• Journal of KIISE:Software and Applications
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• 제30권3_4호
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• Journal of Digital Convergence
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• 제16권3호
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• pp.201-210
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• 2018

WorldJob+, being operated by The Human Resources Development Service of Korea, provides a recruitment support services to overseas companies wanting to hire talented Korean applicants and interns, and support the entire course from overseas advancement information check to enrollment, interview, and learning for young job-seekers. More than 300,000 young people have registered in WorldJob+, an overseas united information network, for job placement. To innovate WorldJob+'s services for young job-seekers, Splunk, a powerful platform for analyzing machine data, was introduced to collate and view system log files collected from its website. Leveraging Splunk's built-in data visualization and analytical features, WorldJob+ has built custom tools to gain insight into the operation of the recruitment supporting service system and to increase its integrity. Use cases include descriptive and predictive analytics for matching up services to allow employers and job seekers to be matched based on their respective needs and profiles, and connect jobseekers with the best recruiters and employers on the market, helping job seekers secure the best jobs fast. This paper will cover the numerous ways WorldJob+ has leveraged Splunk to improve its recruitment supporting services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제18권1호
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.

• Journal of Internet Computing and Services
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• 제21권2호
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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.

• Journal of the Korean Chemical Society
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• 제51권1호
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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 the Korea Contents Association
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• 제16권4호
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• pp.204-210
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• 2016

The reason to research the musical is it has a lot of useful things for the various studies department not only Korea Musical Theatre own although it has been a successful musical theater on the Off-Broadway by Reboot culture era. Even though does not release on Korea, the popular of the show and powerful results of environments have delivered through the international magazines and Youtube channels to Korea. To study of Musical will be lead us to the world which adopted to the social problems as the youth school violence, family communication hurdle, and religion missing by script not only the musical drama but the interpretation for Teen-agers social problem. There are many kinds of Neo educations are proved by smart learning as STEAM. The students who have been studied with the smartphone, I-pad, personal computer, or laptop as smart tools for class are familliar as feedback processing speedly. It would make them learn the skill for their knowledge of a digital age, but it should not let them how to understand other people's emotion as real although STEAM has emtion part. Besides they have communicated on the social network not the ordinary man but the special ego by themselves, as mention or retweet as like their amusements and make the gossip group. This study would show the perspective for understanding Teen-agers Social Problem and who is the victims today's juvenile problems though the musical based on Jim Taulli's directing.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제42권3호
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• pp.17-28
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• 2005

Recently intelligent characters in computer games have been an important element more and more because they continually stimulate gamers' interests. As a typical method for implementing such intelligent characters, neural networks have been used for training action patterns of opponent's characters and game rules. However, some of the game rules can be abruptly changed and action properties of garners in on-line game environments are quite different according to gamers. In this paper, we address how a neural network adapts to those environmental changes. Our adaptation solution includes two components: an individual adaptation mechanism and a group adaptation mechanism. With the individual adaptation algorithm, an intelligent character steadily checks its game score, assesses the environmental change with taking into consideration of the lastly earned scores, and initiates a new learning process when a change is detected. In multi-user games, including massively multiple on-line games, intelligent characters confront diverse opponents that have various action patterns and strategies depending on the gamers controlling the opponents. The group adaptation algorithm controls the birth of intelligent characters to conserve an equilibrium state of a game world by using a genetic algorithm. To show the performance of the proposed schemes, we implement a simple fighting action game and experiment on it with changing game rules and opponent characters' action patterns. The experimental results show that the proposed algorithms are able to make intelligent characters adapt themselves to the change.

• Archives of design research
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• 제17권1호
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• pp.309-318
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• 2004

As the mobile market has been expanded and segmented, a mobile market for kids could be possibly appeared sooner or later. Then, it is necessary to develop a new contents for the new media - a mobile game hardware for kids. These days, kids are most interested in computer games, and they do not have enough time to play with peers. Therefore, in this paper, edutainment game contents based on the wireless internet, are developed. The game could supply kids' learning, fun and especially, peer interaction. In order to develop a game contents through user centered design process, the state of art in mobile hardware and contents was examined, a secondary research and interviews and survey was conducted to understand users. Then, when ideas for game contents has suggested, behavior prototype test was done to verify and modify contents. The suggested game contents in this study, is a occupation simulation game, in which kids simulate their own future career and learn related knowledge in a unintentional way. The result of the study suggests the new direction of edutainment game contents and platform. Also, this study shows the representation of user-centered contents developing process for kids, which could be helpful for the following studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제20권8호
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• pp.139-148
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• 2019

Fostering science-gifted individuals are very important for the future of the nation, and it is especially important to cultivate information-gifted individuals in the age of the fourth industry. There is no standardized curriculum for each gifted education center of the University. Therefore, in this study, we analyzed how effective the curriculum developed on the basis of computing thinking is to affect the characteristics of the information-gifted individuals. The curriculum developed on the components of computing thinking was applied to the information-gifted students of K University. In order to verify the effectiveness of the curriculum, we developed a creative personality test and an intrinsic motivation test, and conducted tests before and after the training. We compared pre-post test results by t-test with R program. The creative personality test consisted of 36 items with 6 factors: risk-taking, self - acceptance, curiosity, humor, dominance, and autonomy. The intrinsic motivation test consisted of 20 items with 5 items: curiosity and interest oriented tendency, challenging learning task preference orientation, independent judgment dependency propensity, independent mastery propensity, and internal criterion propensity. The effect of the curriculum on the creative personality of the experimental group was significant (0.009, 0.05). The significance level of the intrinsic motivation was 0.056 and was not significant at the 0.05 level of significance.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제20권2호
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.