• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.197-206
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• 2012

A exisiting recommedation system using association rules has the problem, such as delay of processing speed from a cause of frequent scanning a large data, scalability and accuracy as well. In this paper, using a Implicit method which is not used user's profile for rating, we propose the personalized recommendation system which is a new method using the FP-tree mining based on RFM. It is necessary for us to keep the analysis of RFM method and FP-tree mining to be able to reflect attributes of customers and items based on the whole customers' data and purchased data in order to find the items with high purchasability. The proposed makes frequent items and creates association rule by using the FP-tree mining based on RFM without occurrence of candidate set. We can recommend the items with efficiency, are used to generate the recommendable item according to the basic threshold for association rules with support, confidence and lift. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.20-26
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• 2021

In this paper, we studied the rotation angle estimation methods required for image alignment in an image recognition environment. In particular, a rotation angle estimation method applicable to a low specification embedded-based environment was proposed and compared with the existing method using complex moment. The proposed method estimates the rotation angle through similarity mathcing of the 1D projection profile along the radial axis after converting an image into polar coordinates. In addition, it is also possible to select a method of using vector sum of the projection profile, which more simplifies the calculation. Through experiments conducted on binary pattern images and gray-scale images, it was shown that the estimation error of the proposed method is not significantly different from that of complex moment-based method and requires less computation and system resources. For future expansion, a study on how to match the rotation center in gray-scale images will be needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1234-1243
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• 2021

This study intends to provide a forecast of the diffusion of countries participating in a newly proposed G to G mechanism named as the "International Defense Industry Cooperation Program of Korea", modeled after the U.S. Foreign Military Sales(FMS). For this purpose, the study analyses 40 years of statistical data of U.S. FMS customers to find two parameters, coefficient of innovation and imitation, which explain the diffusion in FMS customers. Furthermore, the study forecasts the diffusion in international participation to the proposed mechanism taking account of the differences in the level of government competitiveness and the strength of defense industrial base of Korea and the U.S. This study also provides recommendations for accelerating the desired outcomes under the new program. While Korea is likely to have relative advantages over 'imitators' in the international market, it will need to gain competitiveness in high-level capabilities going beyond the realm of medium-high level systems, and present attractive alternatives for offsets.

• Journal of Climate Change Research
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• v.5 no.1
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• pp.61-70
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• 2014

The amount of greenhouse gas (GHG) emissions has been increasing steadily over the last 3 years (2009~2011), averaging 5.7 percent a year, due to the growth of low cost carriers and the increased demand for air transportations. The present study attempts to investigate the aviation fuel consumption and GHG emissions of Tier 3a type by the flight phase from three aircraft type such as B737-600(routes between Gimpo-Jeju airport), B737-700(routes between Gimpo-Jeju airport and Inchon-Narita), B737-800(routes between Inchon-Narita) using the Flight Operation Quality Assurance(FOQA) data of the year 2011.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.347-353
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• 2019

Recent recommendation systems are developing toward the utilization of high-dimensional data. However, high-dimensional data can increase algorithm complexity by expanding dimensions and be lower the accuracy of recommended items. In addition, it can cause the problem of data sparsity and make it difficult to provide users with proper recommended items. This study proposed an algorithm that classify users' subjective data with objective criteria with fuzzy-AHP and make use of rules with repetitive patterns through fuzzy association rules. Trying to check how problems with high-dimensional data would be mitigated by the algorithm, we performed 5-fold cross validation according to the changing number of users. The results show that the algorithm-applied system recorded accuracy that was 12.5% higher than that of the fuzzy-AHP-applied system and mitigated the problem of data sparsity.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.285-290
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• 2019

This study is a study on the methodology and possibility of making more creative 'Zentangle Art' works through the effective convergence of digital art during the process of Zentangle Art' which draws patterns using writing instruments such as analog pencils and pens to be. In particular, we studied the convergence of traditional pattern and 'Zentangle Art' by applying the method of making using digital author's authoring tool and the pattern symbol of Korean traditional pattern. And It was studied and analyzed in terms of semiotics. In the future, I intend to study the psychological phenomenon and characteristics of the artist during the production of the works. Later, Zentangle artists and researchers will be presenting the continuing direction of content creation and industrial value.

• Explosives and Blasting
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• v.38 no.4
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• pp.26-36
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• 2020

With the increase of expansion and use of the underground space, the possibility of an underground explosion by terrorists is increasing. In this study, after modeling a circular tunnel excavated at a depth of 50m, an explosion load was applied to the inside of the tunnel. As for the explosion load, the explosion load of the maximum explosive amount for six types of vehicle booms proposed by ATF (Bureau of Alcohol, Tobacco, and Firearms) was calculated. For the rock mass around the circular tunnel, three types of rock grades were selected according to the support pattern suggested in the domestic tunnel design. Nonlinear dynamic analysis was performed to evaluate the influence of the ground structure by examining the surface displacement using the explosion load and rock mass characteristics as parameters. As a result of the analysis, for grade 1 rock, the influence on the uplift of the surface should be considered, and for grade 2 and 3 rocks, the influence on a differential settlement should be considered. In particular, for grade 3 rocks, detailed analysis is required for ground-structure interaction within 40m. Also, it is considered that the influence of Young's modulus is the main factor for the surface displacement.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.582-592
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• 2020

The purpose of this research is to analyze the psychological dynamics of the characters in the novel 'vegetarian' of the Han Gang and the relationship patterns in the system by applying object relation theory. 'Vegetarianism' has already been analyzed and reinterpreted in various angles, but if you look at it from the object relationship theory and the systematic perspective, you can understand the inevitable history of the generation through psychological analysis and relation dynamics of the person. First, we will analyze the psychological dynamics of the characters by analyzing the meanings and exploring the meaning with the object relation theory and concept. The psychological analysis and the search process of the characters based on the theory are enough evidence for the counselor to reinterpret the life story of the client in the future clinical scene. In addition, in order to realize ethical but practical clinical education, the field of clinical practice will be extended when analyzing the characters using art. It is suggested that the meaning search through various character analysis needs to be accumulated culturally.

• Smart Media Journal
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• v.9 no.4
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• pp.60-65
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• 2020

The monopulse tracking algorithm can estimate the location of a partner station based on an RF (Radio Frequency) signal. The location of the partner station is estimated based on the monopulse ratio curve (MR-C), which is calculated based on the sum and difference signal patterns of an antenna. Therefore, the range in which the estimated location can be calculated with high accuracy increases in proportion to the linear region of MR-C. In this paper, we proposed a method to extend the linear region of the MR-C curve using the beamforming technique for the tracking antenna system using the active phased array antenna. Simulation results based on the same antenna system, it was confirmed that the linear region of MR-C was enlarged by about twice as much as the general case where the proposed method was not applied.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.