• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.159-178
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• 2013

The purpose of this study was to 1) replicate the Wells effect(i.e., reluctance to rule against the Defendant solely on the basis of probabilistic evidence) in Korea and 2) examine the validity of an Alternative explanation(i.e., perception of risk of wrong verdict). In study 1(n=46), mock jurors in the tire-tracks condition were reluctant to rule against the defendant based on their perceived probability and this pattern was not resulted in the tire-tracks-belief condition. Therefore, the Wells effect was replicated in Korea. In study 2(n=70), we manipulated the participants' perception of risk of wrong verdict. That is, participants who were assigned in the high risk perception of wrong verdict were informed that if the defendant were found guilty, the defendant would get considerable demage both in finance and reputation of the company. Participants in the low risk perception of wrong verdict condition were informed that these demage would not be great. The results revealed that the Wells effect was pronounced in the high risk perception of wrong verdict condition. That is, participants were more reluctant to rule against the defendant when they perceive the significance of the result of wrong verdict as high. Limitations of the study and the directions for future study were discussed.

• Korean Journal of Culture and Social Issue
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• v.11 no.1
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• pp.59-84
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• 2005

Three studies were conducted to examine the degree to which three common heuristics, anchoring heuristic, framing effect and representative-ness heuristic, influence the decision-making precesses of actual judges and 5-persons mock juries. With scenarios regarding various issues that are commonly raised in actual criminal and civil trials, study 1 examined the 158 actual judges' decisions. In study 2, the decisions of 80 mock jury groups that consisted of college students were examined with similar scenarios. And individual decisions were examined in study 3 to compare with the group decisions in study 2. The decision processes of the actual judges and the mock jury groups alike were found to be influenced by "anchors". But the biases by the anchoring heuristic were more pronounced in the group decisions than in the decisions of the actual judges. With respect to framing effect, the actual judges were found to be resistant, while a small effect was found in the decisions of mock jury groups. Representative-ness biases weren't found in the decisions of both the actual judges and mock juries. The implications of the results for judicial systems were discussed.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.481-491
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• 2014

The power production using renewable energy is more important because of a limited amount of fossil fuel and the problem of global warming. A concentrative photovoltaic system comes into the spotlight with high energy production, since the rate of power production using solar energy is proliferated. These systems, however, need to sophisticated tracking methods to give the high power production. In this paper, we propose a hierarchical tracking system using modular Bayesian networks and a naive Bayes classifier. The Bayesian networks can respond flexibly in uncertain situations and can be designed by domain knowledge even when the data are not enough. Bayesian network modules infer the weather states which are classified into nine classes. Then, naive Bayes classifier selects the most effective method considering inferred weather states and the system makes a decision using the rules. We collected real weather data for the experiments and the average accuracy of the proposed method is 93.9%. In addition, comparing the photovoltaic efficiency with the pinhole camera system results in improved performance of about 16.58%.

• Journal of KIISE
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• v.41 no.9
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• pp.652-665
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• 2014

Many important terminologies in biomedical text are expressed as abbreviations or acronyms. We newly suggest a semantic link topic model based on the concepts of topic and dependency link to disambiguate biomedical abbreviations and cluster long form variants of abbreviations which refer to the same senses. This model is a generative model inspired by the latent Dirichlet allocation (LDA) topic model, in which each document is viewed as a mixture of topics, with each topic characterized by a distribution over words. Thus, words of a document are generated from a hidden topic structure of a document and the topic structure is inferred from observable word sequences of document collections. In this study, we allow two distinct word generation to incorporate semantic dependencies between words, particularly between expansions (long forms) of abbreviations and their sentential co-occurring words. Besides topic information, the semantic dependency between words is defined as a link and a new random parameter for the link presence is assigned to each word. As a result, the most probable expansions with respect to abbreviations of a given abstract are decided by word-topic distribution, document-topic distribution, and word-link distribution estimated from document collection though the semantic dependency link topic model. The abstracts retrieved from the MEDLINE Entrez interface by the query relating 22 abbreviations and their 186 expansions were used as a data set. The link topic model correctly predicted expansions of abbreviations with the accuracy of 98.30%.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.509-520
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• 2023

Scientific explanation is the main goal of scientists' scientific practice, and the science curriculum also includes developing students' abilities to construct scientific explanations as a major goal. Thus, clarifying its meaning is an important issue in the science education community. In this paper, the researchers identified three perspectives on 'scientific explanation' based on the scoping review method (Deductive-Nomological, Probabilistic, and Pragmatic explanation models). We argued that it is important to clarify and distinguish the meanings of 'scientific explanation' from other concepts used in science education, such as 'description', 'prediction', 'hypothesis', and 'argument' based on a review of the literature. It is also pointed out that there is a difference between 'scientific explanation' as a product and 'explaining scientifically' as communication, and several ways to revise achievement standard statements in the science curriculum are suggested, to guide students to construct scientific explanations and to help students to explain scientifically. By adopting the three scientific explanation models, the important factors to be considered were classified and organized, and examples of science learning activities for scientific explanation considering such factors were suggested. It is hoped that the discussion in this study will help establish clearer learning goals in science learning related to scientific explanation and aid the design of more appropriate learning activities accordingly.

• Journal of Animal Science and Technology
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• v.44 no.2
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• pp.151-164
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• 2002

Genetic variance and covariance components of the linear traits and the ordered categorical traits, that are usually observed as dichotomous or polychotomous outcomes, were simultaneously estimated in a multivariate threshold animal model with concepts of arbitrary underlying liability scales with Bayesian inference via Gibbs sampling algorithms. A multivariate threshold animal model in this study can be allowed in any combination of missing traits with assuming correlation among the traits considered. Gibbs sampling algorithms as a hierarchical Bayesian inference were used to get reliable point estimates to which marginal posterior means of parameters were assumed. Main point of this study is that the underlying values for the observations on the categorical traits sampled at previous round of iteration and the observations on the continuous traits can be considered to sample the underlying values for categorical data and continuous data with missing at current cycle (see appendix). This study also showed that the underlying variables for missing categorical data should be generated with taking into account for the correlated traits to satisfy the fully conditional posterior distributions of parameters although some of papers (Wang et al., 1997; VanTassell et al., 1998) presented that only the residual effects of missing traits were generated in same situation. In present study, Gibbs samplers for making the fully Bayesian inferences for unknown parameters of interests are played rolls with methodologies to enable the any combinations of the linear and categorical traits with missing observations. Moreover, two kinds of constraints to guarantee identifiability for the arbitrary underlying variables are shown with keeping the fully conditional posterior distributions of those parameters. Numerical example for a threshold animal model included the maternal and permanent environmental effects on a multiple ordered categorical trait as calving ease, a binary trait as non-return rate, and the other normally distributed trait, birth weight, is provided with simulation study.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.377-389
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• 2011

A higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The third generation index $C_{pmk}$ is more powerful than two useful indices $C_p$ and $C_{pk}$ that have been widely used in six sigma industries to assess process performance. In actual manufacturing industries, process capability analysis often entails characterizing or assessing processes or products based on more than one engineering specification or quality characteristic. Since these characteristics are related, it is a risky undertaking to represent the variation of even a univariate characteristic by a single index. Therefore, the desirability of using vector-valued process capability index(PCI) arises quite naturally. In this paper, we consider more powerful vector-valued process capability index $C_{pmk}$ = ($C_{pmkx}$, $C_{pmky}$)$^t$ that consider the univariate process capability index $C_{pmk}$. First, we examine the process capability index $C_{pmk}$ and plug-in estimator $\hat{C}_{pmk}$. In addition, we derive its asymptotic distribution and variance-covariance matrix $V_{pmk}$ for the vector valued process capability index $C_{pmk}$. Under the assumption of bivariate normal distribution, we study asymptotic confidence regions of our vector-valued process capability index $C_{pmk}$ = ($C_{pmkx}$, $C_{pmky}$)$^t$.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.581-594
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• 2013

A group sequential design can end a clinical trial early if a confirmed efficacy or a futility of study medication is found during clinical trials. Adaptation can adjust the design of clinical trials based on accumulated data. The key to this methodology is considered to control the overall type 1 error rate while maintaining the integrity of clinical trials. The estimation would be more complex and the sample size calculation will be more difficult if the clinical trials have repeated measurement data. Lee et al. (2002) suggested a repeated observation case by using the independent increments properties of the interim test statistics and investigated the properties of the proposed confidence interval based on the stage-wise ordering. This study extend Lee et al. (2002) to adaptive group sequential design. We suggest test statistics for the adaptation as redesigning the second stage of clinical trials and induce the stage-wise confidence interval of parameter of interests. The simulation will help to confirm the suggested method.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.117-140
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• 1991

The purpose of this paper is primarily to introduce a nonparametric statistical tool developed by Baek and Brock to detect a unidirectional causal ordering between two economic variables and apply it to interesting macroeconomic relationships among money, production and prices. It can be applied to any other causal structure, for instance, defense spending and economic performance, stock market index and market interest rates etc. A key building block of the test for nonlinear Granger causality used in this paper is the correlation. The main emphasis is put on nonlinear causal structure rather than a linear one because the conventional F-test provides high power against the linear causal relationship. Based on asymptotic normality of our test statistic, the nonlinear causality test is finally derived. Size of the test is reported for some parameters. When it is applied to a money, production and prices model, some evidences of nonlinear causality are found by the corrected size of the test. For instance, nonlinear causal relationships between production and prices are demonstrated in both directions, however, these results were ignored by the conventional F-test. A similar results between money and prices are obtained at high lag variables.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.439-450
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• 2016

For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.