• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.6
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• pp.1100-1111
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• 2001

The purpose of this study was to develop fashion On-line store attributes for fashion On-line shopping mall and to identify significant On-line store attributes, influencing consumers'purchase intention of interned fashion product shopping. A questionnaire was administered to 456 adults who had purchasing experience at fashion On-line shopping mall. SPSS 9.0 package was used for data analysis. Factor analysis, $X^2-test$, t-test, frequency, percentage, one-way ANOVA, multiple regression analysis were utilized. The results were as follows; 1. The On-line store attribute dimensions of fashion On-line shopping mall were tangibility, variety, marketing promotion, responsiveness, reputation, price and convenience. 2. The purchase experienced consumers showed higher purchase intention of Internet fashion product shopping and highly perceived about all sub-factors, except reputation. in On-line store attributes that have significantly positive influence on fashion On-line shopping attitudes. The purchase experienced consumers showed more favorable attitudes toward Fashion On-line shopping than non purchase experienced consumers. Attitudes toward Fashion On-line shopping have directly impact on purchase intention of Internet fashion product shopping.

• Journal of Biosystems Engineering
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• v.32 no.4
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

• Korean Journal of Applied Biomechanics
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• v.17 no.3
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• pp.51-60
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• 2007

The purpose of this study was to kinematically analyze the differences between short(2.17 m) and long(10.94 m) putting stroke motions. Thirteen male professional golfers were participated in this study. Experiment was conducted on the artificial grass mat in the gymnasium. Kinematic data were collected by the 60 Hz Kwon3D motion analysis system. Differences were compared by SPSS paired t-test and one-way ANOVA. Duncan was used for post-hoc test and a=.05. The results were as follows: 1. Ground projected trajectory of the putter head were statistically straight during both short and long putts. 2. There was no consistent alignment tendency among shoulder, hip, and stance alignments. However stance alignment was consistent between short and long putts. Thus it is assumed that professional golfers align their body based on their stance alignment. 3. During putting, shoulder rotated not only up and down but also right and left. 4. Left and right elbow distance was maintained during all phases of the putts for both short and long putts. 5. Inter foot distance of long putting was longer than that of short putting.

• The Korean Journal of Health Service Management
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• v.6 no.4
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• pp.99-109
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• 2012

The purpose of this study is to explore the factors that influence employer to rehire the mentally disabled. The participants of survey were 121 of employers' in Busan. Data were analyzed using ${\chi}^2$-test, t-test and logistic regression analysis with SPSS/WIN 18.0. According to this analysis, the results show that employer's rehiring intentions for the mentally disabled is a significantly related to gender, relationship with mental disabled person, industrial classification, experience of disabled employees, period of employment with mentally disabled people, subsidy for employment promotion, employment quota system, benevolence, community mental health ideology. Logistic regression analysis showed that relationship with mental disabled person, industrial classification, experience of disabled employees, period of employment with mentally disabled people, subsidy for employment promotion, employment quota system and benevolence. On the basis of results, program for encouraging employer's intention of rehiring the mentally disabled should be development and establish mediate strategies.

• Korea Journal of Hospital Management
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• v.24 no.1
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• pp.1-10
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• 2019

Purpose: To analyze the results of an online survey conducted to develop a user-friendly respiratory disease management mobile application. Methodology: The questionnaires were conducted from July 26, 2018 to October 23, 2018 for 90 days. A total of 267 respondents were used for the analysis. Chi-square test, t-test, and multivariate logistic regression were used for statistical analysis. Findings: As a result of the analysis, preference for functions related to medical services was high in all ages and the odds of positive intention to use respiratory disease management application was 4.76 times higher than 40 years old compared with less than 40 years old. The group with more than one effort was found to be significantly higher than those who did not. Practical Implication: It is expected that the functions derived from the main results in this study will be helpful for the effective health management of patients with chronic respiratory disease.

• Microbiology and Biotechnology Letters
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• v.49 no.2
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• pp.249-254
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• 2021

The study of the impact of weather on viral respiratory infections enables the assignment of causality to disease outbreaks caused by climatic factors. A better understanding of the seasonal distribution of viruses may facilitate the development of potential treatment approaches and effective preventive strategies for respiratory viral infections. We analyzed the incidence of human mastadenovirus infection using real-time reverse transcription polymerase chain reaction in 9,010 test samples obtained from Cheonan, South Korea, and simultaneously collected the weather data from January 1, 2012, to December 31, 2018. We used the data collected on the infection frequency to detect seasonal patterns of human mastadenovirus prevalence, which were directly compared with local weather data obtained over the same period. Descriptive statistical analysis, frequency analysis, t-test, and binomial logistic regression analysis were performed to examine the relationship between weather, particulate matter, and human mastadenovirus infections. Patients under 10 years of age showed the highest mastadenovirus infection rates (89.78%) at an average monthly temperature of 18.2℃. Moreover, we observed a negative correlation between human mastadenovirus infection and temperature, wind chill, and air pressure. The obtained results indicate that climatic factors affect the rate of human mastadenovirus infection. Therefore, it may be possible to predict the instance when preventive strategies would yield the most effective results.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.1
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• pp.66-72
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• 2022

The Mooney-Rivlin second order optimal strain energy function derived through uniaxial tensile test and analysis was applied to a gasket to confirm the internal stress and surface pressure generated during compression. The Taguchi method, a statistical technique, was used to design the optimum shape of the gasket, and through characteristic evaluation, the optimum shape of the gasket was obtained when the reference plane (T: 0.15 mm), contact surface (W: 1.00 mm), and curvature (R: 0.30 mm) were used. It was determined that the optimum shape yields a von Mises stress of 4.83 MPa, and the contact pressure stress is 20.14 MPa, which satisfies breakage and sealing requirements. In the future, we plan to manufacture a jig that can measure surface pressure to conduct comparative verification studies between the test results and analysis results.

• Journal of Korean Clinical Nursing Research
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• v.16 no.3
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• pp.51-61
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• 2010

Purpose: The purpose of this study was to determine the effect of needs for professional development and organizational climate on organizational socialization of clinical nurses. A cross-sectional analysis were performed to assess the factors affecting organizational socialization. Methods: The data used in this study were obtained from clinical nurses who were employed in a hospital (N=606). Using multiple regression, we tested variables to assess their effects on organizational socialization in this sample. The data were analyzed using descriptive test, t-test, ANOVA, Pearson correlation coefficiency and stepwise multivariate regression. SPSS 17.0 program was utilized for data analysis. Results: The mean scores of organizational socialization, needs for professional development and organizational climate were statistically differed by career ladder, educational level and position. Organizational socialization had significant positive correlations with the needs for professional development (r=.332, p<.01) and organizational climate (r=.523, p<.01). Those variables including career ladder explained 33.4% of organizational socialization. Conclusion: Our findings indicate that organizational socialization of clinical nurses could be enhanced by meeting the needs for professional development and organizational climate. Developing innovative educations for encouraging clinical nurses' carrier development and creating a positive organizational climate are mandated for clinical nurses to have constructive organizational socialization.

• Journal of Korean society of Dental Hygiene
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• v.23 no.5
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• pp.369-377
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• 2023

Objectives: The aim of this study was to develop and validate a Korean-adapted version of the job expectations scale for dental hygienists. Methods: To achieve this goal, a comprehensive methodology was employed, including frequency analysis, exploratory factor analysis (maximum likelihood, direct oblimin rotation), confirmatory factor analysis, Cronbach's α reliability, independent t-test, and one-way ANOVA (Duncan post-hoc test) were performed. Results: The Korean version of job expectations scale for dental hygienists comprised 21 items in the personal domain and 5 items in the social domain. The scale demonstrated high construct validity, convergent validity, discriminant validity, and reliability were found. While dental hygienists were found to have higher expectations in the their personal domain than the social domain, expectations in the social domain were higher among male hygienists, those with a bachelor's degree or higher, those in regular permanent employment, and those working in hospital-level or higher facilities. Conclusions: Job expectations is a more comprehensive construct than job roles or professional identity. We anticipate that the instrument will be widely used to analyze trends in job expectations in response to changes in societal values regarding to dental hygienists, the gap between realities and ideals within the dental hygiene profession, and policy considerations.