• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.331-367
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• 2008

This study aims to validate a web-based neuropsychological testing tool developed by Kwak(2007) and to suggest solutions to potential problems that can deteriorate its validity. When it targets a wider range of subjects, a web-based neuropsychological testing tool is challenged by high drop-out rates, lack of motivation, lack of interactivity with the experimenter, fear of computer, etc. As a possible solution to these threats, this study aims to redesign the user interface of a web-based attention testing tool through three phases of study. In Study 1, an extensive analysis of Kwak's(2007) attention testing tool was conducted to identify potential usability problems. The Heuristic Walkthrough(HW) method was used by three usability experts to review various design features. As a result, many problems were found throughout the tool. The findings concluded that the design of instructions, user information survey forms, task screen, results screen, etc. did not conform to the needs of users and their tasks. In Study 2, 11 guidelines for the design of web-based attention testing tools were established based on the findings from Study 1. The guidelines were used to optimize the design and organization of the tool so that it fits to the user and task needs. The resulting new design alternative was then implemented as a working prototype using the JAVA programming language. In Study 3, a comparative study was conducted to demonstrate the excellence of the new design of attention testing tool(named graphic style tool) over the existing design(named text style tool). A total of 60 subjects participated in user testing sessions where their error frequency, error patterns, and subjective satisfaction were measured through performance observation and questionnaires. Through the task performance measurement, a number of user errors in various types were observed in the existing text style tool. The questionnaire results were also in support of the new graphic style tool, users rated the new graphic style tool higher than the existing text style tool in terms of overall satisfaction, screen design, terms and system information, ease of learning, and system performance.

• Journal of Korean Home Economics Education Association
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• v.19 no.1 s.43
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• pp.115-131
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• 2007

Philosophical and social backgrounds and inquiring into new direction of Practical Arts and Home Economics Education is done through this paper. The overall review of the related documents, records, books has been done, and research findings are presented as follows; Thought(Educational theory and Philosophy) for Korean Practical Arts Education is based on Learning to Labor, Practical Science and Pragmatism. Korean curriculum for Home Economics were originated in Confucianism background, which stressed the importance of different gender roles for men and women. However, Korean Home Economics based on Home Economics Subject Matter has been developed without philosophical base unlike that of American Pragmatism and Critical Theory. Therefore, scientific recognition in a section of value recognition was separated and developed so far. Thus, we could not answer to social missions about keeping values of life corresponding with changing environment I also observed the analysis of revision curriculum of the mentioned subject, and the changes of concepts of Work and Prasix, necessity of Home Economics Education for fixing about a basic life education and a basic life skill, and reinforcement of the function in Home. And then, new directions is proposed that the role of Home Economics Education in school be reinforced for the upcoming low birth rate and the aging society(high proportion of the aged people). Because Characters on correct values of children and youths might be nurtured in home foremost.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.511-522
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• 2014

During the development of the software, a variety of bugs are reported. Several bug tracking systems, such as, Bugzilla, MantisBT, Trac, JIRA, are used to deal with reported bug information in many open source development projects. Bug reports in bug tracking system would be triaged to manage bugs and determine developer who is responsible for resolving the bug report. As the size of the software is increasingly growing and bug reports tend to be duplicated, bug triage becomes more and more complex and difficult. In this paper, we present an approach to assign bug reports to appropriate developers, which is a main part of bug triage task. At first, words which have been included the resolved bug reports are classified according to each developer. Second, words in newly bug reports are selected. After first and second steps, vectors whose items are the selected words are generated. At the third step, TF-IDF(Term frequency - Inverse document frequency) of the each selected words are computed, which is the weight value of each vector item. Finally, the developers are recommended based on the similarity between the developer's word vector and the vector of new bug report. We conducted an experiment on Eclipse JDT and CDT project to show the applicability of the proposed approach. We also compared the proposed approach with an existing study which is based on machine learning. The experimental results show that the proposed approach is superior to existing method.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.402-411
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• 2019

The purpose of this study is to determine critical assessments and core competencies, and to determine the competence and discipline of self-assessment. We surveyed 511 students who graduated from 12 universities. Self-efficacy 24 items were measured on a 5-point scale, 8 core competencies and 52 detailed competencies were self - assessed from 0 to a maximum of 10 points. The higher the score, the higher the self - evaluation competency level. Statistical analysis was performed using SPSS 20.0 Ver., And a statistical significance level of 0.05 was considered. The self - evaluation competency level was the highest at 6.7 points in the clinical dentistry area, and the lowest at the evidence - based decision area of 5.7 points. Self-regulation was found to be positively related to the self-evaluation core competence level among self-efficacy sub-factors. As the students' self-efficacy affects subjective academic achievement and self-evaluation, it is necessary to develop and apply relevant programs to enhance critical thinking in curriculum, apply problem-based learning method, improve self-efficacy and leadership, It should be possible to cultivate.

• 한국체육학회지인문사회과학편
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• v.54 no.4
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• pp.329-345
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• 2015

Our study examines the relationship between coach turnover and professional sport team performance using the evidences of Korean professional soccer teams. We collected panel dataset of 304 team-year observations and 96 coaches from Korean professional soccer league during the period of 1983-2013. Among them, our final sample is comprised of 226 observations and 81 coaches manifested for fixed-effect generalized least square (GLS) regression analysis. Drawing on sport management literatures and organizational learning theory, we argue that it takes time for a new head coach to take charge of the team in which the new leader who secure more time to interact with organization members is better able to remodel and improve team performance. Our empirical findings reveal that off-season coach turnover has a positive impact while turnover during the season has its negative influences on team performance. In addition, we find that subsequent team performance in association of off-season coach turnover is comparably better than that of on-season succession. The results show that coach succession rendered from inside the professional soccer team mediates the relationship between coach turnover and team performance. Our findings imply that coach turnover in professional sport teams is a significant factor affecting team performance.

• Journal of The Korean Association For Science Education
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• v.39 no.5
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• pp.573-584
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• 2019

It is necessary to look at the essence of STEAM education from the viewpoint of the teacher who is the subject of education execution. We carry out questionnaires and telephone interviews for the purpose, definition, change, etc. of STEAM education from eight elementary, middle, and high teachers who are rich in policy and field application experience. As a result of the analysis, the purpose of the STEAM education that the specialists mentioned includes the active participation of the students. Most experts pointed out that the definition of STEAM education is ambiguous. So, it is necessary to express a clear goal of STEAM education. The category and level meaning "fields" from "a convergence of two or more fields" are not indicative definitions, but can be different depending on the situation, considering the context of activities and the level of students. The perception of the experts on framework may be a guide for STEAM education and stumbling block. It is necessary for "Context" to shift away from the emphasis on the real life connection and to the emphasis on the interest of the student and the guidance of the class. "Creative design" must be based on trial and error in the process of solving problems. "Emotional touch" needs to correct elements that cannot be observed, evaluated, and applied to lessons that are elements of emotional experience. As for the expansion of STEAM education, most expert teachers have recognized that STEAM education is becoming increasingly stable and that policy change has continued to slow the pace of stabilization.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.