1.10 to 2.40), contact with a person with TB (OR, 1.53; 95% CI, 1.16 to 2.01), and contact at the participant's home (OR, 1.42; 95% CI, 1.19 to 1.82) were significantly associated with TB status. Conclusions: The duration of long-term social contact, rather than the number of contacts, may be the main contact-related factor associated with TB transmission in this population. The focus of contact-tracing efforts should be on finding and treating both family members and long-term contacts in non-household settings.

• Korean Journal of Human Ecology
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• v.10 no.4
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• pp.399-409
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• 2001

The purpose of this study was to evaluate the preference of image for modern application of Korean traditional patterns. A survey was conducted using the random selection among female undergraduate students in Daegu city. The degree of interest and preference in Korean traditional style or something like that measured by 5 scale method. And then they were classified into two groups which were interest/non-interest group, and preference/non-preference group. The image of Korean traditional patterns consisted of semantic differential scales. Frequency, percentage and mean were analyzed, for difference of groups t-test was analyzed. The results were as fellows; 1. For the degree of interest for Korean traditional patterns, it was showed that 53.8% of total respondents took interest and about 40.4% of them had preference for traditional patterns. the correlation coefficient of the degree of interest and preference was 0.782(p<0.01) and showed that the positive correlation was high. 2. Among 20 kinds of Korean traditional patterns, the degree of preference for the patterns of plants and nature was quite high whereas that for the patterns of geometrical things was low relatively. 3. It was evaluated that pattern of nature was fresh, refined and womanly image generally. It was evaluated that pattern of plants was womanly, fresh, weak, light and soft image and that of animals was heavy, splendid, high-class, manly, strong and positive image. It was evaluated that pattern of geometrical things was the most refined image and high-class, rigid and strong. 4. The statistical significance of mean between interest/non-interest group was showed statistically in the patterns of clouds, mountains, lotus, apricot, orchid, dragon, phoenix and bogey. In case of pattern of orchids, the degree of preference was most different between interest/non-interest group. 5. The pattern of plants showed the most different evaluation for images between interest/non-interest group. For refined/old-fashioned polar adjective images, the interest group evaluated the pattern of plants more refined. 6. For pattern of orchids, the difference of degree of preference between preference/non-preference group was most remarkable in Korean traditional patterns. 7. The pattern of geometrical things showed the most different evaluation for images between preference/non-preference group. For warm/cool polar adjective images, the preference group evaluated the pattern of geometrical things cooler.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.633-645
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• 2017

This study proposes a statistical procedure for analyzing container ship operation data that can help determine fuel consumption patterns. We first investigate the features that affect fuel consumption and develop the prediction model to find current fuel consumption. The ship data can be divided into two-type data. One set of operation data includes sea route, voyage information, longitudinal water speed, longitudinal ground speed, and wind, the other includes machinery data such as engine power, rpm, fuel consumption, temperature, and pressure. In this study, we separate the effects of external force on ships according to Beaufort Scale and apply a partial least squares regression to develop a prediction model.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.