• IE interfaces
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• v.20 no.3
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• pp.387-394
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• 2007

Numerous countries promote business programs to revitalize local economy, increase employment, and nurture high-tech industries. Recently, a number of business incubators have been established and operated with aims to adapt to changing environment and increase economic competitiveness in Korea. To give satisfactory results of governmental policy, the requirement to develop the evaluation model to support effective operations of business incubators using the objective and rational criteria is growing. The purpose of this study is to develop evaluation model in Business Incubator using Data Mining Process. We suggested the evaluation model of business incubator, 'Score-5 RS' consists of making evaluation factor process using weighted sum and 5-grade classification and analyzing process by Decision Tree algorithm.

• Nuclear Engineering and Technology
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• v.35 no.1
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• pp.35-44
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• 2003

The neutron induced nuclear data for Eu-153, Gd-155 and Cd-157 are calculated and evaluated in the high energy region. The evaluation procedure for deformed nuclei is setup by using Ecis-Empire codes. The energy dependent optical model potential parameters are searched based on the recent experimental data and applied up to 20 MeV. Optical model, full featured Hauser-Feshbach model and multistep direct and multistep compound model are used in the calculation. The direct-semidirect capture model and the direct coupled-channels contribution to discrete levels are introduced to improve the capture and inelastic scattering cross sections. The theoretically calculated cross sections are compared with the experimental data and the evaluated files. The model-calculated total and capture cross sections are in good agreement with the reference experimental data. The evaluated cross section results are compiled to ENDF-6 format and are expected to improve the ENDF/B-Vl.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.533-545
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• 2014

According to the evolving of IT technologies, the amount of data we are facing increasing exponentially. Thus, the technique for managing and analyzing these vast data that has emerged is a distributed processing system of big data. A quality evaluation for the existing distributed processing systems has been proceeded by the structured data environment. Thus, if we apply this to the evaluation of distributed processing systems of big data which has to focus on the analysis of the unstructured data, a precise quality assessment cannot be made. Therefore, a study of the quality evaluation model for the distributed processing systems is needed, which considers the environment of the analysis of big data. In this paper, we propose a new quality evaluation model by deriving the quality evaluation elements based on the ISO/IEC9126 which is the international standard on software quality, and defining metrics for validating the elements.

• Journal of the Korean housing association
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• v.2 no.1
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• pp.69-76
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• 1991

It is the purpose of this study to abtain a basic information about how the users evaluate housing environment. The structural model of housing environment which is employed Repertory Grid Developmental Method is extracted. This model Is composed of 4 classifications : 1) psychological evaluation, 2) visual evaluation, 3) variation, 4) spaciousness.The extracted model can be expected to be used as follows : 1) It is to provide the knowlege of user's evaluation of housing enironment with designers so that they can explore the optimum solution in environ-mental design. 2) It will be an useful data for selecting an evaluation item in psychological evaluation study using SD(Semantic Differential)method. 3) On the physical experiments, it will be an useful data to select an evaluation item.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.769-776
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• 2006

It is important for evaluation execution about technology development. And it is necessary to settle together with technology development activity to evaluation execution. Purpose of this paper is to decide request for proposal and suitable to proposed enterprise contents about technology part in performance. Therefore let estimate the data about it. So suitable enterprise is selected through applying evaluation data to TEPM(Technology Evaluation Process Model).

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.41-47
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• 2019

In this paper, we propose a new batter evaluation model that reflects the skill of the opponent pitcher in Korean professional baseball. The model consists of evaluation factors such as Run Value, Contribution Score and Ball Consumption considering the pitcher grade. These evaluation factors are calculated as different data. In order to include the evaluation factors having different characteristics into one model, each evaluation factor is weighted and added. The genetic algorithms were used to calculate the weights, and the data were based on the 2016 records of Korea Professional Baseball and the salary data of the players of 2017. As a result of calculation of the weight, the weight of the Run Value was high and the weight of the Contribution Score was very low. This means that when calculating the annual salary, it reflects much of the expected score according to the batting result of the batter. On the other hand, the contribution score indicating the degree to which the batting result contributed to the victory of the team according to the state of the economy is not reflected in the salary or point system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.95-96
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• 2014

These information systems projects have unique characteristics such as technology sensitiveness, network effectiveness, embeddedness, and externality, these investment projects have been not taken care of in the field of administration and evaluation. Furthermore, it is not easy to evaluate the results of projects under the circumstances where the conditions for evaluation of budget, time, and data leave much to be desired. But the efficient monitoring and effective analysis of information systems are surely needed for beneficient results of investment in information systems. We propose an effect evaluation model on the basis of restriction to evaluate information systems.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.209-216
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• 2003

Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.185-187
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• 2011

The purpose of this study is to develop and apply the oversea construction competitiveness evaluation model which measures the competitiveness of construction companies in global construction market. This model consists of the design and construction competitiveness indexes by ENR statistic data and provides the oversea construction competitiveness index based on the evaluation model.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.