• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.440-443
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• 2005

The wide spread of internet business recently necessitates recommendation systems which can recommend the most suitable product fur customer demands. Currently the recommendation systems use content-based filtering and/or collaborative filtering methods, which are unable both to explain the reason for the recommendation and to reflect constantly changing requirements of the users. These methods guarantee good efficiency only if there is a lot of information about users. This paper proposes an algorithm called 'demand articulate & integration' which can perceive user's continuously varying intents and recommend proper contents. A method of knowledge classification which can be applicable to this algorithm is also developed in order to disassemble knowledge into basic units and articulate indices. The algorithm provides recommendation outputs that are close to expert's opinion through the tracing of articulate index. As a case study, a knowledge base for heritage information is constructed with the expert guide's knowledge. An intelligent recommendation system that can guide heritage tour as good as the expert guider is developed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.4
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• pp.295-299
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• 2004

The prices of domestic green tea products are relatively expensive and price differences within products of the same levels of quality are various. Also, there is no basic criteria on evaluation of green tea quality. To group 43 commercial green tea products into several parts by the principal component and cluster analyses, this work was done by use of 8 chemical constituents which were analyzed by NIR system. The principal component and cluster analyses revealed 8 groups. The first group included 16 products that had lower free amino acid and theanine contents. The second group included 5 products having higher free amino acid and theanine contents, but lower ash contents. The third group included 13 products showing medium values of 8 constituents. The IV group included 4 products having higher contents of moisture, free amino acids, and theanine. The V group included 1 product showing higher moisture but lower catechins contents. The VI group included 2 products that had higher moisture and catechins contents, but lower free amino acid and theanine contents. The VII group had higher moisture and catechins contents. The VIII group had higher ash and vitamin C contents. The free amino acid contents which were the most important in flavor evaluation of green tea quality did highly positively correlate with the contents of total nitrogen $(0.956^{**}),\;theanine\;(0.981^{**}),\;and\;caffeine\;(0.793^{**})$, but negatively with the contents of ash $(-0.884^{**})$. The catechins used as for functional ingredients did correlate with contents of caffeine(+) and vitamin C(-), respectively.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.1-8
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• 2009

With the development of IT convergence technology and the construction of master plan for the four rivers restoration of the government, the importance of the eco-friendly water pollution management is being spotlighted. In this paper, we proposed the effective water pollution management using the reservoir tank automatic classification for improving the water quality and on-line managing efforts of ceo-friendly reservoir tanks. The proposed method defined the seven factors of water pollution evaluation and managed the water pollution according to hydrogen ion concentration(pH), chemical oxygen demand(COD), suspend solid(SS), dissolved oxygen(DO), count of coliform group(MPN), total phosphorus(T-P), and total nitrogen(T-N) using the sensors. We measured the values for the seven factors from the reservoir tank and normalized to ranging from 1 to 9. To evaluate the performance of the water pollution management using the reservoir tank automatic classification, we conducted F-measure so as to verify usefulness. This evaluation found that the difference of satisfaction by the traditional system was statistically meaningful.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.93-100
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• 2007

Internet had spread in all fields with the fast speed during the last 10 years. Lately, wireless network is also spreading rapidly. Also, number of times that succeed attack attempt and invasion for wireless network is increasing rapidly TMS system was developed to overcome these threat on wireless network. Existing TMS system supplies active confrontation mechanism on these threats. However, existent TMS has limitation that new form of attack do not filtered efficiently. Therefor this paper proposes a new method that it automatically compute the threat from the imput packets with vector space model and detect anomaly detection of wireless network. Proposed mechanism in this research analyzes similarity degree between packets, and detect something wrong symptom of wireless network and then classify these threats automatically.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.859-864
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• 2006

The openness of the Web allows any user to access almost any type of information easily at any time and anywhere. However, with function of easy access for useful information, internet has dysfunctions of providing users with harmful contents indiscriminately. Some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people's mental health harm. In the meantime, since Internet is a worldwide open network it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse way, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1469-1474
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• 2014

This research aims to investigate the difference between game graphics which considers key elements and game systems which do them in the rating classification of adult arcade games during reviews. The case of the supreme court about 'The Golden Porker Castle' last year for 3 years presents the basis whether considers the game graphics or the game system during the review for the game. It implies to identify the gambling game device for the adult arcade game. This research try to find the direction for the scientific, systematic rating classification to enhance the reliability and the validity in it.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1777-1783
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• 2021

The use of drones is gradually increasing for the efficient maintenance of large-scale renewable energy power generation complexes. For a long time, photovoltaic panels have been photographed with drones to manage panel loss and contamination. Various approaches using artificial intelligence are being tried for efficient maintenance of large-scale photovoltaic complexes. Recently, semantic segmentation-based application techniques have been developed to solve the image classification problem. In this paper, we propose a classification model using semantic segmentation to determine the presence or absence of failures such as arcs, disconnections, and cracks in solar panel images obtained using a drone equipped with a thermal imaging camera. In addition, an efficient classification model was implemented by tuning several factors such as data size and type and loss function customization in U-Net, which shows robust classification performance even with a small dataset.

• Korean Journal of Construction Engineering and Management
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• v.22 no.6
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• pp.120-130
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• 2021

Recently, the government is reinforcing safety management at construction sites to prevent safety accidents in construction works, and the safety management plan of workers is an important situation. Meanwhile, modular construction is expected to be gradually expanded to middle and high-rise buildings, but active measures to ensure worker safety are insufficient. This study is a preliminary study of the development of a checklist for preventive worker safety management. The purpose of this study is to derive a checklist classification system for the safety management of workers in the field of modular construction by preceding studies, case analysis, and expert advisory opinions. The classification system consists of large categories of factory manufacturing, transportation, and on-site construction, and the sub-system consists of six sub-classes: foundation work, frame work, modular frame installation work, finishing work, and facility work. Among them, the sub-classification of modular frame installation work consists of 12 unit works, centering on module lifting and assembly module work, which are the main construction processes. And the classification system reflects the three main management factors and contents for defined safety management. It is expected that the research results of this study can contribute to efficient safety management at the modular construction site.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.497-506
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• 2022

In recent years, the specialized construction industry has undergone major construction and major industries, and without considering the technical expertise of construction works, the construction industry is promoting the integration and establishment of specialized construction industries according to convenience and abolition of their own industries. As the reorganization plan causes confusion in the production structure and lacks persuasive power by aiming only for industry simplification, it is judged to be desirable to review it according to the detailed characteristics of the specialized construction industry. In this study, -to review the reorganization of a rational classification system that considers the specific nature of the specialization of specialized construction projects, the classification of construction works, major work contents and characteristics, technical expertise, and problems of largescale industry in the case of painting construction and landscaping construction was analyzed. Based on this, aspects to be considered when reorganizing the current professional construction industry classification system are identified and reasonable improvement plans for each industry are suggested.