• 대한치과기공학회지
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• 제42권4호
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• pp.362-371
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• 2020

Purpose: The following study seeks to ascertain the motivations behind students' academic major selection and to identify the obstacles they encounter in the transition to university life, with the objective of providing information necessary to adapt well to the university and the course. Thereby, we aim to supply basic resources needed in the development of a university adaptation program to prevent academic dropout. Methods: Between October 1, 2019 and November 29, 2019, a self-administered questionnaire was distributed to a study sample consisting of students currently attending dental technology courses in Gangwondo and Gyeonggido. A total of 474 (94.8%) responses to the questionnaire were received and used for the final analysis. Results: Factors including major selection motivation, intrinsic motivation (p<0.001), academic adjustment (p<0.001), social adjustment (p<0.01), and institutional adjustment (p<0.05) all had negative relationships with academic dropout intention. Personal-emotional adjustment (p<0.001), however, showed a positive relationship with dropout intention. The explanatory power of the model was found to be 50.0%. Conclusion: This research shows that intrinsic motivation and personal-emotional adjustment diminish academic dropout intention. Therefore, it is recommended that diverse postenrolment course-adjustment programs should be developed to improve students' confidence in their choice of study, their adjustment to the course, and their level of satisfaction.

• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.84-91
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• 2021

The purpose of this study is to investigate the structural relationship between resort selection attributes, emotional responses, and empirical values of scuba diving participants. The general population who enjoys scuba diving in Korea was selected as the population. Using the convenience sampling method, 553 of the 600 questionnaire samples were extracted as the final valid sample. For data processing, frequency analysis, exploratory factor analysis, and Cronbach's α test were performed using SPSS 23, and confirmatory factor analysis and structural equation model analysis were performed with AMOS 18. The results are as follows: First, among the sub-factors of selection attributes, equipment, facility environment, and diving point showed a positive effect on emotional response, but staff service did not have any significant effect. Second, the emotional response positively affected by the selection attribute showed a positive effect on all factors of service excellence, consumer utility, fun value, and aesthetic value of empirical value. Therefore, scuba diving resort managers must recognize the importance of equipment, facility environment, and diving point among these selection attributes of customers. And to satisfy the customer needs the resort must accurately identify the needs for diving equipment, facility environment and diving point. Various methods for this should be explored through the needs of the identified customers, and efforts should be made to provide safe equipment, comfortable facilities, and various diving points.

• 한국수자원학회논문집
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• 제39권12호
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• pp.997-1012
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• 2006

본 연구에서는 조건부 핵밀도함수와 CAFPE(Corrected Asymptotic Final Prediction Error) 차수결정 방법에 근거한 비매개변수적 비선형 자기회귀 (Nonlinear AutoRegressive, NAR) 모형을 소개하고 이를 SOI(Southern Oscillation Index)에 적용하였다. SOI 자료에 대해서 선형 AR 모형을 적용하였으나 잔차에 대한 검정결과 이분산성(heteroscedasticity)을 나타내었다. 또한 BDS(Brock-Dechert-Sheinkman) 검정에서 비선형성이 존재함을 확인하였다. 따라서 NAR 모형에 SOI 자료를 적용시켰다. CAFPE를 이용하여 가장 적합한 모형으로 지체 1, 2와 4가 선택되었으며 조건부 평균함수를 추정하여 SOI 자료를 모의한 결과 잔차에 대해서 정규성과 이분산성 가정이 Jarque-Bera 검정과 ARCH-LM 검정에서 각각 기각되었으며 또한 조건부 표준편차함수의 최적 차수로 3, 8과 9가 CAPFE를 통해 선택되었다. 조건부 평균함수와 표준편차함수를 모두 고려한 모형에 대한 잔차 검정 결과 잔차의 I.I.D 가정을 만족하였으며 특히, BDS 검정에서 신뢰구간 95%와 99%에서 모두 만족한 결과를 나타내었다. 마지막으로 전체의 15%에 해당하는 SOI 자료에 대해서 One-Step 예측을 수행하였으며 선형 모형에 비해 평균제곱예측오차가 7% 적게 나타났다. 따라서, NAR 모형은 여타의 매개변수적 방법과 달리 모형 선택에 있어 자유로우며 비선형성을 고려할 수 있는 모형으로서 SOI 자료와 같은 비선형 자료를 위한 모의방법으로 선형 모형에 비해 많은 장점을 가지고 있다.

• Nutrition Research and Practice
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• 제12권4호
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• pp.348-354
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• 2018

BACKGROUND/OBJECTIVES: Obesity is a serious concern worldwide, for which the restaurant industry holds partial responsibility. This study was conducted to estimate restaurant consumers' intention to select healthy menu items and to examine the relationships among behavioral beliefs, past behaviors, attitudes and behavioral intentions, which are known to be major determinants of consumer behaviors. SUBJECTS/METHODS: An online, self-administered survey was distributed for data collection. The study sample consisted of customers who reported having visited casual dining restaurants in the last three months at the time of the survey. Structural equation modeling was used to verify the fit of the proposed research model. RESULTS: Structural equation modeling revealed that the proposed model supports the sequential, mediated (indirect) relationships among behavioral beliefs, past behaviors, attitudes and behavioral intentions toward healthy menu selection. CONCLUSION: This study contributes to the available literature regarding obesity by adding past behaviors, one of the most influential variables involved in prediction of future behaviors of consumers, to the TPB model, enabling a better understanding of restaurant consumers' rational decision process regarding healthy menu choices. The results of this study provide practical implications for restaurant practitioners and government agencies regarding ways to promote healthy menus.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 2003년도 제11회 춘계 심포지움 연제집
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• pp.30-37
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• 2003

o Cohort study became the major approach to study of chronic diseases such as CVD and cancer o Cohort can be population-based or volunteer-based o Types of be population-be categorized by source population and selection mechanism o More and more cohort studies involve biological specimens, such as blood, urine, toenail, cheek cells, etc. o Multi-center and multi-national collaboration is an effective way to increase sample size. o Current statistical method typically use time-to-event analysis by Cox proportional hazard model.

• 한국병원경영학회지
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• 제20권1호
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• pp.53-64
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• 2015

Our objective was to evaluate differences in linear regression versus multilevel(cross-level interaction model) modeling for affecting factors lumbar discectomy. The data were used in 2011 patients with HIRA sample data. Total number of analysis is 3,641 patients and 248 hospitals. The results of research model showed that the type and location of the hospital-level factors were significant. However, all factors of patient-level were similar in the two models. Therefore, it requires the selection of an appropriate model for a more accurate analysis of the influencing factors in the daily medical charge.

• 농촌계획
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• 제21권2호
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• pp.137-147
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• 2015

In this study, consumers who have experience of visiting Jeongsun Arirang Market has been selected as samples to understand the characteristics of agricultural products purchase. For this, double hurdle model was used in order to resolve sample selection problem and obtain consistent estimator. The key points are the following. First, as the age increases(up to 59.8 years), chances of purchasing the products at traditional market increase as income increases. Second, when the residence area is outside of Gangwon-province, the purchase amount of the products increased compared to those from visitors within the Gangwon province. Also, visitors who use public transportations purchase less products compared to those who use their own car. Third, probability of agricultural products increase as the visitors consider positive effect the product purchase leads to the local farmers. Fourth, if the visitors consider the quality of the agricultural products, probability of purchasing agricultural product at the site increases. However, if the visitors consider the freshness of the agricultural products, the purchase amount rather drops. Fifth, the probability of purchase increases as visitors consider the brand of traditional market.

• 로봇학회논문지
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• 제9권2호
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• pp.117-123
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• 2014

Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.

• 한국국방경영분석학회지
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• 제12권1호
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• pp.87-105
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• 1986

Among the various types of waiting line systems, the elevator servicing system is quite different from the usual queueing system in view of the service characteristics. For example, the FIFO discipline is not always valid depending upon the situation when the direction of first-come customer's is opposite of the operating elevator direction and at that time a later-arrived one has a luck to be served first. In this paper, a simulation model is constructed and tested by the sample data and the results have turned out to be fairly adequate. This model, therefore, will provide a good guide to anyone who is interested in the decision of optimal location selection of no-passenger elevator in high buildings whatsoever. This model is also available, with slight modification, to the problem of city bus dispatching or any other waiting line problems where the servicing equipments are moving.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.801-812
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• 1999

Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.