• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.27-33
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• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.385-397
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• 2023

This study presents an experiment and analysis to compare the seismic behavior of full-scale reinforced concrete beam-column joint strengthened by prestressed steel strips, externally bonded steel plate, and CFRP sheets. For experimental investigation, five specimens, including one joint without any retrofitting, one joint retrofitted by externally bonded steel plate, one joint retrofitted by CFRP sheets, and two joints retrofitted by prestressed steel strips, were tested under cyclic-reserve loading. The failure mode, strain response, shear deformation, hysteresis behavior, energy dissipation capacity, stiffness degradation and damage indexes of all specimens were analyzed according to experimental study. It was found that prestressed steel strips, steel plate and CFRP sheets improved shear resistance, energy dissipation capacity, stiffness degradation behavior and reduced the shear deformation of the joint core area, as well as changed the failure pattern of the specimen, which led to the failure mode changed from the combination of flexural failure of beams and shear failure of joints core to the flexural failure of beams. In addition, the beam-column joint retrofitted by steel plate exhibited a high bearing capacity, energy consumption capacity and low damage index compared with the joint strengthened by prestressed steel strip, and the prestressed steel strips reinforced joint showed a high strength, energy dissipation capacity and low shear deformation, stirrups strains and damage index compared to the CFRP reinforced joint, which indicated that the frame joints strengthened with steel plate exhibited the most excellent seismic behavior, followed by the prestressed steel strips.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.313-320
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• 2023

The cumulative registration status of dogs is from 1.07 million in 2016 to 2.32 million in 2020. Animal registration is increasing by more than 10% every year, and accordingly, a name must be decided when registering a dog. We want to give a name that fits the characteristics of a dog's appearance, but there are many difficulties in naming it. This paper explains the development of a system for recognizing dog images and recommends dog names based on similar objects or food. This system extracts similarities with dogs' images through models that learn images of various objects and foods, and recommends dog names based on similarities. In addition, by recommending additional related words based on the image data of the result value, it was possible to provide users with various options, increase convenience, and increase interest and fun. Through this system, it is expected that users will be able to solve their concerns about naming their dogs, check names that suit their dogs comfortably, and give them various options through various recommended names to increase satisfaction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.151-154
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• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.326-327
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• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.472-482
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• 2023

The grid-type or room-and-pillar method is applied for the purpose of mining horizontally buried minerals. In this study, design and pilot test were performed to apply the room-and-pillar method which uses natural rock as a rock pillar to the construction of underground space. The area where the pilot test was conducted was in stone mine and had good rock conditions with an appropriate depth (about 30 m) to apply the pilot test. The pilot test site was selected by reviewing accessibility and ground conditions and then site construction was performed through detailed ground investigation and design. The pilot test was designed with a column shape of 8×8 m and a cross-section of 8×12 m. The blasting pattern was determined through test blasting at the site, and blasting of 3 m excavation with 89 holes was performed. Through field observations, the average width of 12.5 m and the average height of 8.3 m were measured. Therefore, it is possible to proceed similar to the cross-sectional shape considered in the design.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.67-76
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• 2017

In industrial site in various fields it will be generated in combination with large amounts of data have a correlation. It is able to collect a variety of data in types of industry process, but they are unable to integrate each other's association between each process. For the data of the existing industry, the set values of the molding condition table are input by the operator as an arbitrary value When a problem occurs in the work process. In this paper, design the fusion and analysis processing model of data collected for each industrial type, Prediction Case(Automobile Connect), a through for corporate earnings improvement and process manufacturing industries such as master data through standard molding condition table and the production history file comparison collected during the manufacturing process and reduced failure rate with a new molding condition table digitized by arbitrary value for worker, a new pattern analysis and reinterpreted for various malfunction factors and exceptions, increased productivity, process improvement, the cost savings. It can be designed in a variety of data analysis and model validation. In addition, to secure manufacturing process of objectivity, consistency and optimization by standard set values analyzed and verified and may be optimized to support the industry type, fits optimization(standard setting) techniques through various pattern types.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.585-600
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• 2012

Security issues in online games are increasing as the online game industry grows. Real money trading (RMT) by online game users has become a security issue in several countries including Korea because RMT is related to criminal activities such as money laundering or tax evasion. RMT-related activities are done by professional work forces, namely gold-farmers, and many of them employ the automated program, bot, to gain cyber asset in a quick and efficient way. Online game companies try to prevent the activities of gold-farmers using game bots detection algorithm and block their accounts or IP addresses. However, game bot detection algorithm can detect a part of gold-farmer's network and IP address blocking also can be detoured easily by using the virtual private server or IP spoofing. In this paper, we propose a method to detect gold-farmer groups by analyzing their connection patterns to the online game servers, particularly information on their routing and source locations. We verified that the proposed method can reveal gold-farmers' group effectively by analyzing real data from the famous MMORPG.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.537-549
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• 2007

The characteristics of the mineralization and geology in the northern Mt. Taebaek mining district are found to be similar with those reported from Nevada district where the Carlin-type gold deposit occurs characteristically as repeated metallic ore deposits in space and time. Though two spots of hs and several spots of Sb anomalies were recognized in the Yeongweol area, they have no relationship with any metalliferous mineralization. On the other hand, two spots of As anomaly in the Jeongseon area have shown to be related with metalliferous ore deposits (mainly Ag-Au), and they are closely associated with Sb anomaly. Some elements of altered limestones in the study such as Au, Ag, As, Sb, Cu, Pb, Zn, and Mo area are closely associated together, and are more enriched in the Jeongseon area than in the Yeongweol area. In particular, Sb and As which may reflect the occurrence of the Carlin-type gold deposit are highly enriched. However, the base metals such af Zn and Pb are highly variable according to samples. The patterns of the enrichment factor for Sb and As, as well as those for Ag and Au, are very similar with those reported from the Carlin-type gold deposits in Nevada. These similarities in elemental distribution may imply that hydrothermal ore mineralization in the study areas was possibly originated from a fluid with the characteristics of the Carlin-type gold mineralization found in Nevada, China, and Indonesia. However, the pattern of base metals and Mo are different. This may result from different chemistry and/or mineralogy of host rock in the study areas.