• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.69-92
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• 2005

A brief survey of linguistic studies on the nature of contrastive information in discourse was Presented first, and an attempt was also made to incorporate the Linguistic theories and concepts about contrast in discourse into a psychological framework. A tentative model of processing of contrastive information in discourse was Proposed, and eight experimental studies on the effects of contrastive information on comprehension and memory of short and ions discourses were reviewed. Experimental results showed that contrastive sentences took more time to process at encoding, and yet were recognized faster and cued-recalled in greater amount than noncontrastive sentences. It was also found that levels of contrast in the discourse structure have some effects on encoding time. It was further found that the sentence immediately following the contrastive sentence was processed slowly regardless of whether it does or does not resolve the contrast. The implications of the results of empirical studies were discussed in relation to developing a research framework that integrate coherence studies and contrast studies urns the two disciplines of linguistics and cognitive psychology.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.131-143
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• 2021

Commercial transactions, one of the pillars of the capitalist economy, are occurring countless times every day, especially small and medium-sized businesses. However, small and medium-sized enterprises are bound to be the legal underdogs in contracts for commercial transactions and do not receive legal support for contracts for fair and legitimate commercial transactions. When subcontracting contracts are concluded among small and medium-sized enterprises, 58.2% of them do not apply standard contracts and sign contracts that have not undergone legal review. In order to support small and medium-sized enterprises' fair and legitimate contracts, small and medium-sized enterprises can be protected from legal threats if they can reduce the risk of signing contracts by analyzing various risks in the contract and analyzing and informing them of toxic clauses and omitted contracts in advance. We propose a risk prediction model for the machine reading-based legal contract to minimize legal damage to small and medium-sized business owners in the legal blind spots. We have established our own set of legal questions and answers based on the legal data disclosed for the purpose of building a model specialized in legal contracts. Quantitative verification was carried out through indicators such as EM and F1 Score by applying pine tuning and hostile learning to pre-learned machine reading models. The highest F1 score was 87.93, with an EM value of 72.41.

• Journal of The Korean Association For Science Education
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• v.12 no.1
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• pp.35-46
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• 1992

The purpose of this study was to investigate the most effective teaching model in the study of boiling point elevation. The teaching models were classified into three group-deductive, inductive and analogical teaching models. Learning materials, based on three teaching models respectively, were applied to 11th grade students, and the effect of teaching models were investigated and analyzed. The average achievement score(4.24) of the group treated with the analogical teaching model was higher than those(3.06 respectively) of each group treated with inductive or deductive teaching model(p<0.001). Most students answered that the analogical teaching model was helpful and interesting one for the comprehension of scientific concept.

• Journal of the Korean Chemical Society
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• v.53 no.3
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• pp.355-367
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• 2009

In this study, the 9th grade students were interviewed to explore their comprehension and interpretation processes of inscriptions representing the concept of atom and molecule. We used a semiotic model for the interview and the analysis of result. The research result revealed that the students performed structuring processes of interpreting inscriptions successfully, but they had a difficulty with translating processes for attaining the target concept or for connecting an inscription with another inscription. Translating processes of connecting inscription with text showed a different result according to achievement level of each student. On the other hand, all the interviewees showed similar sequences in the processes of interpreting inscriptions. Educational implications of these findings were discussed.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.325-330
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• 2014

Eddy current induction is used in a wide range of electronic devices, for example in detection sensors. Due to the advances in computer hardware and software, the need for 3D computation and system comprehension is a requirement to develop and optimize such devices nowadays. Pure theoretical models are mostly limited to special cases. On the other hand, the classical use of commercial Finite Element (FE) electromagnetic 3D models is not computationally efficient and lacks modeling flexibility or robustness. The proposed approach focuses on: (1) implementing theoretical formulations in 3D (FE) model of a detection device as well as (2) an automatic Volumetric Estimation Method (VEM) developed to selectively model the target finite elements. Due to these two approaches, this model is suitable for parametric studies and optimization of the number, location, shape, and size of PCB receivers in order to get the desired target discrimination information preserving high accuracy with tenfold reduction in computation time compared to commercial FE software.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.57-68
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• 2024

In this paper, we are interested in how creator economy startups allowing creators to make money from doing that they love. So, we look at European creator economy startups among Web3.0 business model landscape surveyed in 2022, because the US is home of Web2.0 giant platforms like YouTube. Totally seventeen European startups are investigated, and the theoretical logic is the disruptive innovation. We firstly review the survey published in 2022 and utilize the theory of the disruptive innovation to design the research framework including questions with each type of the disruptive innovation. In this paper, we firstly show, Kalao and Gem as NFT ecosystem platforms aim at service convenience. Secondly, Talkbase, Passionfroot, Bildr, Customuse, and Earnr aim at providing creator tools for under-skilled customers. Lastly, when it comes direct monetization with a decentralized business model, CrowdPad, Admix, GOALS, Realm, Dropstar, Pianity, Sonomo, Stage11, Miiji, and ReadyPlayerMe are representative. Despite the relatively small data size, the results are meaningful as they contribute to a more profound comprehension of the Web3.0 business models and offer guidance for future research directions.

• Journal of the Korean Chemical Society
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• v.68 no.4
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• pp.205-220
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• 2024

This study aims to explore characteristics of pedagogical reasoning and action of beginning science teachers that naturally and spontaneously occurs in a professional learning community. Three novice middle school science teachers who majored chemistry education in A college of education, passed the examination for selecting secondary school chemistry teachers, and had a common goal of designing 8^th grade science lesson plan voluntarily created a professional learning community and had weekly meetings over a year. Main data sources included transcribed audio-recording of 11 meetings of three science teachers in a professional learning community. Data was analyzed using Shulman's pedagogical reasoning model that includes comprehension, transformation, instruction, evaluation, reflection, and new comprehension to identify characteristics and features of pedagogical reasoning in a professional learning community. Data analysis revealed that pedagogical reasoning in a professional learning community comprises not only preparation, representations, instructional selections, and adaptation but also evaluation, reflection, and new comprehension in transformation stage. Reflection in transformation stage leads teachers to be actively engaged in discussion and get new comprehension on each sub-component(preparation, representations, instructional selections, adaptation, and evaluation) of transformation stage.

• Journal of The Korean Association For Science Education
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• v.31 no.4
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• pp.539-556
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• 2011

The purpose of this study was to examine preservice secondary science teachers' understanding of the nature of science, by using nature of science (NOS) questionnaire on the basis of atomic model, and compare this to pre-studies. 'Understanding of nature of scientific model,' 'Tentativeness of scientific knowledge,' 'Subjectivity in science,' 'Use of inference and imagination,' 'Myths of the scientific method,' and 'Comparison between science and art.' were examined. Preservice teachers showed great comprehension of the tentativeness of scientific knowledge (the orbital model) and the subjectivity in science (the different interpretation about the experiment of particle scattering), but displayed the lowest comprehension of the scientific method. For understanding of nature of scientific model (the atomic model) and the comparison between science (Bohr's atomic model) and art (Picasso's work), preservice teachers brought out a combination of ontological and constructivist perspective and showed the contradictory thought about imagination in science research. In the result of comparison to pre-studies using the NOS instruments contains general terms, represented high levels of agreement about the tentativeness of scientific knowledge by using concrete examples of 'atomic model'. When concrete scientists such as Thomson, Rutherford, Bohr were presented, respondents revealed more informed views about the scientists' research method.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.9-13
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• 2005

A comprehension-based computational model of pilot action planning called ADAPT is presented to model pilot performance in a flight simulation context. Individual pilots were asked to execute a series of flight maneuvers using a flight simulator, and their eye-scanning, control movements, and flight performance were recorded in a time-synched database. Computational models of each of the 25 individual pilots were constructed, and the individual models simulated execution of the same flight maneuvers performed by human pilots. The time-synched eye-scanning, control movements, and flight performance of individual pilots and their respective models were compared to test ADAPT's predictive validity.

• Journal of the Ergonomics Society of Korea
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• v.21 no.1
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• pp.1-14
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• 2002

The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.