• Journal of Distribution Science
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• v.18 no.3
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• pp.87-97
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• 2020

Purpose: The aim of this study is to understand the internal and external responses that consumers experience when they are exposed to an innovative system in retail stores. This study considered the SST(Self-Service Technology) system in a retail setting as a type of functional environmental stimuli and selected a smart shopping cart as an example of SST system. The influences of functional environmental stimuli on consumers' emotional, cognitive, and behavioral responses were examined by applying S-O-R model. In addition, this study attempted to extend the traditional S-O-R model by (a) incorporating personal characteristics variables such as time pressure and perceived crowding and (b) considering not only emotional but also cognitive aspects of consumers' internal responses. Research Design, Data, and Methodology: This study used a video-scenario technique. Participants watched a video about grocery shopping situations using a smart shopping cart and responded to their emotional, cognitive, and behavioral responses. An online survey was conducted using Amazon's Mechanical Turk (N = 185). All participants were US consumers over 20 years old and had been shopping at the grocery store in the last month. Data were analyzed through structural equations modeling with AMOS 20. Results: Test results showed that consumers who perceived higher levels of time pressure and perceived crowding in usual shopping situations were more likely to evaluate the SST system favorably. The results showed that personal characteristics have a significant impact on consumers' evaluation of functional environmental stimuli in retail setting. As consumers evaluated the SST system favorably, they experienced more positive affect and less negative affect during their shopping behaviors. Positive affect led to good service quality inference, which further increased patronize intention. However, negative affect did not show a significant impact on service quality inference, but only on patronize intention. Conclusions: This study attempted to investigate the influence of SST system by extending the traditional S-O-R model. This study classified the SST system as functional environmental stimulus of retail stores and analyzed the effect of stimulus on consumers' internal and external responses. The results of this study showed that the introduction of innovative SST can serve as an effective store differentiation strategy in an increasingly competitive retail environment.

• Korean Journal of Cognitive Science
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• v.20 no.3
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• pp.335-355
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• 2009

We examined risk judgment and the accuracy of inference based on two kinds of probabilities in a Bayesian inference task: the death probability from a disease (base rates) and the probability of having a disease with positive results in the screening test (posterior probabilities). Risk information were presented in either a probability or a frequency format. In Study 1, we found a numerical format effect for both base rate and posterior probability. Participants rated information as riskier and inferred more accurately in the frequency condition than in the probability condition for both base rate and posterior probability. However, there was no frequency range effect, which suggested that the ranges of frequency format did not influence risk ratings. In order to find out how the analytic thought system influences risk ratings, we compared the ratings of a computation condition and those of a no-computation condition and still found the numerical format effect in computation condition. In Study 2, we examined the numerical format effect and frequency range effect in a high and a low probability condition and found the numerical format effect at each probability level. This result suggests that people feel riskier in the frequency format than in the probability format regardless of the base rates and the posterior probability. We also found a frequency range effect only for the low base rate condition. Our results were discussed in terms of the dual process theories.

• Journal of the Korean Chemical Society
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• v.60 no.2
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• pp.137-143
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• 2016

Effective teaching and learning is a continuous process of monitoring and re-organization of teaching method, so to benefit both students and educators. Reflective journal writing is an effective method for students to reflect on their learning experience about a new concept or subject taught and at the same time enables educators to improve on their academic skills. In the present paper, we have examined and evaluated the effectiveness of the Uncritical Inference Test (UIT) that was conducted in our basic organic chemistry course through a systematic network built based on students’ reflective writing. From the data analysis, the UIT has benefited students in three dimensions, namely cognitive, affective and group learning domains. Moreover, the UIT activity instilled an active learning environment in organic chemistry classroom and deeper learning among chemistry students as shown in the collected data. In future, this activity could be adapted as a teaching method to enhance students’ critical thinking skills and question-asking capability in other teaching courses.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.461-467
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• 1998

Although many methods of knowledge acquisition has been developed in the expert systems field, such a need for causal knowledge acquisition has not been stressed relatively. In this respect, this paper is aimed at suggesting a causal knowledge acquisition process, and then investigate the causal knowledge-based inference process. A vehicle for causal knowledge acquisition is FCM (Fuzzy Cognitive Map), a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain. Although FCM has a plenty of generic properties for causal knowledge acquisition, it needs some theoretical improvement for acquiring a more refined causal knowledge. In this sense, we refine fuzzy implications of FCM by proposing fuzzy implications of FCM by proposing fuzzy causal relationship and fuzzy partially causal relationship. To test the validity of our proposed approcach, we prototyped a causal knowledge-driven inference engine named CAKES and then experime ted with some illustrative examples.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.549-556
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• 2017

This study investigated the importance of social cognitive intervention and the cognitive rehabilitation intervention by comparing the difference and examining the relationship between neurological cognitive function and social cognitive function of stroke patients in the acute phase and chronic stroke before returning to the community. LOTCA, cartoon intention inference task, and social behavior sequence task were performed on 30 acute stroke inpatients and 30 chronic stroke patients from May 2015 to June 2016. A two sample t test was conducted to examine the differences between the groups. The Pearson's correlations test was performed to examine the correlation among the variables in each group. As a result, there were statistically significant differences between the neurological cognitive function and social cognitive function of acute stroke patients and chronic stroke patients who were undergoing rehabilitation training before returning to the community (p<0.05). A linear relationship was found between the thinking operation and social behavior sequence task in the acute stroke group (r=0.539, p<0.05). In the chronic stroke group, visual perception (r=0.530, p<0.05), visual motor organization (r=0.655, p<0.05) and thinking operation (r=0.534, p<0.05) were correlated with the cartoon intention inference task. In addition, the social behavior sequence task were correlated with visual organization (r=0.534, p<0.05) and thinking operation (r=0.764, p<0.05). As a result of multiple regression analysis, the neurological cognitive functions influencing the social cognitive function in the cartoon task was found to be the thinking operation (B = 0.431) in acute stroke patients and the thinking operation (B=0.272) and visuomotor organization (B = 0.218) in the case of chronic stroke. In addition, the results of the social behavior sequence task revealed the thinking operation (B=0.417) in the acute stroke patients, and thinking operation (B=0.267), visual motor organization(B=0.274) and visual perception(B=151) in chronic stroke patients to be significant. According to this result, there is a difference in the neurological and social cognitive levels between the two groups. Therefore, the social cognition is strongly related to the high level cognitive function as thinking operation of the neurological cognitive function. Therefore, in further research, it would be necessary to determine if there is a change in higher cognitive function in neurological cognitive function after applying a social cognition intervention program for stroke.

• Korean Journal of Cognitive Science
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• v.15 no.1
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• pp.25-33
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• 2004

This paper discusses two problems with LR parsing with regard to constructing parsing tables with feature-based grammars. First, we show that traditional LR parsing methods suffer from nontermination and nondeterminism problems when they are applied to feature-based grammars. We then present an LR method for feature-based grammars that avoids both nontermination and nondetermisim by making use of partial information of a feature structure. Second, we describe the problem of adapting LR parsing to feature-based grammars with schematic rules (i.e., rules that do not contain enough information to construct parsing tables). To remedy this problem, we propose a rule inference algorithm which instantiates underspecified rules into more specified ones containing enough information.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.255-257
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• 1989

This paper proposes a method for extracting the imformation of aspect and modality from the predicative part which is consisted of main verbal and auxiiary verbals.Data which are expressed by the compound predicate with many consecutive verbals are collected and analyzed to thirty-six structual forms of the predicative part.Inthe final analysis, an extracting function of conceptual information is derived to find the connoted aspect and modality in each structure.The informations which are obtained by this function decrease the individual ambiguity of an auxiliary verbal and offer a detailed meaning inthe syntactic and semantic analysis of machine translation system or inference machine.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.65-71
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• 2002

우리의 기억에 표상되어 있는 개념의 본질과 근원 그리고 이들의 관계에 대한 연구는 연상과 기억구조의 관계에 집중되어 왔다 따라서, 어떤 한 개념과 다른 한 개념이 관계되어 있다는 의미적 혹은 연상적 점화의 양상은 의미기억 구조를 적절히 예시할 수 있을 것이다. 본 연구는 어휘수준에서 보여지는 연상의 양상이 문장수준에서도 유사한 예측을 해낼 수 있는지를 살펴보고자 한다. 즉, 어휘수준에서 연상적 관계에 있는 두 개념이 선행사와 연상 조응사라는 문법성을 띠면서 문장에서 예상되는 역할을 수행할 때는, 의미기억의 또 다른 양상을 보여줄 것이라 예측되며, 이것은 문장의 의미·화용적 추론의 기제로 유인되고 있음을 제안하려고 한다. 또한, 의미·연상적 점화와 추론의 기제간의 적절한 상호작용은 문장의 응집성과 처리속도 간에도 유의미한 예측을 할 수 있음을 제안한다.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.201-206
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• 2000

도구추론에서 읽기범위에 따른 개인차 효과가 나타나는지를 살펴보고자 2개의 실험을 수행하였다. 실험 1에서 어휘판단과제를 사용한 결과 읽기범위가 큰 이해자는 도구추론을 온라인으로 생성하였지만, 읽기범위가 작은 이해자는 도구추론을 온라인으로 생성하지 못하는 것으로 나타났다. 그림명명과제를 사용한 실험 2 에서는 읽기 범위에 관계없이 도구추론이 온라인으로 생성되는 것으로 나타났다. 실험 1과 2의 상반된 결과를 종합해 보면, 언어이해과정에서는 발생하는 도구추론의 유형은 언어적인 도구추론과 시각적인 도구추론으로 구분할 수 있으며, 어휘판단과제는 언어적 추론에 민감한 과제인 반면, 그림명명과제는 시각적 추론에 매우 민감함 과제인 것으로 해석할 수 있다. 이러한 결과는 읽기범위가 작업기억의 음운루프 모듈에서의 처리효율성을 반영하는 측정치라는 점을 시사한다.