• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.149-160
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• 1995

We consider the problem of optimal adaptive estiamtion of the euclidean parameter vector $\theta$ of the univariate non-linerar autogressive time series model ${X_t}$ which is defined by the following system of stochastic difference equations ; $X_t = \sum^p_{i=1} \theta_i \cdot T_i(X_{t-1})+e_t, t=1, \cdots, n$, where $\theta$ is the unknown parameter vector which descrives the deterministic dynamics of the stochastic process ${X_t}$ and ${e_t}$ is the sequence of white noises with unknown density $f(\cdot)$. Under some general growth conditions on $T_i(\cdot)$ which guarantee ergodicity of the process, we construct a sequence of adaptive estimatros which is locally asymptotic minimax (LAM) efficient and also attains the least possible covariance matrix among all regular estimators for arbitrary symmetric density.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.2
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• pp.88-97
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• 1989

In general turret servo system is subject to influnces by disturbances and uncertain modeling errors, which result from large dynamic characteristics and high-spedd operation. In this paper the influences of such disturbances and modeling errors are analyzed quali- tatively for the linerar approximation model of turret servo system, and then LQG/LTR control theory is applied to linear approximation model in order to design a controller which satisfies robustness/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.139-145
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• 2021

This study was conducted to find out the effect of job-crafting of social workers at community children's centers on the satisfaction of children. This study used a multi-level analysis model that calculated the child factor (level 1) and the social worker factor (level 2) by utilizing the responses of 31 social workers and 216 children used at 31 community children's centers. The main research results are as follows: First, it was found that 34.3% of the total variation in child satisfaction was due to differences by community children's centers. Second, it was found that the number of hours used per day in the child factor (level 1), and gender, age, and job-crafting in the life worker factor (level 2) affect the satisfaction of children. Based on these results, measures to improve the satisfaction level of children using community children's centers were discussed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.37-49
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• 2024

To date, numerous empirical formulas have been proposed through hydraulic model experiments to predict the wave breaker index, including wave height and depth of wave breaking, due to the inherent complexity of generation mechanisms. Unfortunately, research on the characteristics of wave breaking and the prediction of the wave breaker index for gravel beaches has been limited. This study aims to forecast the wave breaker index for gravel beaches using representative linear-based machine learning techniques known for their high predictive performance in regression or classification problems across various research fields. Initially, the applicability of existing empirical formulas for wave breaker indices to gravel seabeds was assessed. Various linear-based machine learning algorithms were then employed to build prediction models, aiming to overcome the limitations of existing empirical formulas in predicting wave breaker indices for gravel seabeds. Among the developed machine learning models, a new calculation formula for easily computable wave breaker indices based on the model was proposed, demonstrating high predictive performance for wave height and depth of wave breaking on gravel beaches. The study validated the predictive capabilities of the proposed wave breaker indices through hydraulic model experiments and compared them with existing empirical formulas. Despite its simplicity as a polynomial, the newly proposed empirical formula for wave breaking indices in this study exhibited exceptional predictive performance for gravel beaches.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.79-98
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• 2009

Web traffic is becoming an important indicator to make inferences about internet companies' future prospects so that traditional firm valuation methods need to be modified to integrate the ideas of web traffic information as a major asset of internet companies. It is because web traffic is a measure of attracting visitors to firm's web site and is the basis for internet companies' marketing expenditure and customer acquisition and retention. Also the web traffic represents the internet companies' technological advances and marketability. The major purpose of this study is to show the relevance of web traffic for valuation of internet companies. For this, we test hypothesis with the firm's web traffic and financial data using the analysis model of Hand(2000a) derived from the log-linear model introduced by Ye and Finn(1999). Test results show that the web traffic, more specifically the number of unique visitors, visits, and page views are all positively related to the firm's value. This implies that the web traffic information should be considered as one of the important non-financial indicator for the internet firm valuation.