• 한국식생활문화학회지
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• 제16권5호
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• pp.423-430
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• 2001

The facts of job satisfaction and their perceived importance among elementary school foodservice dietitians were assessed. The survey instrument consisted of three parts: the job satisfaction survey was used to measure facets of job satisfaction and the level of total satisfaction; perceived importance questions for corresponding job facets; and demographic items. A survey of school food service operations was undertaken and detailed information was collected from 170 dietitians. The collected data were processed using the SPSS package program for descriptive analysis and analysis of valiance. School foodservice dietitians' importance and satisfactions scores on their job and working environment were 4.25 and 2.83, respectively. The respondents rated the subscales of 'communication' and 'nature of work' the highest and the subscales of 'pay' and 'working environment' the lowest The results of facet satisfaction scores and corresponding perceived importance scores were paired to be plotted on the Importance-Performance Analysis Grid. IPA grid was used to provide a strategy for food service managers to counteract dietitian dissatisfaction.

• 정보관리학회지
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• 제39권2호
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• pp.325-346
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• 2022

뉴노멀 시대로 특징지어지는 현대사회가 COVID-19 팬데믹을 겪으면서 도서관에 많은 변화를 요구하였고, 도서관계는 이에 대하여 선제적으로 그리고 다각적으로 대응하였다. 본 연구는 팬데믹과 같은 새로운 환경이 사서들이 인식하는 도서관 운영정책 우선순위를 변화시킬 것이라고 보고, 2020년 팬데믹이 시작되는 시점과 2022년 팬데믹이 정점을 지난 시점에서 도서관 운영정책 중요도를 쌍대비교 분석을 통하여 파악하였고 그 차이를 비교·분석하였다. 1차 조사에서는 도서관경영, 도서관 서비스 관련 운영정책 영역을 중요하게 여겼다면, 2차 조사에서는 인적자원과 정보자원에 관련된 운영정책 영역을 보다 중요하게 인지하고 있었다. 또한, 전체 영역 상위 5위에 인적자원과 관련된 3개의 세부 운영영역과 자료구입 예산, 이용자만족도 기반의 정책이 포함되었다. 따라서 공공도서관은 새로운 패러다임에 빠르게 적응하면서도 지속가능한 도서관 서비스를 제공하기 위해서는 지속적인 인적자원에 대한 투자, 충분하고도 다양한 형태의 정보자원 구축, 그리고 이용자 맞춤 정책 수립 등을 우선적으로 수행해야 할 것이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.443-446
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• 2007

A new association rule mining algorithm, which reflects the strategic importance of associative relationships between items, was developed and presented in this paper. This algorithm exploits the basic framework of Apriori procedures and TSAA(transitive support association Apriori) procedure developed by Hyun and Choi in evaluating non-frequent itemsets. The algorithm considers the strategic importance(weight) of feature variables in the association rule mining process. Sample feature variables of strategic importance include: profitability, marketing value, customer satisfaction, and frequency. A database with 730 transaction data set of a large scale discount store was used to compare and verify the performance of the presented algorithm against the existing Apriori and TSAA algorithms. The result clearly indicated that the new algorithm produced substantially different association itemsets according to the weights assigned to the strategic feature variables.

• 한국식품조리과학회지
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• 제16권2호
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• pp.112-120
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• 2000

The purpose of this study was to examine the needs of high school students on foodservice. A survey from 8 high school foodservice operations in Seoul was undertaken and detailed information was collected from 538 high school students. Completed questionnaires were received from 3 self-operated and 5 contracted school foodservice operations. Statistical analyses were performed by SPSS including descriptive analysis and t-test. The 49.8% of the respondent students were male and 50.2% female. The whole students assessed the importance and performance of school foodservice as 4.18 and 2.83 out of 5 respectively, which suggests that the school foodservice needs to be improved. The Importance-Performance Analysis(IPA) used for obtaining information on high school foodservice management suggested that foodservice attributes with fair to poor performance but with high importance were sanitation of food, service of foodservice personnel, dealing with complaints and the reflection of students'opinion in menu.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1165-1172
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• 2008

A considerable amount of research has focused on the dimensionality of service quality construct. To achieve and maintain their comprehensiveness and profitability, restaurant managers should manage and aim to continuously improve the level of service quality offered to their customers. This paper is focused on service quality in the Korean native cattle and imported beef restaurant industry in the Korea. So, this paper has adapted DINESERV scale so that restaurant managers can use it to determine how customers perceive the service quality in Korean native cattle beef restaurant and imported beef restaurant. The purpose of this research is to test the difference in importance and actual performance of 5 dimensions between the restaurants that sell the beef of Korean native cattle and imported cattle. The t-value is used to test difference of the importance and actual performance for DINESERV's 5 dimensions of the 2 restaurant types. But, there is no difference between Korean native cattle and imported beef restaurant.

• 한국통신학회논문지
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• 제22권5호
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• pp.1097-1106
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• 1997

Most works on importance sampling (IS) as an efficient evaluation technique havd been done in an additibe white gaussian noise channel (Awgn). In this paper we propose a CQ(conventional importance sampling and quasi-translantion) IS technique for the mobile radio channel modeled as Rician fading, and analyze the IS estimator's variance to determine optimum IS parameters and the minimum number of run times. Reference showed that CIS technique has a poor performance for systems with meories, but it is shown that the CIS technique can be improved by combining with quasi-translation technique even for systems with memories. Here the CQ IS technique modifies the variance of additive noise and also performs quasi-translation for the fading distribution. We determine the optimum IS parameters of the proposed CQ IS estimator and whow that the simulation gains are about 10$^{3}$~10$^{6}$ for the mobile communication systems with memories in case of the expected BERs 10$^{-5}$ ~10$^{-8}$ .

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1990년도 춘계공동학술대회논문집; 한국과학기술원; 28 Apr. 1990
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• pp.272-288
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• 1990

The uncertainty quantification process in probabilistic Risk Assessment usually involves a specification of the uncertainty in the input data and the propagation of this uncertainty to the final risk results. The distributional sensitivity analysis is to study the impact of the various assumptions made during the quantification of input parameter uncertainties on the final output uncertainty. The uncertainty importance of input parameters, in this case, should reflect the degree of changes in the whole output distribution and not just in a point estimate value. A measure of the uncertainty importance is proposed in the present paper. The measure is called the distributional sensitivity measure(DSM) and explicitly derived from the definition of the Kullback's discrimination information. The DSM is applied to three typical discrimination information. The DSM is applied to three typical cases of input distributional changes: 1) Uncertainty is completely eliminated, 2) Uncertainty range is increased by a factor of 10, and 3) Type of distribution is changed. For all three cases of application, the DSM-based importance ranking agrees very well with the observed changes of output distribution while other statistical parameters are shown to be insensitive.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.82-89
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• 2023

Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

• 한국컴퓨터정보학회논문지
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• 제16권12호
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• pp.59-69
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• 2011

최근 건강관리에 대한 국민의 관심이 높아지면서 헬스케어 서비스에 대한 인식과 이용률이 증가하고 있다. 하지만 기존의 헬스케어 서비스는 이동성의 불편함이 있으며, 정보입력의 신뢰성과 제공되는 정보의 정확성이 낮은 문제점을 가지고 있다. 본 연구는 이러한 문제점을 개선하여 스마트 폰을 활용한 m-Health 어플리케이션을 개발하였다. 이는 잘못된 생활습관으로 건강관리를 제대로 하지 못하는 20~30대를 대상으로 맞춤화된 식이추천, 심혈관 질환위험도 알림 등의 총 5가지 서비스를 제공한다. 또한 Importance-Performance Analysis(IPA)기법을 통해 일반적인 m-Health 서비스의 중요도와 본 서비스의 만족도를 비교분석하여 장점 및 문제점을 파악하였다. 개발된 어플리케이션의 IPA분석결과 m-Health 서비스를 효과적으로 제공받기 위해 필요한 12가지 항목 중 '정보 입력의 정확성 및 신뢰성', '컨텐츠 신뢰성', '건강에 적합한 서비스 추천' 등의 6가지 속성이 중요도와 만족도가 높은 영역에 속하였다. 그리고 '정보의 보안성'은 중요도는 높지만 만족도가 낮은 영역에 속하였다. 결론적으로 본서비스의 장점을 지속적으로 잘 유지하기 위해 Personal Heath record(PHR) 정보 연동과 함께 제공되는 서비스의 업 데이트 및 정보의 보안성 강화를 위한 연구를 진행할 예정이다.