• Journal of Korea Game Society
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• v.18 no.3
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• pp.17-26
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• 2018

As the concept of experience economy has been accelerated recently, user experience is more emphasized today, most of all. And related representative keywords are gamification. Gamification characterized by that intangible elements are produced and consumed through various interactions between providers and users and by having a structure that is difficult to generalize and objectify to economic value. Therefore, the purpose of the present study is to develop a quantitative valuation indicator of concept and standardize the valuation formula covering economic value for gamification technology and overall framework from the perspective of evaluating economic values of intangible technologies such as of knowledge, design, contents, and service of a company.

• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.73-84
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• 2005

A three layered neural network model was developed using back propagation algorithm to estimate the UU undrained shear strength of Korean soft soil based on the database of actual undrained shear strengths and piezocone measurements compiled from 8 sites over the Korea. The developed model was validated by comparing model predictions with measured values about new piezocone data, which were not previously employed during development of model. Performance of the neural network model was also compared with conventional empirical methods. It was found that the number of neuron in hidden layer is different for the different combination of transfer functions of neural network models. However, all piezocone neural network models are successful in inferring a complex relationship between piezocone measurements and the undrained shear strength of Korean soft soils, which give relatively high coefficients of determination ranging from 0.69 to 0.72. Since neural network model has been generalized by self-learning from database of piezocone measurements and undrained shear strength over the various sites, the developed neural network models give more precise and generally reliable undrained shear strengths than empirical approaches which still need site specific calibration.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.411-418
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• 2018

With the proliferation of artificial intelligence technology, it is becoming important to obtain, store, and utilize scientific data in research and science sectors. A number of methods for extracting meaningful objects such as graphs and tables from research articles have been proposed to eventually obtain scientific data. Existing extraction methods using heuristic approaches are hardly applicable to electronic documents having heterogeneous manuscript formats because they are designed to work properly for some targeted manuscripts. This paper proposes a prototype of an object extraction system which exploits a recent deep-learning technology so as to overcome the inflexibility of the heuristic approaches. We implemented our trained model, based on the Faster R-CNN algorithm, using the Google TensorFlow Object Detection API and also composed an annotated data set from 100 research articles for training and evaluation. Finally, a performance evaluation shows that the proposed system outperforms a comparator adopting heuristic approaches by 5.2%.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.415-425
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• 2017

The purpose of this study is to examine the effect of perceived enjoyment and user's characteristics on the intention of continuous use when users play social network games on a mobile device. In addition, the study empirically investigated the mediating effect of flow experience in this process. To fulfill the purpose, this study conducted a survey on 244 college students and collected data. When the collected data was analyzed, the followings were known. First, perceived enjoyment, and both self-efficacy and innovation propensity of user's characteristics turned out to have a positive (+) effect on the intention of continuous use in mobile social network game. Second, in the process, it was known that flow experience played a mediating role. These findings are expected to be useful data in developing game contents of high quality or making a marketing strategy for continuous improvement of online social network game industry. In addition, future studies are expected to generalize the research to various age groups.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.97-111
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• 1998

This paper suggests a Bayesian method for testing first-order markov correlation among linear regression disturbances. As a Bayesian test criterion, Bayes factor is derived in the form of generalized Savage-Dickey density ratio that is easily estimated by means of posterior simulation via Gibbs sampling scheme. Performance of the Bayesian test is evaluated and examined based upon a Monte Carlo experiment and an empirical data analysis. Efficiency of the posterior simulation is also examined.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.228-228
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• 2016

증발산량은 수자원 부존량 평가, 물수지 분석, 지구의 물순환 및 에너지 순환을 이해하기 위해서 알아야할 수문량이나, 이를 산정하기 위하여 단순한 가정을 하거나 경험식을 사용하는 접근에는 신뢰성에 문제가 생긴다. 본 연구에서는 아시아 지역내의 여러 지점에서 에디공분산 시스템을 활용해 플럭스 자료를 구축해놓은 Asia Fluxnet의 자료를 활용해 보완관계법(Complimentary relationship) 기반으로 제한된 기상자료를 이용해 구한 증발산량을 산정하는 방법론들을 평가하였다. Granger and Gary(GG)는 실제 증발산량은 습윤조건의 증발산량의 2배에 잠재 증발산량간의 차와 같다는 보완관계를 수정하여 일반화하고, 잠재 증발산량을 산정하는 경험식을 제시하였다. 이러한 수정된 보완관계식을 활용한 GG 방법론을 활용하여 산정한 증발산량을 측정된 증발산량과 비교한 정확성을 정량화 하기 위해 Average root mean square error (RMSE), mean absolute bias (BIAS), coefficient of determination ($R^2$)과 같은 통계값을 이용하였다. 최종적으로 각 사이트의 기후를 Aridity Index (AI)를 이용하여 분류하였으며 분류된 기후별로 GG 방법론의 적용성을 검토하였다.

• Korean Security Journal
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• no.51
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• pp.61-78
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• 2017

This study aims to empirically validate the relationship between organizational learning transfer climate and the transfer of training and to enhance the transfer of training among South Korean coast guards. The empirical data was collected through 526 South Korean coast guards admitted to the institute, and support by managers and peers, and potential for organizational change were selected as independent variables for multiple regression. As a result, the transfer of training is positively correlated with support of mangers and peers, and potential for organizational change, thus suggesting factors like supervisor participation and long-term educational planning as policy implications for the effective transfer of training to work environment. Though findings from research cannot be generalized to the broader population due to limitations of sampling, this study does find its significance in that organizational learning transfer climate was considered as a key factor influencing the transfer of learning for the first time.

• Industry Promotion Research
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• v.7 no.2
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• pp.31-42
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• 2022

This study was conducted in-depth interviews and examinations by selecting mothers with low levels of self-differentiation and experiencing anxiety about parenting among mothers with low levels of self-differentiation, and analyzed them around categories and analyzed them into general structural techniques. As a current period task, it is the cause of the rasing-anxiety of parenthood in school age and the number of children due to nuclear familyization, and by generalizing the family's problems and experiences of parenting insolvency into categories, it is the reason for recognizing problems such as the child's social response and emotional support and the cause of the mother's low level of self-differentiation and anxiety, and setting the correct direction for parenting.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.255-268
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• 2023

This paper focuses on the tests for generalized fluctuation in the context of assessing structural changes based on linear regression models. For efficient estimation there has been a growing focus on the structural change monitoring, particularly in relation to fields such as artificial intelligence(hereafter AI) and machine learning(hereafter ML). Specifically, the investigation elucidates the implementation of structural changes and presents a coherent approach for the practical application to the BDI(Baltic Dry-bulk Index), which serves as a representative maritime trade index in global market. The framework encompasses a range of F-statistics type methodologies for fitting, visualization, and evaluation of empirical fluctuation processes, including CUSUM, MOSUM, and estimates-based processes. Additionally, it provides functionality for the computation and evaluation of sequences of pruned exact linear time(hereafter PELT).

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.311-319
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• 2012

The simplest and the most important distribution in survival analysis is exponential distribution. Koziol and Green (1976) derived Cram$\acute{e}$r-von Mises statistic's randomly censored version based on the Kaplan-Meier product limit estimate of the distribution function; however, it could not be practical for a real data set since the statistic is for testing a simple goodness of fit hypothesis. We generalized it to the composite hypothesis for exponentiality with an unknown scale parameter. We also considered the classical Kolmogorov-Smirnov statistic and generalized it by the exact same way. The two statistics are compared through a simulation study. As a result, we can see that the generalized Koziol-Green statistic has better power in most of the alternative distributions considered.