• 제목/요약/키워드: evaluation models

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신제품 개발을 위한 통합 고객만족도 평가모델에 관한 실증적 연구 - 자동차 산업을 중심으로 - (An Empirical Study on the Integrated Customer Satisfaction Evaluation Model for New Product Development - Focused on Automobile Industry -)

  • 김동남;조재림
    • 품질경영학회지
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    • 제32권4호
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    • pp.113-124
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    • 2004
  • Customer satisfaction is becoming an increasingly salient topic in many firms and in academic research. One main rationale behind this interest is that customer satisfaction is believed to be associated with fruitful customer re-visit from the firm's point of view. Some country already had index models which can measure the degree of customer satisfaction. But, such models are ordinary models which used generally the scope of nation-wide /industry. Therefore, we needs some modifications to measure customer satisfaction for specific product & service and to provide the valuable feedback to specific firms. In this Perspectives, this study will evaluate the customer satisfaction index about automobile company and analyze it's result for valuable feedback. This study will present a model for an integrated customer satisfaction evaluation system which used structural equation modeling. Through this study, we anticipate that it will offer the measuring method about customer satisfaction and some guideline for product design process.

R & D 프로젝트의 위험분석모형의 연구 (A Risk Analysis Model Using VERT for R & D Project Management)

  • 황홍석
    • 한국경영과학회지
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    • 제20권1호
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    • pp.85-99
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    • 1995
  • Increasingly, risk analysis is becoming important ingredients in achieving the successful implementation and application in the area of the project management. The project management system is designed to manage or control the project resources on a given activity within time, cost and performance so called TPPM (Total Productive Project Management). In this research, a risk analysis model misproposed to identify potential problem areas, quantify the risks, and generated the chice of the action that can be taken to reduce the risk. In addition two analysis models are proposed : 1) risk factor model and 2) network simulation model using VERT (Venture Evaluation and Review Technique ). The objective of the remodels is to estimate the schedule, cost performance risks. These proposed quantitative models for project risk analysis are proving its value for the project managers who need to assess the risk of changes in cost, schedule, or performance. The proposed models will be used in the area of project selection, evaluation and the allocation of project resources.

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DEVSIF Composer: A Synthesis Tool for Fast Interpretation of Simulation Models

  • Lee, Wan-Bok
    • Journal of information and communication convergence engineering
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    • 제6권1호
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    • pp.59-63
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    • 2008
  • The methods or algorithms which can accelerate simulation speed became of great importance, as the modeling and simulation methodology for discrete event systems is used in many areas such as model validation/verification and performance evaluation. This paper proposes a tool named, DEVSIF composer. The tool is made of an automated compiled simulation technology and it builds a new composed model which can be executed much fast by composing the component models together. Models are described by our new specification language DEVSIF, which is compatible with object-oriented language and supports representation of a hierarchical model structure. Experimental results demonstrates that DEVSIF composer enhances the simulation speed of a transformed DEVS model 5 times faster than that of the original ones in average.

직사각형 공동 내부 자연연대류 문제에 대한 k-epsilon-vv-f 난류모델의 평가 (Evaluation of the K-Epsilon-VV-F Turbulence Model for Natural Convection in a Rectangular Cavity)

  • 최석기;김성오;김의광;최훈기
    • 한국전산유체공학회지
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    • 제7권4호
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    • pp.8-18
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    • 2002
  • The primary objective of the present study is evaluation of the k-ε-vv-f turbulence model for prediction of natural convection in a rectangular cavity. As a comparative study, the two-layer k-ε model is also considered. Both models, with and without algebraic heat flux model, are applied to the analysis of natural convection in a rectangular cavity. The performances of turbulence models are investigated through comparison with available experimental data. The predicted results of vertical velocity component, turbulent heat fluxes, turbulent shear stress, local Nusselt number and wall shear stress are compared with experimental data. It is shown that, among the turbulence models considered in the present study, the k-ε-vv-f model with an algebraic heat flux model predicts best the vertical mean velocity and velocity fluctuation, and the inclusion of algebraic heat flux model slightly improves the accuracy of results.

A comparative Study of ARIMA and Neural Network Model;Case study in Korea Corporate Bond Yields

  • Kim, Steven H.;Noh, Hyunju
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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    • pp.19-22
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    • 1996
  • A traditional approach to the prediction of economic and financial variables takes the form of statistical models to summarize past observations and to project them into the envisioned future. Over the past decade, an increasing number of organizations has turned to the use of neural networks. To date, however, many spheres of interest still lack a systematic evaluation of the statistical and neural approaches. One of these lies in the prediction of corporate bond yields for Korea. This paper reports on a comparative evaluation of ARIMA models and neural networks in the context of interest rate prediction. An additional experiment relates to an integration of the two methods. More specifically, the statistical model serves as a filter by providing estimtes which are then used as input into the neural network models.

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Large-Scale Integrated Network System Simulation with DEVS-Suite

  • Zengin, Ahmet
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권4호
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    • pp.452-474
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    • 2010
  • Formidable growth of Internet technologies has revealed challenging issues about its scale and performance evaluation. Modeling and simulation play a central role in the evaluation of the behavior and performance of the large-scale network systems. Large numbers of nodes affect simulation performance, simulation execution time and scalability in a weighty manner. Most of the existing simulators have numerous problems such as size, lack of system theoretic approach and complexity of modeled network. In this work, a scalable discrete-event modeling approach is described for studying networks' scalability and performance traits. Key fundamental attributes of Internet and its protocols are incorporated into a set of simulation models developed using the Discrete Event System Specification (DEVS) approach. Large-scale network models are simulated and evaluated to show the benefits of the developed network models and approaches.

Hybrid Fungal Genome Annotation Pipeline Combining ab initio, Evidence-, and Homology-based gene model evaluation

  • Min, Byoungnam;Choi, In-Geol
    • 한국균학회소식:학술대회논문집
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    • 한국균학회 2018년도 춘계학술대회 및 임시총회
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    • pp.22-22
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    • 2018
  • Fungal genome sequencing and assembly have been trivial in these days. Genome analysis relies on high quality of gene prediction and annotation. Automatic fungal genome annotation pipeline is essential for handling genomic sequence data accumulated exponentially. However, building an automatic annotation procedure for fungal genomes is not an easy task. FunGAP (Fungal Genome Annotation Pipeline) is developed for precise and accurate prediction of gene models from any fungal genome assembly. To make high-quality gene models, this pipeline employs multiple gene prediction programs encompassing ab initio, evidence-, and homology-based evaluation. FunGAP aims to evaluate all predicted genes by filtering gene models. To make a successful filtering guide for removal of false-positive genes, we used a scoring function that seeks for a consensus by estimating each gene model based on homology to the known proteins or domains. FunGAP is freely available for non-commercial users at the GitHub site (https://github.com/CompSynBioLab-KoreaUniv/FunGAP).

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사교에 작용하는 지진하중의 영향 평가 (Evaluation of Seismic Force Effects on Skew Bridges)

  • 박형기
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 1998년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Spring 1998
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    • pp.113-119
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    • 1998
  • This study is focused on evaluation of the structural behavior of skewed bridge during earthquake. The variation of natural frequencies and the lateral forces at pier shoes by the skewness and the rotational effect about vertical axis of skewed bridge due to seismic activity are analytically evaluated and identified through case studies. For this purpose, the composite steel girder highway bridges are selected as case study models. The seismic analyses by response spectrum method and time history method are performed for the selected models. It has been recognized that the frequency of longitudinal model increased as the skew angle decreased, while the lateral mode frequency showed the opposite trends. When the skew angle decreased, longitudina seismic forces of the bridge at the pier were increased but decreased in transverse direction. And it also has been found that the skewed bridges of the case study models showed the rotational behavior about vertical axis due to motion of San Fernando earthquake at Pacoima Dam.

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평가지표의 통계적 특성을 고려한 대학순위 결정 모형 (University Ranking Model Considering the Statistical Characteristics of Indicators)

  • 박영선
    • 대한산업공학회지
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    • 제40권1호
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    • pp.140-150
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    • 2014
  • University ranking models, though they consider multiple indicators to evaluate universities, determine the overall score of each university based on their own normalization and aggregation methods. Thus, the rankings provided by such models primarily depend on actual scores of evaluation indicators, but they are also significantly affected by the normalization and aggregation methods. We examine the normalization methods of four university ranking models used in South Korea, China, and United Kingdom. We discuss a possible unintended consequence of these methods, i.e., some universities who want to improve their rankings may focus on unnecessary indicators, contrary to the evaluator's intension, due to the normalization methods. We suggest a new normalization method based on the statistical characteristics of the distribution of each evaluation indicator so that the new method can motivate the universities to move into the desirable directions intended by the evaluator.

A Comparative Study on the Spatial Statistical Models for the Estimation of Population Distribution

  • Oh, Doo-Ri;Hwang, Chul Sue
    • 한국측량학회지
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    • 제33권3호
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    • pp.145-153
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    • 2015
  • This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density