• Journal of Information Technology Services
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• v.16 no.4
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• pp.137-148
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• 2017

Researches on the Artificial Intelligence has been explosively activated in various fields since the advent of AlphaGo. Particularly, researchers on the application of multi-layer neural network such as deep learning, and various machine learning algorithms are being focused actively. In this paper, we described a development of an artificial intelligence Janggi game based on reinforcement learning algorithm and MCTS (Monte Carlo Tree Search) algorithm with accumulated game data. The previous artificial intelligence games are mostly developed based on mini-max algorithm, which depends only on the results of the tree search algorithms. They cannot use of the real data from the games experts, nor cannot enhance the performance by learning. In this paper, we suggest our approach to overcome those limitations as follows. First, we collects Janggi expert's game data, which can reflect abundant real game results. Second, we create a graph structure by using the game data, which can remove redundant movement. And third, we apply the reinforcement learning algorithm and MCTS algorithm to select the best next move. In addition, the learned graph is stored by object serialization method to provide continuity of the game. The experiment of this study is done with two different types as follows. First, our system is confronted with other AI based system that is currently being served on the internet. Second, our system confronted with some Janggi experts who have winning records of more than 50%. Experimental results show that the rate of our system is significantly higher.

• Journal of Engineering Education Research
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• v.23 no.3
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• pp.49-58
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• 2020

In the era of the fourth industrial revolution, the world is undergoing rapid social change. The purpose of this study is to predict the expected changes and necessary competencies and desired curriculum and teaching methods in the field of mechanical engineering in the near future. The research method was a Delphi study. It was conducted three times with 20 mechanical engineering experts. The results of the study are as follows: In the field of mechanical engineering, it will be increased the situational awareness by the use of measurement sensors, development of computer applications, flexibility and optimization by user's needs and mechanical equipment, and demand for robots equipped with AI. The mechanical engineer's career perspectives will be positive, but if it is stable, it will be a crisis. Therefore active response is needed. The competencies required in the field of mechanical engineering include collaborative skills, complex problem solving skills, self-directed learning skills, problem finding skills, creativity, communication skills, convergent thinking skills, and system engineering skills. The undergraduate curriculum to achieve above competencies includes four major dynamics, basic science, programming coding education, convergence education, data processing education, and cyber physical system education. Preferred mechanical engineering teaching methods include project-based learning, hands-on education, problem-based learning, team-based collaborative learning, experiment-based education, and software-assisted education. The mechanical engineering community and the government should be concerned about the education for mechanical engineers with the necessary competencies in the era of the 4th Industrial Revolution, which will make global competitiveness in the mechanical engineering fields.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.143-152
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• 1993

A long-term water quality study has been initiated by the Korean Ministry of Environment(MOE) - The G-7 Project--in cooperation with two national research institutes, an University research tn and a consulting firm. This study includes the development of computer software for total water quality management system, so called ISWQM (Integrated System of Water Quality Management). ISWQM includes four major components: a GIS database; two artificial intelligence (AI) based expert systems to estimate pollutant loadings and to provide cost-effective wastewater treatment system for small and medium size urban areas; and computer programs to integrate the database and expert systems. ISWQM is to provide user-friendly Decision Support System (DSS) for water quality planners. A GIS was used to create spatial database which stores all the necessary data to n DSS. GIS was also used to integrate the four components of ISWQM from data creation to decision making through Graphic User Interface (GUI). The results from the first phase of this study showed that GIS would provide an effective tool to build DSS using expert system.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.709-716
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• 2020

In social media, when posting a post, tag information of an image is generally used because the search is mainly performed using a tag. Users want to expose the post to many people by attaching the tag to the post. Also, the user has trouble posting the tag to be tagged along with the post, and posts that have not been tagged are also posted. In this paper, we propose a method to find an image similar to the input image, extract the label attached to the image, find the posts on instagram, where the label exists as a tag, and recommend other tags in the post. In the proposed method, the label is extracted from the image through the model of the convolutional neural network (CNN) deep learning technique, and the instagram is crawled with the extracted label to sort and recommended tags other than the label. We can see that it is easy to post an image using the recommended tag, increase the exposure of the search, and derive high accuracy due to fewer search errors.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.427-432
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• 2019

In this paper, we propose three approaches to modeling Android malware. The first method involves human security experts for meticulously selecting feature sets. With the second approach, we choose 300 features with the highest importance among the top 99% features in terms of occurrence rate. The third approach is to combine multiple models and identify malware through weighted voting. In addition, we applied a novel method of eliminating permission information which used to be regarded as a critical factor for distinguishing malware. With our carefully generated feature sets and the weighted voting by the ensemble algorithm, we were able to reach the highest malware detection accuracy of 97.8%. We also verified that discarding the permission information lead to the improvement in terms of false positive and false negative rates.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.99-107
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• 2020

In this paper, we analyze the characteristics of mobile cache, which is used to improve the data access speed when executing applications on mobile devices, and verify the importance of mobile cache through a cache data access experiment. The mobile device market has grown at a fast pace over the past decade; however, battery limitations and size, price considerations restrict the usage of fast hardware. Thus, their performance are supplemented by using a memory buffer structure such as the cache memory. The analysis mainly focuses on cache size, hierarchical structure of cache, cache replacement policy, and the effect these features has on mobile performance. For the experimental data, we applied a data set from a microprocessor system study, originally used to test the cache performance. In the experimental results, the average data access speed on a mobile device showed a performance improvement of up to 10 times with the presence of cache memory than without. Accordingly, the cache memory was helpful for the performance improvement of a mobile device when the specifications were identical.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.761-768
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• 2021

Recently, various platforms and contents for artificial intelligence education have been developed, but artificial intelligence education programs for the lower grades of elementary school are insufficient. Therefore, the purpose of this study is to develop an artificial intelligence education program for learners in the lower grades of elementary school. It was designed using the Novel Engineering with various convergence education research cases for software education. After the first program was developed, it was verified by expert validity test, and the program was modified and developed accordingly. It was necessary to construct a program based on spoken language rather than written language in consideration of the level of learners in the lower grades in the process of acquiring Hangeul, and to secure the number of educational hours through integration between subjects. It is expected that this study can suggest a new direction for artificial intelligence education for elementary and lower grade learners.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.8-13
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• 2019

Recently, In line with the recent trend of the fourth industrial revolution, many companies and institutions have been increasingly applying automated technologies using artificial intelligence to various tasks. Particularly, due to the government's 52-hour workweek system, companies are increasingly struggling with manpower management. Therefore, they are interested in RPA (Robotic Process Automation) for office environment automation for efficient manpower management. It is being introduced in the back-office business in credit card companies, bank, insurance. These RPA solutions require AI-based recognition technology, scripting technology, business software API-related technologies, and various solutions such as Automate One, Automation Anywhere, UiPath, and Blue Prism are provided. This paper analyzes and describes the technology of RPA solution, the market trend, and the efficiency of RPA adoption.

• The Korean Journal of Archival Studies
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• no.54
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• pp.211-248
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• 2017

This study examined ways to improve records management by using the new technology of the Fourth Industrial Revolution. To do this, we selected four technologies that have a huge impact on the production and management of records such as cloud, big data, artificial intelligence, and the Internet of Things. We tested these technologies and summarized their concepts, characteristics, and applications. The characteristics of the changed production records were analyzed by each technology. Because of new technology, the production of records has rapidly increased and the types of records have become diverse. With this, there is also a need for solutions to explain the quality of data and the context of production. To effectively introduce each technology into records management, a roadmap should be designed by classifying which technology should be applied immediately and which should be applied later depending on the maturity of the technology. To cope with changes in the characteristics of production records, a flexible data structure must be produced in a standardized format. Public authorities should also be able to procure Software as a Service (SaaS) products and use digital technology to improve the quality of public services.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.