• Korean Journal of Cognitive Science
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• v.16 no.1
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• pp.29-52
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• 2005

This study was carried out to examine whether children had the naive psychological knowledge that the mental states ate requited to understand the intentional actions, whether their psychological knowledge was organized as a theory, and in what aspects the knowledge changed as children get older. Three- to 11-year-olds were presented with two types of tasks. In action explanation tasks, children were presented with simple descriptions of two characters engaging in specific actions and then asked to explain the characters' action. In action prediction tasks, they were told stories depicting a character's desire and belief and then asked to predict the action of the character. Three-year-olds explained the action in terms of abstract construct such as emotion, intention, and desire, and they predicted the character's action on the basis of her/his desire and explicit belief but not on the basis of inferred false belief and traits. In addition when they were asked to explain one mental state, they explained in terms of other mental states, suggesting the coherence of their knowledge. The present results suggested that even 3-year-olds' psychological knowledge was organized as a theory, in that it was used as a causal device in explaining and predicting human actions, and it had abstractness and coherence. Older children's knowledge was different from 3-year-olds' in that older children explained the action in terms of more complicated mental states such as beliefs and traits. The nature of the developmental change in psychological knowledge was discussed.

• Journal of the Korean Society of Safety
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• v.30 no.4
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• pp.151-158
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• 2015

Usually risk assessment is performed for the safety of diverse industries though, many kinds of risks cannot be analyzed effectively by using classical probability models due to lack of experience data and impreciseness of human decision making. For these reasons, fuzzy risk assessment utilizing subjective judgment and experience of skillful experts has been considered as a solution. In this study, to comprehend the relationship between conventional fuzzy theory and human conceptual images on risks, linguistic variables were reviewed with reference to fuzzy membership functions, especially in the Korean language. As interviewees, about a hundred people including students as well as safety engineers voluntarily participated. The research results showed that most people were in favor of adjective expressions decorated with adverbs rather than naive expressions such as "high" or "low", and that directly translated linguistic variables were not appropriate for the Korean people in risk assessment as far. Therefore, with consideration of the selection tendency by the Korean people in linguistic variables, it could be concluded that 5 level expressions would be most favorable for linguistic variables in risk assessments in Korea.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• Journal of Distribution Science
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• v.22 no.4
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• pp.37-46
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• 2024

Purpose: Social media influencers (SMIs) have become significant sources of information influencing their followers' purchase intentions; few studies have been published on the effect of the number of followers and package tour prices on followers' purchase intention within the Vietnam travel industry utilizing naïve theories. This study examined the relationship between the number of followers and purchase intention and tested the moderating role of package tour price. Research Design, data and methodology: A 2 (number of followers: high vs. medium) × 2 (package tour price: high vs. low) between-subjects factorial design was used. 395 Vietnamese students (114 men, 281 women; M_age = 19.99, SD_age = 1.25) from Thuongmai University participated in the study. ANOVA and PROCESS MARCO were used to test hypotheses. Results: Findings indicate that participants show a higher purchase intention for SMIs with a higher number of followers than those with a medium one. When the package tour price is high, participants with a medium number of followers show a greater purchase intention than those with a high one. Conclusion: This recommendsthat tourism managers collaborate with SMIs with a high number of followers when the package tour price is low and with SMIs with medium ones when the package tour price is high.

• Korean journal of communication and information
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• v.55
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• pp.164-183
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• 2011

Technology innovation of digital convergence in recent years of the media sector has produced a series of significant changes in journalist labor. This study analyzes how recent introduction of convergent newsroom changed the nature of journalist labor and what strategy the management used to control journalists within the technologically innovated working condition with case of CBS. As the labor process theory tells us, the analysis found that technological innovation in the newsroom has encouraged a couple of aspects regarding labor process. First, losing control over their own labor journalists have undergone the process of significant deskilling. Second, the management have made a constant effort to introduce ideological and political apparatuses with twofold purposes, effective control over workers on one hand and concealing oppressive labor conditions on the other. The effort generated journalists' acceptance of new news-making routine and their consent on labor-management culture founded upon naive familism, which at last resulted in reinforcement of corporate power and isolation of labor society by separating internal labor market.

• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.31-47
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• 2004

This study was carried out to examine the development of physical knowledge in children. Eighty children aged 3- to 11-year-old and 16 adults were participated in this study. Participants' knowledge about failing, sliding and sinking/floating objects was investigated to understand what kind of knowledge they had, whether their knowledge was organized as theory and what was the nature of the developmental change in physical knowledge. Results showed that, for falling object task children of all age had correct knowledge about object's falling phenomena. However, there were age differences in children's understanding of the cause of object's falling. As the children's age decreased, the frequency of explanation referring to the absence of supper rather than the gravity as the cause of falling phenomena increased. For the sliding object task, children of all age could predict the motion of sliding object correctly. But only a few 9- and 11-year-old children could understand the effect of object weight and relations between gravity, frictional force and their interactions. Children under age 7 showed no evidence of possessing these knowledge. For sinking or floating object task, children of all age and even adults showed difficulties in understanding the sinking or float phenomena per se. For the cause of these phenomena although a few 9- and 11-year-old children referred to buoyancy as the cause, they had no correct knowledge about the buoyancy. This was also true for the adults. As a conclusion, the results of this study suggested that, not 3, but as young as 5-year-old children's physical knowledge exited as a form of naive theory in terms of their use as a causal devise in explaining the cause of object motion. However, even the theory of 9- and 11-year-old children was lack of the abstractness and coherence, which were also important characteristics of a theory. Finally, developmental change in physical knowledge proceeded toward more frequent and consistent use of physical knowledge as causal device and more abstract and coherently organized theory.

• Journal of Computing Science and Engineering
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• v.7 no.2
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• pp.99-111
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• 2013

Approximating a divergence between two probability distributions from their samples is a fundamental challenge in statistics, information theory, and machine learning. A divergence approximator can be used for various purposes, such as two-sample homogeneity testing, change-point detection, and class-balance estimation. Furthermore, an approximator of a divergence between the joint distribution and the product of marginals can be used for independence testing, which has a wide range of applications, including feature selection and extraction, clustering, object matching, independent component analysis, and causal direction estimation. In this paper, we review recent advances in divergence approximation. Our emphasis is that directly approximating the divergence without estimating probability distributions is more sensible than a naive two-step approach of first estimating probability distributions and then approximating the divergence. Furthermore, despite the overwhelming popularity of the Kullback-Leibler divergence as a divergence measure, we argue that alternatives such as the Pearson divergence, the relative Pearson divergence, and the $L^2$-distance are more useful in practice because of their computationally efficient approximability, high numerical stability, and superior robustness against outliers.

• Journal of The Korean Association For Science Education
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• v.30 no.2
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• pp.249-260
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• 2010

The main purpose of this study is to examine the effects of explicit instructions on the nature of science (NOS) on the understanding of science-gifted students. Participants were engaged in 8 explicit NOS instructions spanning 6 months. Data were collected before and after the instructions from 20 science-gifted students using student worksheets, open-ended questionnaires (Views of Nature Of Science, VNOS), and in-depth interviews. The results of this study showed that explicit instructions were helpful in improving the understanding of the tentativeness in science and socially and culturally embedded aspects of science. However, participants not only still possess naive views on the nature of science about the distinction of law and theory and the empirical aspects of science, but also had conflicting views and misconceptions in some areas. The study has implication for development of science-gifted program that the explicit instructions on NOS and science inquiry should be provided concurrently, given the complementary relationship of the two activities.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.710-718
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• 2000

Many multiprocessing systems have been developed to exploit the parallelism and to improve the performance. However, the naive multiprocessing schemes were not successful as many researchers thought, due to the heavy cost of communication and synchronization resulting from parallelization. In this paper, we will identify the reasons for the poor performance and the compiler requirements for the performance improvement. We realized that the decisions for multiprocessing should be derived by the overhead information. We applied this idea to the automatic parallelizing compiler, SUIF. We substituted the original backend of SUIF with our backend using MPI, and gave it the capability to validate parallelization decisions based on overhead parameters. This backend converts the intermediate code containing spacification of parallelizable regions into the distributed-memory based parallel program with MPI function calls without excessive parallelization that may cause performance degradation.

• Asia Marketing Journal
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• v.15 no.3
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• pp.31-52
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• 2013

The metacognitive experience of the ease or difficulty with which new, external information can be processed, referred to as 'processing fluency,' has been shown to influence a wide range of human judgments including truth judgments, familiarity judgments, risk perception, evaluation, and preference (see Alter and Oppenheimer 2009 for a review). The current research explores the possibility of a consumer's product innovativeness judgment based on the difficulty of processing new information. In specific, this study examines if the inferential link between (dis)fluency-(un)familiarity can feed into the perception of innovativeness. This study also explores how a consumer's processing motivation can moderate the consumer's reliance on processing fluency in judgments and how the influence of fluency can vary depending on judgment task orders. In an experiment, participants rated a new product's innovativeness and then indicated their product attitude (or vice versa depending on the judgment task order condition) after reading a product review article that was printed in either an easy-to-read or a difficult-to-read font (for fluency manipulation). The findings show that low need for cognition individuals infer higher product innovativeness when processing product information is difficult rather than easy, consistent with the common assumption that 'new information is more difficult to process than familiar information.' The findings also suggest that once low fluency is attributed to innovativeness, it may no longer lead to a negative response to the product. High need for cognition individuals' judgments on product innovativeness are not affected by fluency. The findings also demonstrate a judgment task order effect on the use of fluency in judgments (e.g., Xu and Schwarz 2005). This study provides the first evidence that an individual's fluency experience can be used as a source of information in product innovativeness judgments especially under low processing motivation conditions. The findings can help marketers better understand the malleability of consumer judgments and perceptions of product characteristics (e.g., product innovativeness) by demonstrating an interesting interplay of processing fluency, processing motivation, and judgment task-related contextual factors.