• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.33-45
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• 2020

While venture creation is considered to be of high social and economic importance, entrepreneurial outcomes are inherently uncertain and that failure is thus a central feature of entrepreneurship. Although failure in entrepreneurship is pervasive and critical, the impact of prior failure on future entrepreneurship has not received significant attention in the literature. Although failure is a painful and costly experience for entrepreneurs, it can also provide a powerful learning opportunity for those experiencing it. It has been argued that entrepreneurial failure is not just a individual problem but a matter of social concern. As part of the restarting business support system, entrepreneurial re-education program is provided to support failed entrepreneurs. The aim of this study is to examine the effects of failed entrepreneurs' prior entrepreneurial experience and re-education on subsequent venture creation. Moreover, this study also examined the moderating effects of entrepreneurial motivation. For the analyses, we surveyed the entrepreneurs who tried to re-start the subsequent business after the entrepreneurial failure through the "Revitalization Center for Strained Entrepreneur". The result found that failed entrepreneurs who learned a lot from their previous founding experience were more likely to re-start their subsequent business. The failed entrepreneurs who learned a lot from entrepreneurial re-education program were more likely to re-start their subsequent business. Moreover, the positive effect of failed entrepreneurs' previous founding experience and entrepreneurial re-education program on re-starting subsequent business was found to be weaker when entrepreneurial extrinsic motivation was high.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.81-90
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• 2020

The purpose of this study is to study how to apply block-chain technology to prevent data forgery and alteration in the defense sector of AI(Artificial intelligence). AI is a technology for predicting big data by clustering or classifying it by applying various machine learning methodologies, and military powers including the U.S. have reached the completion stage of technology. If data-based AI's data forgery and modulation occurs, the processing process of the data, even if it is perfect, could be the biggest enemy risk factor, and the falsification and modification of the data can be too easy in the form of hacking. Unexpected attacks could occur if data used by weaponized AI is hacked and manipulated by North Korea. Therefore, a technology that prevents data from being falsified and altered is essential for the use of AI. It is expected that data forgery prevention will solve the problem by applying block-chain, a technology that does not damage data, unless more than half of the connected computers agree, even if a single computer is hacked by a distributed storage of encrypted data as a function of seawater.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.13-33
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• 2020

This study proposes a Korean sentimental analysis algorithm that utilizes a letter-unit embedding and convolutional neural networks. Sentimental analysis is a natural language processing technique for subjective data analysis, such as a person's attitude, opinion, and propensity, as shown in the text. Recently, Korean sentimental analysis research has been steadily increased. However, it has failed to use a general-purpose sentimental dictionary and has built-up and used its own sentimental dictionary in each field. The problem with this phenomenon is that it does not conform to the characteristics of Korean. In this study, we have developed a model for analyzing emotions by producing syllable vectors based on the onset, peak, and coda, excluding morphology analysis during the emotional analysis procedure. As a result, we were able to minimize the problem of word learning and the problem of unregistered words, and the accuracy of the model was 88%. The model is less influenced by the unstructured nature of the input data and allows for polarized classification according to the context of the text. We hope that through this developed model will be easier for non-experts who wish to perform Korean sentimental analysis.

• Journal of the Korean Chemical Society
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• v.51 no.1
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• pp.56-64
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• 2007

This study examined the influences of cognitive conflict and anxiety induced by a discrepant event and an alternative hypothesis, attention, and effort on conceptual change. Two hundred three students having misconceptions about density were selected from 462 seventh graders based on the results of a preconception test. Tests of cognitive responses and anxiety to a discrepant event were administered before and after presenting an alternative hypothesis. Computer-assisted instruction (CAI) was then provided to students as a conceptual change intervention. Tests assessing attention and effort allocated to the CAI, and conceptual understanding were administered as posttests. Cognitive conflict induced by a discrepant event was found to increase after presenting an alternative hypothesis. Pre-cognitive conflict induced by only a discrepant event exerted a direct effect on post-cognitive conflict induced by a discrepant event and an alternative hypothesis. Post-cognitive conflict had a direct effect on conceptual change. Pre-anxiety decreased after presenting an alternative hypothesis. Pre-anxiety influenced post-anxiety, and this influenced on conceptual change via effort negatively. Attention had a direct effect as well as an indirect effect on conceptual change via effort. These results suggest that the strategy presenting both a discrepant event and an alternative hypothesis to students in concept learning could facilitate conceptual change by inducing more cognitive conflict or active participation of students through the decrease of anxiety than that presenting a discrepant event only.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.681-689
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• 2019

Web usage pattern discovery is an advanced means by using web log data, and it's also a specific application of data mining technology in Web log data mining. In education Data Mining (DM) is the application of Data Mining techniques to educational data (such as Web logs of University, e-learning, adaptive hypermedia and intelligent tutoring systems, etc.), and so, its objective is to analyze these types of data in order to resolve educational research issues. In this paper, the Web log data of a university are used as the research object of data mining. With using the database OLAP technology the Web log data are preprocessed into the data format that can be used for data mining, and the processing results are stored into the MSSQL. At the same time the basic data statistics and analysis are completed based on the processed Web log records. In addition, we introduced the Apriori Algorithm of Web usage pattern mining and its implementation process, developed the Apriori Algorithm program in Python development environment, then gave the performance of the Apriori Algorithm and realized the mining of Web user access pattern. The results have important theoretical significance for the application of the patterns in the development of teaching systems. The next research is to explore the improvement of the Apriori Algorithm in the distributed computing environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.491-495
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• 2008

The purpose of this study is to analyze the characteristics of IT gifted middle school students. The researcher analyzed the observational assessments of 16 gifted noddle school students through 19 education programs conducted from During the latest 3 years at the Science Gifted Children Education Center. The researcher hypothesized that IT gifted children would be outstanding in computer skills and information processing abilities. But they were not much different from gifted children in the other areas. Therefore there are two suggestions resulted from the study. First, it might not be meaningful to sub-categorize the subjects because of their developmental stages. The tenth grade students observed in this study were in their formal operational period by Piaget. Therefore, it would be desirable to teach them integrated areas rather than separated areas. Second, gifted children could be excellent in most areas. Due to their curiosity, task tenacity, and intellectual abilities, they could show excellence in any areas. Therefore, it is important to elaborate the educational programs so that the gifted children can develop their abilities in each areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.414-419
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• 2020

An artificial intelligence-based cable tension estimation model was developed to expand the utilization of data obtained from cable accelerometers of cable-stayed bridges. The model was based on an algorithm for selecting the natural frequency in the tension estimation process based on the vibration method and an applied artificial neural network (ANN). The training data of the ANN was composed after converting the cable acceleration data into the frequency, and machine learning was carried out using the characteristics with a pattern on the natural frequency. When developing the training data, the frequencies with various amplitudes can be used to represent the frequencies of multiple shapes to improve the selection performance for natural frequencies. The performance of the model was estimated by comparing it with the control criteria of the tension estimated by an expert. As a result of the verification using 139 frequencies obtained from the cable accelerometer as the input, the natural frequency was determined to be similar to the real criteria and the estimated tension of the cable by the natural frequency was 96.4% of the criteria.

• Journal of Science Education
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• v.40 no.1
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• pp.31-51
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• 2016

The purpose of this study was to develop "Movie Production Project" Science-Arts convergence STEAM program for elementary students and investigate the effects of the program on career orientation of science, career awareness and creative personality. Participants were 82 elementary school students. The results of this study were as follows: First, experimental group's total score of career orientation of science was significantly higher than that of comparative group. Among sub-areas, science learning preference, science career preference and perception on science career worth were significantly different between two groups. Experimental group's scores were significantly higher than those of comparative group. Second, experimental group's career awareness total score was significantly higher than that of comparative group including all sub-areas. Third, experimental group's creative personality total score was significantly higher than that of comparative group including 2 sub-areas, independence, openness. Finally, experimental group student's perception on the program showed that it was interesting, a little easy and they hoped to study again.

• Journal of the Korean School Mathematics Society
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• v.12 no.2
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• pp.309-325
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• 2009

The purpose of the study was to investigate the differences between Korean mathematics textbooks and CPMP textbooks in the view of conceptual network, structure of mathematical contents, instructional design, and teaching and learning environment to explore the implications for mathematics education in Korea. According to the results, Korean textbooks emphasized the mathematical structures and conceptual network, on the other hand, CPMP textbooks focused on making connections between mathematical concepts and corresponding real life situations as well as mathematical structures. And generalizing mathematical concepts at the symbolic level was very important objective in Korean textbooks, but in the CPMP textbooks, investigating mathematical ideas and solving problems in diverse contexts including real- life situations were considered very important. Teachers using Korean textbooks preferred an explanatory teaching method with the use of concrete manipulatives and student worksheet, however, teachers using CPMP textbooks emphasized collaborative group activities to communicate mathematical ideas and encouraged students to use graphing calculators when they explore mathematical concepts and solve problems.