• Journal of Information Technology Services
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• v.8 no.1
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• pp.59-71
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• 2009

Korean government has operated EA by the act on efficient introduction of information system and operation. etc. But the utilization and the evaluation system for EA don't prepare well. In this study. we analyzed characteristics and advantages of EA maturity models that is developed by some domestic and foreign government departments in logical view. and then we derive evaluation scopes and factors of the models. Also. we applied the models to EA maturity for the B organization and measured maturity levels. We identify similarity and difference between the models. We propose evaluation scopes, levels and factors between the models and solutions for evaluation ambiguity by evaluators and maturity improvement through the identified results.

• Journal of Information Technology Applications and Management
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• v.13 no.1
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• pp.17-38
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• 2006

Recently, ASP business models based on Web services are attracting considerable attention and regarded as the next generation of the ASP business models. It is, however, undesirable for ASP users to adopt them simply because the Web services are the new trend in the IT world. Instead, an in-depth comparison of the benefits against the costs between the Web services based ASP business models and the traditional models are required. Furthermore, it is desirable that this comparative analysis should be applied from the ASP users' viewpoints rather than those of the government or ASP providers. So, we have applied a comparative ROI (Return on Investment) analysis from the ASP users' perspective and shown that the Web services based ASP business models (382%) are superior to the traditional models (280%) in terms of ROI. We have also employed Balanced Scorecard (BSC) framework to keep the balance between tangible and intangible benefits considering the characteristics of IT value measurement.

• IE interfaces
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• v.18 no.4
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• pp.418-430
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• 2005

We establish an efficient strategy for construction and operation of data consolidation center for multi-organization in public sector. First, we introduce important concepts on data consolidation center in public sector, and draw some success factors by analyzing several foreign and domestic cases. Second, we construct all the possible logical operational models of the center and investigate the properties and feasibility of the models. Third, we suggest a virtual operational environment for the two representative models selected by feasibility criteria among the possible logical models, and compare the two models in terms of operational cost. We also utilize AHP methodology to evaluate qualitative opinions on the two models from several experts in public information systems. As a result, we find the best alternative is the case in which all infrastructure and facilities for the center are provided by government, and common essential IT operations are integrated, associated data are consolidated and the whole operational work are outsourced to specialized IT operations service providers.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.31-45
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• 2013

PURPOSES : Determination of particle packing model variables that can be used for formulation of new DEM based particle packing model by examining existing particle packing models METHODS : Existing particle packing models are thoroughly examined by analytical reformulation and sensitivity analysis in order to set up DEM based new particle packing model and to determine its variables. All model equations considered in this examination are represented with consistent expressions and are compared to each others to find mathematical and conceptual similarity in expressions. RESULTS : From the examination of existing models, it is observed that the models are very similar in their shapes although the derivation of the models may be different. As well, it is observed that variables used in some existing models are comprehensive enough to estimate particle packing but not applicable to DEM simulation. CONCLUSIONS : A set of variables that can be used in DEM based particle packing model is determined.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.79-89
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• 1997

In order to reduce the outbreaks of short-term high concentrations and its impacts, we developed the models which predicted tomorrow's maximum hourly concentrations of $O_3$, TSP, SO$_2$, NO$_2$ and CO. Statistical methods like multi regressions were used because it must be operated easily under the present conditions. 47 independent variables were used, which included observed concentrations of air pollutants, observed and forcasted meteorological data in 1994 at Seoul and its surrounding areas. We subdivided Seoul into 4 areas coinciding with the present ozone warning areas. 4 kinds of seasonal models were developed due to the seasonal variations of observed concentrations, and 2 kinds of data models for the unavailable case of forecasted meteorological data. By comparing the $R^2$and root mean square error(hearafter 'RMSE') of each model, we confirmed that the models including forecasted data showed higher accuracy than ones using observed only. It was also shown that the higher the seasonal mean concentrations, the larger the RMSE. There was no distinct difference between the results of 4 areal models. In case of test run using 1995's data, the models predicted well the trends of daily variation of concentrations and the days when the possibility of outbreak of high concentarion was high. This study showed that it was reasonable to use those models as operational ones, because the $R^2$ and RMSE of models were smaller than those of operational/research models such as in South Coast Air Basin, CA, USA.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.275-287
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• 2015

Information technology (IT) convergence have been recognized one of the key drivers in the industry perspective. Especially, IT convergence have been one of the most important innovative way for defense sector. Korea government established IT convergence policy in 2008 and have been applying it to the core industry such as automotive, shipbuilding and defense industries. Recently, the creative vitamin project has been launched. Vitamin 'D' means the way to create the value of defense industry. This research analyzes and evaluates various IT convergence business models based on an operation of defense IT convergence center from 2011 to 2014, which is the industry IT convergence centers. Defense IT convergence business models can be classified into four types of mission area as follows : weapon acquisition and management, military intelligence, military power construction, and resources management. We define the concept of defense IT convergence and describe the framework and processes for applying IT to the defense sector. We analyzes and evaluates various business models designed through defense IT convergence framework and processes.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.99-110
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• 1999

This study deals with the adaptability questions of O-D table estimation models. Its objectives are two-fold; (1) to estimate the characteristics of various O-D table estimation models(i.e. linear regression models. entropy models and statistic models) and (2) to find the model which estimates the O-D table with the best accuracy under the various data conditions. In Pursuing the above, this study gives the particular attentions to the test of the models, using the Sioux Falls network and equilibrium assignment method of MINUTP. The major findings are the followings. Firstly. it finds that the statistic models have the most goodness of fat among all models, if the required data are all Prepared. But it Presents that statistic models are the most sensitive against the underspecification and inconsistency problems of link data. Secondly, It shows that the linear regression models have the worst goodness of fat among all models. But the linear regression models are the most insensitive to the underspecification and inconsistency problems. Thirdly, THE/1 model of entropy model is sensitive against the underspecification and incon-sistency problems, but THE/2 model is insensitive. Finally, other informations like total volume, zonal Production and attraction volumes in 0-D table, help models to gain the better goodness of fit. Especially, in the statistic models. both the zonal production and attraction volume data are helpful to estimate the link volumes. It can be expected that the results dive some implications not only to the selection of optimal model under the various given data, but also to the development or modification of model.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1322-1327
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• 2004

There are some previous studies that utilize constant impedance models or constant current models for electric trains to perform the static analysis of AT feeding systems. These mentioned models have some merits of linear systems but yield erroneous results because of the innate restraints of the models since linear models cannot represent the features of constant power in inverter-driven trains. From these reasons, it is suitable that the train be considered as a constant load model when it drives or as a constant source model when it applies regenerative brake. However, excessive rise of regenerative voltage during the braking may damage the vehicle itself and the feeding systems so the voltage must be restricted below a certain value. Keeping these facts in minds, we suggest new methods of analyzing AT feeding systems using the constant power models with the conditions of voltage constraints. The simulation results from a sample system using the proposed method illustrate both the states of system variables and the supply-demand relation of power among the trains and the systems very clearly, so it is believed that the proposed method yields more accurate results than conventional methods do.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.19-33
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• 1998

The primary objective of this research was to develop optimal models for masking the road traffic noise with the sound of a waterfall at urban small green spaces. Noise levels were measured at 8 roadside green spaces in SEOUL and questionnaires were randomly distributed to 40 users for evaluating the noise at each site at the same time. College students participated in the experiment for the development of masking models and the developed models were tested by users at 2 green spaces. The major results are as follows ; 1. Traffic noises ranged from 65dBto 70 dB. Users' satisfaction with the noise became considerably low on the basis of 60 dB and it was highly related to noise level. 2. Noise was a main factor to depreciate the amenity of green spaces where its level was more than 60 dB and so it neds to be excluded or reduced the traffic noise at the process of design. 3. Masking effects kept constant independent of the spatial location of masker on condition that masker levels were equal. It was effective when masker was 5-10dB greater than noise level which was masked. 4. As noise level went up, satisfaction ratings about the masked noise became low but masking effects increased in proportion to its level. 5. It was proved that the models were valid through the field experiment.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.