• Perspectives in Nursing Science
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• 제13권2호
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• pp.81-87
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• 2016

Purpose: The aim of this study is to review the nurse demand forecasting methods in empirical studies published during 1991~2014 and suggest ideas to improve the validity in nurse demand forecasting. Methods: Previous studies on nurse demand forecasting methodology were categorized into four groups: time series analysis, top-down approach of workforce requirement, bottom-up approach of workforce requirement, and labor market analysis. Major methodological properties of each group were summarized and compared. Results: Time series analysis and top-down approach were the most frequently used forecasting methodologies. Conclusion: To improve decision-making in nursing workforce planning, stakeholders should consider a variety of demand forecasting methods and appraise the validity of forecasting nurse demand.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.224-229
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• 2009

Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

• 가정과삶의질연구
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• 제6권1호
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• pp.95-116
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• 1988

this study has dual purposes; one is to develope a new theoretical framework in consumer behavior area by applying the human ecological approach, and the other is to test the theory empirically area by applying the human ecological approach, and the other is to test the theory empirically by examining prepurchasing behavior of housing. Research methods adopted in this study are library search and survey research with self-administered questionnaires. The statistical methods used in the survey research are factor analysis, chi square test, and multivariate analysis with crosstablulations. According to the human ecological approach, ecological environments are important sources of consumer needs which , in turn, are satisfied by purchasing behavior in the market. Within this theoretical framework, consumers con improve the quality to life by perceving clearly what their needs are thereby making the most possible efficient purchasing decision making. The major findings of the empirical research on the basis of the theoretical framework are as follows; 1) Housing needs significantly vary with different ecological environment. 2) consumer information search behavior does not differ significantly by housing needs. 3) Housing needs turn out to be an intervening variable between ecological environments and consumer information search behavior. the results of this study show that the human ecological approach is useful in consumer behavior studies. The empirical result that consumer needs are not significantly satisfied by consumer behavior suggests a now direction in consumer education.

• Asia Marketing Journal
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• 제8권1호
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• pp.1-17
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• 2006

다양한 선행연구에서 준거가격효과는 실증적 지지를 받아온 것이 사실이다. 그러나 대부분의 선행연구에서 간과된 부분은 설명되지 않은 소비자 반응의 이질성이 준거가격에 반영되어 실재하지 않는 효과가 마치 유의한 것으로 나타날 수도 있다는 것이다(Chang, Siddarth, and Weinberg 1999; Bell and Lattin 2000). 또 다른 차원의 이질성으로서, 고려상표군의 이질성이 반영되지 않을 경우 모델에 포함된 변수의 모수추정치에 왜곡현상이 나타날 수 있음을 Meyer and Kahn(1991)이 지적한 바 있다. 이러한 선행연구의 문제점을 고려하여 이 연구에서는 반응의 이질성과 고려상표군의 이질성을 모두 반영한 모델을 적용함으로써 보다 정확한 준거가격효과의 추정을 시도하였다. 또한 소비자별 고려상표군의 이질성을 반영한 준거가격 측정치를 새롭게 제안하여 검증하고자 하였다. 실증분석결과, 제안된 준거가격 측정치가 선행연구에서 사용한 측정치에 비해 모델적합도와 예측타당성을 향상시키는 것으로 나타났다. 이 결과는 준거가격 형성과정에도 고려상표군의 이질성이 반영됨을 실증하는 것이다. 고려상표군의 이질성이 반영될 경우, 선행연구의 준거가격 측정치에 비해서, 제안된 준거가격 측정치의 평균이 높게 나타났으며, 표준편차는 감소한 것으로 나타났다. 이 연구에서 제안된 측정치의 실제적인 적용 측면을 본다면, Greenleaf(1995)의 연구에서처럼, 최적의 가격정책이 손실회피(loss aversion)의 크기, 즉, 준거의존(reference-dependent) 모델상의 준거가격에 의존한다면 제안된 측정치가 유용하게 사용될 수 있을 것으로 판단된다. 최대화해야 할 이익함수에 포함된 준거가격 측정치의 정확성이 최적가격결정을 좌우하기 때문이다. 따라서, 준거가격모델에 근거하여 최적가격을 추정할 경우, 모델자체에 고려상표군과 반응의 이질성을 반영할 뿐만 아니라, 준거가격 측정치 또한 고려상표군의 이질성을 반영하는 것이 바람직할 것으로 판단된다.

• 한국문헌정보학회지
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• 제32권4호
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• pp.53-67
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• 1998

이 연구에서는 실험변수 및 그 통계적 관계를 문서 색인과 검색에 이용하는 가능성을 타진하고 평가하였다. 이를 위해 실험변수검색시스템(Empirical Fact Retrieval System: EFRS)과 유사기존검색시스템(Simulated Traditional Retrieval System: TRS)이라 명명한 두 시스템을 구축, 제한된 질의를 놓고 검색한 결과를 비교 분석하여 보고했으며, 실험변수검색시스템이 가진 잠재적 장점을 전반적으로 고찰하고 관련된 제반 문제들을 논의하였다.

• Steel and Composite Structures
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• 제33권2호
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• pp.181-194
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• 2019

This paper presents an efficient approach to generate a new empirical formula to predict the axial compression capacity (ACC) of circular concrete-filled tube (CCFT) columns using the artificial neural network (ANN). A total of 258 test results extracted from the literature were used to develop the ANN models. The ANN model having the highest correlation coefficient (R) and the lowest mean square error (MSE) was determined as the best model. Stability analysis, sensitivity analysis, and a parametric study were carried out to estimate the stability of the ANN model and to investigate the main contributing factors on the ACC of CCFT columns. Stability analysis revealed that the ANN model was more stable than several existing formulae. Whereas, the sensitivity analysis and parametric study showed that the outer diameter of the steel tube was the most sensitive parameter. Additionally, using the validated ANN model, a new empirical formula was derived for predicting the ACC of CCFT columns. Obviously, a higher accuracy of the proposed empirical formula was achieved compared to the existing formulae.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2166-2176
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• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• 지식경영연구
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• 제18권1호
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• pp.67-81
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• 2017

As the important breakthrough continues in the field of machine learning and artificial intelligence recently, there has been a growing interest in the analysis and the utilization of the big data which constitutes a foundation for the field. In this background, while the economic value of the data held by the corporates and public institutions is well recognized, the research on the evaluation of its economic value is still insufficient. Therefore, in this study, as a part of the economic value evaluation of the data, we have conducted the economic value measurement of the data generated through the small business guarantee program of Korean Federation of Credit Guarantee Foundations (KOREG). To this end, by examining the previous research related to the economic value measurement of the data and intangible assets at home and abroad, we established the evaluation methods and conducted the empirical analysis. For the data value measurements in this paper, we used 'cost-based approach', 'revenue-based approach', and 'market-based approach'. In order to secure the reliability of the measured result of economic values generated through each approach, we conducted expert verification with the employees. Also, we derived the major considerations and issues in regards to the economic value measurement of the data. These will be able to contribute to the empirical methods for economic value measurement of the data in the future.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.775-786
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• 2002

In this paper, we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. The design and weighting effects were calculated for estimates produced from the 1998 small firm survey data. We considered the design and weighting effects on coefficients estimates of regression model using the design-based approach and the GEE approach.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회논문집(I)
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• pp.235-240
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• 2000

Although dapped-end beams are widely used in bridge and building structures, there are not any specific and reasonable design regulations on dapped-end beams. In this study, the validity of the suggested experimental and empirical design methods, conventional strut-tie model approach, and nonlinear strut-tie model approach is evaluated through the analysis of dapped-end beams tested to failure. The nonlinear strut-tie model approach proved to be the most suitable method for dapper-end beam design.