• Journal of The Korean Association For Science Education
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• v.36 no.6
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• pp.935-946
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• 2016

This study aims to explore cognitive biases relating the core competences of science and instructional strategy in reducing the level of cognitive biases. The literature review method was used to explore cognitive biases and science education experts discussed the relevance of cognitive biases to science education. Twenty nine cognitive biases were categorized into five groups (limiting rational causal inference, limiting diverse information search, limiting self-regulated learning, limiting self-directed decision making, and category-limited thinking). The cognitive biases in limiting rational causal inference group are teleological thinking, availability heuristic, illusory correlation, and clustering illusion. The cognitive biases in limiting diverse information search group are selective perception, experimenter bias, confirmation bias, mere thought effect, attentional bias, belief bias, pragmatic fallacy, functional fixedness, and framing effect. The cognitive biases in limiting self-regulated learning group are overconfidence bias, better-than-average bias, planning fallacy, fundamental attribution error, Dunning-Kruger effect, hindsight bias, and blind-spot bias. The cognitive biases in limiting self-directed decision-making group are acquiescence effect, bandwagon effect, group-think, appeal to authority bias, and information bias. Lastly, the cognitive biases in category-limited thinking group are psychological essentialism, stereotyping, anthropomorphism, and outgroup homogeneity bias. The instructional strategy to reduce the level of cognitive biases is disused based on the psychological characters of cognitive biases reviewed in this study and related science education methods.

• Strategy21
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• s.34
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• pp.207-235
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• 2014

이 논문의 목적은 해군력 개량화를 소개하고 그 활용에 대하여 제안함에 있다. 어떻게 하면 여러 국가 간의 다양한 분쟁에 대한 해군력의 효과를 효과적으로 이해할 수 있을까? 혹은, 어떻게 하면 다양한 해군력의 나라별, 시간별 변화를 이해를 할 수 있을까? 지금까지 많은 학자들이 해군력의 변화와 그 변화에 따른 해군력이 분쟁에 미치는 영향을 규명하려고 많은 노력을 해왔다. 그 중의 한 방법이 정성적인 방법이나 아직 정량적인 시도는 매우 적다. 이 글은 해군력을 정량화하는 방법과 그 데이터를 이용하여 여러 기존 이론을 검증하고 여러 다른 연구주제를 연구하는데 어떻게 이용이 될 것인지를 소개를 하는 글이다. 본 논문의 주요 쟁점은 다음과 같다. 첫째, 계량화적 접근이란 무엇인가에 대해 논의 해 본다. 계량화란 무엇이며 정성적인 방법과의 차이는 무엇인지를 통해 정량화의 이용 가치에 대해 논의해 본다. 둘째, 해군력의 정량화이다. 해군력의 정량화를 위해 어떠한 기준들을 세우고, 그 기준에 따라 함정들을 코딩하고 톤수를 세는 과정을 설명한다. 셋째, 정량화된 해군력을 바탕으로 동북아시아 국가들의 해군력 변화를 서술적으로 분석한다. 이제 주어진 해군력 데이터(주요 함정의 톤수)를 가지고 각 동북아 국가별 시간별로 어떠한 변화를 거처 왔고, 각 분쟁들 (1,2차 세계대전 등)에는 어떠한 상관관계가 있는지를 단순통계적 방법을 이용하여 알아본다. 넷째, 해군력의 변화가 경쟁국가 간의 전쟁 발발에 있어서 어떤 영향을 미치는 지에 대하여 통계적인 방법을 이용하여 검증해 본다. 묘사적인 방법은 다른 요소들에 대한 통제가 이루어 지지 않아, 정확히 해군력과 경쟁국가 간의 전쟁에 대한 인과적인 관계를 증명하기에는 한계가 있다. 따라서, 다른 경쟁적 이론들을 (예를 들어 민주평화론 등) 통제하여 해군력이 숙적국가 간의 전쟁 발발에 미치는 영향을 검증하였다. 상호 해군력의 증가는 경쟁국가 간에는 전쟁을 덜 일으키는 요인으로 작용하였으며, 이는 해군력이 경쟁국가 간에는 억제력이 있다고 추론 할 수 있다. 궁극적으로 해군력의 영향에 대한 정량적인 접근은 기존 연구의 검증, 미래 예측, 국가의 정책결정자들에게 보다 신뢰가 가는 자료를 제공하는 장점들이 있다. 이러한 장점들을 바탕으로 해군력의 영향에 대한 연구는 분쟁분야에 있어서 학술적이나 실용적인 측면에서 많은 이점이 있다.

• Korean Journal of Social Welfare
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• v.67 no.4
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• pp.79-101
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• 2015

What is the role of welfare discourse? Michel Foucault suggests the power and knowledge relation that power in a particular society and period controls the society and members by creating knowledge affecting the formation of cognitive and normative systems. Having the formation of exclusions(constraint of cognition), and materiality and reality(normative system) as an analytical framework, this article attempts the exploration of welfare discourse analyses with public statements relating to welfare subjects of the four former Korean presidents. As a result, It is found that dominant epistemic system is formed by balancing welfare and growth and regarding jobs as the best welfare(the linkage of welfare-growth-employment), emphasizing individual economic responsibility and self-reliance, pursuing welfare selectivism, and excluding comprehensive welfare provisions. At the same time, it is observed that power is not always formulating systematic knowledge and that there is a gap between cognition and norm. While the Foucauldian discourse analysis provides a causal inference about low social welfare expenditure, excessive focus on the role of power as knowledge generator and infuser causes a question of how to accommodate contemporary changes into knowledge system.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.120-133
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• 2000

Major obstruction of using formal methods for hybrid real-time systems in industry is the difficulty that engineers have in understanding and applying the quantitative methods in an abstract requirements phase. While formal methods technology in safety-critical systems can help increase confidence of software, difficulty and complexity in using them can cause another hazard. In order to overcome this obstruction, we propose a framework for qualitative requirements engineering of the hybrid real-time systems. It consists of a qualitative method for requirements specification, called QFM (Qualitative Formal Method), and a safety analysis method for the requirements based on a causality information, called CRSA (Causal Requirements Safety Analysis). QFM emphasizes the idea of a causal and qualitative reasoning in formal methods to reduce the cognitive burden of designers when specifying and validating the software requirements of hybrid safety systems. CRSA can evaluate the logical contribution of the software elements to the physical hazard of systems by utilizing the causality information that is kept during specification by QFM. Using the Shutdown System 2 of Wolsong nuclear power plants as a realistic example, we demonstrate the effectiveness of our approach.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.393-402
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• 2007

The purpose of this study is to provide the design direction based on consumer sensitivity through the structure between product design preferences - sensitivity image - design elements. For the purpose, we selected men's shaver products for this study subject and collected 164 shavers' pictures released between 2001-2007 years. Then, we carried out a pilot test for collection of sensitivity images about shavers, made a survey using semantic differential method and analyzed the survey. According the result, consumers preferred the sensitivity images "luxury, attractive, stable", design elements satisfied the preference images were "form of body is not a circular arcs or a polygon, material is steel, button is push style, and a color of body is not brown." This study can provide a base of the causal relationship between design preferences - sensitivity image - design elements and a design process to predict consumer sensitivity-oriented design.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.51-62
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• 2022

AI-based speed prediction studies have been conducted quite actively. However, while the importance of explainable AI is emerging, the study of interpreting and reasoning the AI-based speed predictions has not been carried out much. Therefore, in this paper, 'Explainable Deep Graph Neural Network (GNN)' is devised to analyze the speed prediction and assess the nearby road influence for reasoning the critical contributions to a given road situation. The model's output was explained by comparing the differences in output before and after masking the input values of the GNN model. Using TOPIS traffic speed data, we applied our GNN models for the major congested roads in Seoul. We verified our approach through a traffic flow simulation by adjusting the most influential nearby roads' speed and observing the congestion's relief on the road of interest accordingly. This is meaningful in that our approach can be applied to the transportation network and traffic flow can be improved by controlling specific nearby roads based on the inference results.

• Journal of Korean Elementary Science Education
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• v.41 no.1
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• pp.30-43
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• 2022

In this study, elementary students' science communication competence was investigated based on the grammatical features expressed in their language-use in classroom discourse and science writings. The classes were designed to integrate the evidence-based reasoning framework and traditional learning cycle and were conducted on fifth graders in an elementary school. Eight elementary students' discourse data and writings were analyzed using lexico-grammatical resource analysis, which examined the discourse text's content and logical relations. The results revealed that the student language used in analyzing data, interpreting evidence, or constructing explanations did not precisely conform to the grammatical features in science language use. However, they provided examples of grammatical metaphors by nominalizing observed events in the classroom discourses and those of causal relations in their writings. Thus, elementary students can use science language grammatically from science language-use experiences through listening to a teacher's instructional discourses or recognizing the grammatical structures of science texts in workbooks. The opportunities in which elementary students experience the language-use model in science learning need to be offered to understand the appropriate language use in the epistemic context of evidence-based reasoning and learn literacy skills in science.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.33-42
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• 2018

In the aftermath of an earthquake, seismic-damaged infrastructure systems loss estimation is the first step for the disaster response. However, lifeline systems' ability to supply service can be volatile by external factors such as disturbances of nearby facilities, and not by own physical issue. Thus, this research develops the bayesian model for probabilistic inference on common-cause and cascading failure of seismic-damaged lifeline systems. In addition, the authors present network robustness estimation metrics in the context of failure propagation. In order to quantify the functional loss and observe the effect of the mitigation plan, power and water supply system in Daegu-Gyeongbuk in South Korea is selected as case network. The simulation results show that reduction of cascading failure probability allows withstanding the external disruptions from a perspective of the robustness improvement. This research enhances the comprehensive understanding of how a single failure propagates to whole lifeline system performance and affected region after an earthquake.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.189-212
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• 2005

This study examines the interactions between KTB spot and futures markets using the daily prices from March 4, 2002 to January 31, 2005. We use Granger causality test, impulse Response Analysis and Variance Decomposition through vector autoregressive analysis (VAR). However, considering the long-term relationships between the level variables of KTB spot and futures, we introduced Vector Error Correction Model. The main results are as follows. According to the results of Granger-causality test and impulse response analysis, we find that the yields of KTB forward have a great influence on the change of KTB spot but not vice versa. In terms of volatility analysis, there is no inter-dependence between KTB forward and spot markets. In the variance decomposition analysis we find that the short-term KTB forward has much more impact on the KTB spot market than the long-term KTB forward does. We think these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management and international portfolio management.

• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.193-204
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• 2012

The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.