• Journal of Plant Biotechnology
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• v.49 no.1
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• pp.46-60
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• 2022

The genetic variability and population structure of apple mosaic virus (ApMV) have been studied; however, synonymous codon usage patterns influencing the survival rates and fitness of ApMV have not been reported. Based on phylogenetic analyses of 52 ApMV coat protein (CP) sequences obtained from apple, pear, and hazelnut, ApMV isolates were clustered into two groups. High molecular diversity in GII may indicate their recent expansion. A constant and conserved genomic composition of the CP sequences was inferred from the low codon usage bias. Nucleotide composition and relative synonymous codon usage (RSCU) analysis indicated that the ApMV CP gene is AU-rich, but G- and U-ending codons are favored while coding amino acids. This unequal use of nucleotides together with parity rule 2 and the effective number of codon (ENC) plots indicate that mutation pressure together with natural selection drives codon usage patterns in the CP gene. However, in this combination, selection pressure plays a more crucial role. Based on principal component analysis plots, ApMV seems to have originated from apple trees in Europe. However, according to the relative codon deoptimization index and codon adaptation index (CAI) analyses, ApMV exhibited the greatest fitness to hazelnut. As inferred from the results of the similarity index analysis, hazelnut has a major role in shaping ApMV RSCU patterns, which is consistent with the CAI analysis results. This study contributes to the understanding of plant virus evolution, reveals novel information about ApMV evolutionary fitness, and helps find better ApMV management strategies.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.49-51
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• 2001

데이터 마이닝은 KDD의 분야로서, 의미 있는 정보와 관심 있는 행동 패턴을 추출해 나가는 과정이다. WWW의 발전으로, 웹 데이터가 거대해지고 있다. 이러한 데이터 마이닝 분야에서도, 웹 사용 마이닝의 목적은 의미 있는 사용자 행동 패턴을 찾아내는 것이다. 특히 현재 전자상거래가 널리 활성화되고 있는 환경에서, 사용자의 특성을 발견해내는 것은 매우 중요한 부분이다. 사용자의 특성에 따라 사용자에게 상품을 추천하거나 메일을 보내는 것이나 사용자에게 적절하게 사이트를 구축하는 것이 가능하다. 전처리 과정을 통해서 추출된 트랜잭션 데이터를 모호한 사용자의 요구를 분석할 수 있는 퍼지 집합으로 변형시켜 Fuzzy Association Rule을 통해 분석한다. 그리고 분석된 결과에 대한 규칙을 사용자의 피드백을 통해서 다시 분석하는 과정을 거치게 된다. 사용자의 요구 사항을 적절히 반영할 수 있다.

• Journal of the Korean Institute of Rural Architecture
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• v.8 no.3
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• pp.51-58
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• 2006

It is a study about an architectural agreement contents of Kyoto in Japan. For will including in the near future, new system need to solve people misunderstanding worrying about excessive restriction, and strive for interests among construction, as well as it is helpful to central administration for system propulsion finance and regional administration having to work practical. This study is about an Architectural rule on the architectural agreement contents in agreement of residents. Because This rule is necessary to introduce in Korea, because is possible to conserve regional characteristic in urban.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1141-1144
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• 2012

최근의 SW 개발환경은 네트워크 환경이 발달하고 복잡한 비즈니스를 구현하기 위해 분산 컴퓨팅 환경으로 옮겨진 상황이다. 따라서, 시스템간의 쉬운 연결성을 보장하여 자원의 낭비를 줄이고 재사용하며 활성화 할 수 있는 플랫폼을 갖출 수 있는 SOA(Service Oriendted Architecture)의 활용이 필요한 시점이다. 이런 복잡한 니즈의 비즈니스를 구현함에 있어 업무 규칙을 별도로 관리하고 룰엔진에 의해 판단을 할 수 있다면, 프로그램 코드로부터 업무를 완전히 분리해낼 수 있다 본 논문에서는 이러한 진일보한 사상을 조합하여 비즈니스 구현에 집중하고 결합성은 낮출 수 있는 SW 개발 아키텍쳐를 제시해본다.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.73-83
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• 2011

In the manufacturing system, production-planning is very important in effective management for expensive production facilities and machineries. To enhance efficiency of Manufacturing Execution System(MES), a manufacturing system that reduces the difference between planning and execution, certain production-planning needs a dispatching rule that is properly designed for characteristic of work information and there should be a appropriate selection for the rule as well. Therefore, in this paper dispatching rule will be selected by several simulations based on characteristics of work information derived from process planning data. By constructing information that are from simulation into ontology, one of the knowledge-based-reasoning, production planning platform based on the selection of dispatching rule will be demonstrated. The platform has strength in its wider usage that is not limited to where it is applied. To demonstrate the platform, RacerPro and Prot$\acute{e}$g$\acute{e}$ are used in parts of ontology reasoning, and JAVA and FlexChart were applied for production-planning simulation.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.847-856
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• 2017

In this paper, we propose a system to users which recommends suitable park using linguistic objects by rule-based inference engine which is made with Prolog. According to the function of city park, which provides positive elements to people such as social, psychological, environmental, and physical, Seoul city park is classified into 6 categories. The classified parks are recommended to users based on the rule based expert system. Rule-based object of park recommendation designs nine linguistic objects based on activity, multi-purposiveness, accessibility, and usage of time. This assigns allowed value accordingly. Generated rules by using these values are fired by user's preference, and infer recommended park. Information on preferences is obtained by way of dialogue, in which the user is asked questions about the three elements that are the criteria for choosing a park. As a result, through the park recommendation system, we intend to increase the user's satisfaction of using park and leisure activities.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.93-100
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• 2022

In this paper, we propose a machine learning-based method for supporting resource management of IoT software platforms in a multi-modal sensing scenario. We assume that an IoT device installed with a oneM2M-compatible software platform is connected with various sensors such as PIR, sound, dust, ambient light, ultrasonic, accelerometer, through different embedded system interfaces such as general purpose input output (GPIO), I2C, SPI, USB. Based on a collected dataset including CPU usage and user-defined priority, a machine learning model is trained to estimate the level of nice value required to adjust according to the resource usage patterns. The proposed method is validated by comparing with a rule-based control strategy, showing its practical capability in a multi-modal sensing scenario of IoT devices.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.269-286
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• 2013

The advent of Web 2.0 and social media is taking a leading role of emerging big data. At the same time, however, informational dysfunction such as infringement of one's rights and violation of social order has been increasing sharply. This study, therefore, aims at defining malicious usage, identifying malicious feature, and devising an automated method for classifying them. In particular, the rule-based experiment reveals statistically significant performance enhancement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.163-172
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• 2012

In this study, It is assumed that customers are both usage unit of spare parts and stores of displaying and selling the goods that are installation unit of having the spare parts. The demand pattern through the effective order of spare parts and issue list in installation unit is investigated based on the assumption. Current ASL (Authorized Stockage List) selection of the army has been conducted in the way of using the analysis result of real usage experiences on spare parts used during the Korea War. For this study, ASL selection criteria and procedures based on army regulations and field manuals are specified. Since the traditional method does not presents the association analysis on spare parts used for the current equipment operating and does not have the clear criterion and analysis system about the ASL selection, in order to solve these problems, it was carried out that the association rule is employed for analyzing relationship between the effective order and issue list of the spare parts in point of the spare parts between usage unit and occurring month about purchase spare parts based on the star-schema table. Finally the new ASL selection way using the analysis result is proposed.