• Survey Research
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• v.6 no.1
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• pp.1-38
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• 2005

Considering the importance of corruption index measurement model and the diffusion of popular awareness about the importance of anti-corruption, this research compared and analyzed existing corruption index measurement models. This paper has selected "Anti-Corruption Index model(ACI model)" that was developed by Seoul Development Institute and "CCEJ's Corruption Index model" which is under use by the Citizens' Coaltion for Economic Justice. These two models were analyzed in terms of appropriateness of 'the indicator and index choice method', 'the research design' and 'the use of statistical data'. This analysis shows that two models have some problems. First, at the level of indicator and index choice method, the indicators of CCEJ's corruption index model is too atomized and redundant. As not putting weight of indicator, it did not consider importance of each indicator. Citizens who evaluated the level of corruption didn't participate in the weight evaluation team, which results in failure of the model to reflect the citizens' opinion. Also, because the question about Seoul Metropolis' corruption level is not included, it is not detected difference between real corruption level and perceptive corruption level. Second, in terms of appropriateness of research design, the sample of the CCEJ' corruption index model is too small to get credibility. The objectivity of research method seems to be low because survey was performed by exit interview. In addition, 38 items are overfull in the questionnire of CCEJ's corruption index model compare to 13 items in ACI model. Also, in making up questions, the terms are redundant and unobvious. Third, in regarding with feasibility of the statistical data, the CCEJ's corruption index model uses regulation data for disciplinary punishment of 25 local governments in Seoul from 1995 to 1999. But, it is common ideas of scholars that statistical data indicates the tip of an iceberg in corruption. So for using a statistical data, it needs a data of enough quantity and has a high level credibility. In addition, objective method of giving weight is not developed. In this point of view, the use of statistical data has some limits. To solve this problem, ① objective data should be included in the indicators, ② various indicators should be developed and ③ a method of giving weight should be improved.

• Journal of the Korean Society of Safety
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• v.28 no.2
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• pp.78-83
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• 2013

The traffic culture index is used as a major index in evaluating the traffic safety services of local governments and also serve as important data for the planning and implementation of traffic safety services. However, as the traffic culture index gradually became a standard for comparison among local governments, in part, certain cases arose which questioned the grounds for selecting variables for the index and the validity of the index in terms of its influential relationship between evaluation items. This study analyzed the index's influential relationship by utilizing a PLS structural equation model based on the evaluation results of the 2011 traffic culture index. A variable-linking model was created which recognized the relativity taking into account of the indirect effects between latent variables and this model was proven to be a model suitable in explaining the traffic culture index with a 97.8% explanation power. It was found that traffic safety(0.530), driving behavior(0.527), pedestrian behavior(0.187) and vulnerable road users(0.147), in such order, had an effect on the traffic culture index. It was also found that human casualties due to traffic accidents under "traffic safety" and traffic light compliance rate under "driving behavior" had an important effect. The study showed that motor vehicle share in illegal parking in school zones did not have a valid explanation power regarding "vulnerable road users".

• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.524-528
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• 2006

This study was performed to develop experimental model for milling degree and whiteness from analysis the CBB (colored bran balance) index using NMG dying and image processing. The endosperm layer increased and the pericarp, aleurone layer and CBB index decreased as the milling degree and whiteness increased. So, CBB index was closely linked to milling degree and whiteness. A empirical CBB index model was developed according to the milling degree and whiteness. The model were found to fit adequately to all test data with a coefficient of determination of 0.99, and therefore the CBB model proved to be quite applicable.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.153-166
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• 2003

This study presents the time-divided forecasting model to integrate evolutionary optimization algorithm and change point detection based on artificial neural networks (ANN) for the prediction of (Korea) stock price index. The genetic algorithm(GA) is introduced as an evolutionary optimization method in this study. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as optimal or near-optimal change point groups, and to use them in the forecasting of the stock price index. The proposed model consists of three phases. The first phase detects successive change points. The second phase detects the change-point groups with the GA. Finally, the third phase forecasts the output with ANN using the GA. This study examines the predictability of the proposed model for the prediction of stock price index.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.467-476
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• 2013

Site index information given from forest site map only exist in the sampled locations. In this study, site index for unsampled locations were estimated using kriging interpolation method which can interpolate values between point samples to generate a continuous surface. Site index of Pinus densiplora in Danyang area were calculated using Chapman-Richards model by plot unit. Then site index for unsampled locations were interpolated by theoretical variogram models and ordinary kriging. Also in order to assess parameter selection, cross-validation was performed by calculating mean error (ME), average standard error (ASE) and root mean square error (RMSE). In result, gaussian model was excluded because of the biggest relative nugget (37.40%). Then spherical model (16.80%) and exponential model (8.77%) were selected. Site index estimates of Pinus densiplora throughout the entire area in Danyang showed 4.39~19.53 based on exponential model, and 4.54~19.23 based on spherical model. By cross-validation, RMSE had almost no difference. But ME and ASE from spherical model were slightly lower than exponential model. Therefore site index prediction map from spherical model were finally selected. Average site index from site prediction map was 10.78. It can be expected that regional variance can be considered by site index prediction map in order to estimate forest biomass which has big spatial variance and eventually it is helpful to improve an accuracy of forest carbon estimation.

• Journal of Power System Engineering
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• v.11 no.3
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• pp.66-72
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• 2007

This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.739-745
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• 2010

This paper computes the repurchase index based on statistical modeling. Using the transaction record of a certain product, the repurchase index is obtained by fitting the Poisson regression model. The customers are classified into 5 groups based on the index giving the information about the propensity to repurchase.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.543-556
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• 2001

This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.202-206
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• 2015

Site index curves were developed for Larix kaempferi and Pinus koraiensis in Gangwon and North Gyeongsang provinces in Korea. For the development of site index, Schumacher and Chapman-Richards model were applied using the data collected from 2012 to 2014. Base age was set to 40 years for Larix kaempferi and Pinus koraiensis in site index of this study. Coefficient of determination and root mean square error of site index models were provided by species, and the models were compared with the previous studies to check the suitability. Overall, site index models developed in this study fitted in the current data well. Thus, the site indexes are considered to be properly used in Gangwon and North Gyeongsang provinces.