• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.471-480
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• 2010

The purpose of this study is to explore determinants which affect the significant increase in the user acceptance of smart phone. This study also analyzes the effect of each variable on the actual acceptance by empirical methods. In this study, first, the system quality and the service quality are defined as independent variables based on developed IS success model of DeLone & McLean(2003). Second, we proposed the research model by providing trust and perceptual immersion as intermediate variables, and user satisfaction and actual use as dependent variables by the proceeding research for accepting information technology and new service. Third, the statistical analysis is conducted by surveying to 200 smart phone users for verifying a validity of research models and hypotheses. As a result, almost hypotheses are accepted in confidence interval except for the hypothesis between security and trust variable.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.657-669
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• 2019

To estimate accurate design quantiles considering statistical characteristics of hydrological data is one of the most important procedures in the design of hydraulic structures. While at-site frequency analysis estimates design quantile using observed data at a site of interest, regional frequency analysis (RFA) utilizes a number of sites included in a hydrologically homogeneous region. Therefore, RFA could provide a more accurate design quantile at ungauged site or sites with short observation period. In this review article, RFA is classified into stationary RFA and nonstationary RFA depending on the characteristic of hydrological data, and the basic concept, procedure, and application of each technique are explained in detail focused on the index flood method. Additionally, a review of the state of the art for RFA procedure is presented. This paper is finalized by describing the stationary regional rainfall frequency analysis over South Korea contained in the amendment of "Standard guidelines for design flood estimation" and various future study topics related to nonstationary RFA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.47-54
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• 2019

In this paper, we consider a constant modulus (CM) based blind adaptive receiver design for downlink multi-carrier code-division multiple access (MC-CDMA) systems employing simple space-time block coding (STBC). In the paper, filter weight vectors used for the detection of the transmitted symbols are partitioned into its subvectors and then, special relations among the optimal subvectors minimizing the CM metric are derived. Using the special relations, we present a modified CM metric and propose a new blind adaptive stochastic-gradient CM algorithm (SG-CMA) by minimizing the modified CM metric. The proposed blind adaptive SG-CMA has faster convergence rate than the conventional SG-CMA because the filter weight vectors of the proposed scheme are updated in the region of satisfying the derived special relations. Computer simulation results are given to verify the superiority of the proposed SG-CMA.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.35-42
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• 2021

In order to produce electric vehicle demand forecasting information, which is an important element of the plan to expand charging facilities for electric vehicles, a model for predicting electric vehicle demand was proposed using Exponential Smoothing. In order to establish input data for the model, the monthly power demand of cities and counties was applied as independent variables, monthly electric vehicle charging stations, monthly electric vehicle charging stations, and monthly electric vehicle registration data. To verify the accuracy of the electric vehicle power demand prediction model, we compare the results of the statistical methods Exponential Smoothing (ETS) and ARIMA models with error rates of 12% and 21%, confirming that the ETS presented in this paper is 9% more accurate as electric vehicle power demand prediction models. It is expected that it will be used in terms of operation and management from planning to install charging stations for electric vehicles using this model in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.1-11
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• 2019

Based on the knowledge spillover theory of entrepreneurship(KSTE) and resource based view(RBV), this study examines that how patent based entrepreneurship impacts on improving key performances such as financing, firm innovation, sales, product selling growth, employment. This study which is conducted with data from 353 startup firms indicates that patent based entrepreneurship has positive effects on performance of financing, innovation, product selling growth, and employment. On the other hand, there is no effect of patent-based entrepreneurship on sales performance. This statistical results were the same The results were the same when the independent variables were measured as intensity of patent based entrepreneurship which indicates the rate of patent based product or service among total number of product or service of the startup company.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.55-63
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• 2019

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.165-168
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• 2014

A Meta-analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. Recently, the convergence of knowledge-based society and information telecommunication technologies has a rapid impact on politics, economics and various fields. We conducted a meta-analysis and review of between perceived value, risk and behavioral intention on e-commerce researches. This study focused a total of 25 research papers that established causal relationships in between perceived value, risk and behavioral intention on e-commerce published in Korean academic journals during 2000 and 2014. The result of the meta-analysis might be summarized that the effect size in the path from the perceived value to the behavioral intention with the effect size 0.508. Also, it showed that the effect size in the path from perceived value to the behavioral intention with the effect size -0.251. Based on these findings, several theoretical and practical implications were suggested and discussed with the difference from previous researches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.194-196
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• 2014

A Meta-analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. Recently, the convergence of knowledge-based society and e-commerce, information telecommunication technologies has a rapid impact on politics, economics and various fields. We conducted a meta-analysis and review of between satisfaction, trust and loyalty on e-commerce researches. This study focused a total of 57 research papers that established causal relationships in between satisfaction, trust and loyalty on e-commerce published in Korean academic journals during 2002 and 2013. The result of the meta-analysis might be summarized that the highest effect size in the path from the satisfaction to the trust with the effect size(0.591). Based on these findings, several theoretical and practical implications were suggested and discussed with the difference from previous researches.

• Journal of the Korea Institute of Building Construction
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• v.19 no.4
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• pp.341-350
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• 2019

Construction industry is one of the most dangerous industry. As the construction accidents occur due to the repeated factors found in each accidents, there is a limitation in analyzing all types of occupational accidents by the existing descriptive analysis and statistical test. In this study, we classified safety accidents caused by falling objects among the accident types occurring at construction sites into fatal and nonfatal accidents and deduced the factors. In addition, we deduced the association rules among the safety accidents factors caused by falling objects through the association rule analysis method among the machine learning techniques. Therefore, considering the association rules for fatal and nonfatal accidents proposed in this study, it would be possible to prevent accidents by searching for countermeasures against safety accidents caused by falling objects.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.173-181
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• 2019

To estimate probabilistic distribution function from experimental data, kernel density estimation(KDE) is mostly used in cases when data is insufficient. The estimated distribution using KDE depends on bandwidth selectors that smoothen or overfit a kernel estimator to experimental data. In this study, various bandwidth selectors such as the Silverman's rule of thumb, rule using adaptive estimates, and oversmoothing rule, were compared for accuracy and conservativeness. For this, statistical simulations were carried out using assumed true models including unimodal and multimodal distributions, and, accuracies and conservativeness of estimating distribution functions were compared according to various data. In addition, it was verified how the estimated distributions using KDE with different bandwidth selectors affect reliability analysis results through simple reliability examples.