• 한국건축시공학회지
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• 제11권3호
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.395-400
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• 2004

This study consists of three steps of data modeling procedures. The first step is to identify possible items for the data model based on literature review and expert interviews. The second step is to design delineate possible sub-themes, feature classes, feature types, attributes, attribute domains, and their relationships. These are presented in various UML class diagrams, and each feature type is clearly defined and modeled. The data model also shows geometry objects and their topological relationships in UML diagrams. Finally, a standardized data model has been provided to avoid possible conflicts in the field of geographic and Facility Area, and thus this study and the data model will eventually assist in alleviating efforts to build standardized geographic information databases for Facility Area.

• 문화기술의 융합
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• 제5권4호
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• pp.413-420
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• 2019

본 연구의 목적은 기존의 body fat mass 변수와 고콜레스테롤혈증의 연관성연구를 벗어나, 머신러닝기법을 기반으로 body fat mass 변수들의 조합을 이용하여 고콜레스테롤혈증 예측 모델을 개발하는 것이다. 이러한 연구를 위하여 국민건강영양조사 데이터를 기반으로 두 가지 variable selection 메소드와 머신러닝 알고리즘을 이용하여 총 6개의 모델을 생성하였고 질병 예측력을 비교분석하였다. 여러 body fat mass 관련 변수들 중에서 몸통지방량 변수가 고콜레스테롤혈증 예측력이 가장 우수한 변수인 것을 밝혀내었고, 머신러닝 기반 예측모델들 중에서 correlation-based feature subset selection 기반 naive Bayes 알고리즘을 이용한 모델이 0.739의 the area under the receiver operating characteristic curve 값과 0.36의 Matthews correlation coefficient 값을 얻었다. 이러한 연구의 결과는 향후 국내외 대규모 스크리닝 및 대중보건 연구에서 질병예측분야의 중요정보로 활용될 것으로 예상한다.

• Human Ecology Research
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• 제60권4호
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• pp.625-643
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• 2022

The purpose of this study was to explore the trends and core keywords of the secondary school home economics teacher selection test using content analysis and text network analysis. The sample comprised texts of the secondary school home economics teacher 1st selection test for the 2017-2022 school years. Determination of frequency of occurrence, generation of word clouds, centrality analysis, and topic modeling were performed using NetMiner 4.4. The key results were as follows. First, content analysis revealed that the number of questions and scores for each subject (field) has remained constant since 2020, unlike before 2020. In terms of subjects, most questions focused on 'theory of home economics education', and among the evaluation content elements, the highest percentage of questions asked was for 'home economics teaching·learning methods and practice'. Second, the network of the secondary school home economics teacher selection test covering the 2017-2022 school years has an extremely weak density. For the 2017-2019 school years, 'learning', 'evaluation', 'instruction', and 'method' appeared as important keywords, and 7 topics were extracted. For the 2020-2022 school years, 'evaluation', 'class', 'learning', 'cycle', and 'model' were influential keywords, and five topics were extracted. This study is meaningful in that it attempted a new research method combining content analysis and text network analysis and prepared basic data for the revision of the evaluation area and evaluation content elements of the secondary school home economics teacher selection test.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

• 산업기술연구
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• 제28권B호
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• pp.111-116
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• 2008

Since the hydraulic fracturing field testing method was introduced first to Korean geotechnical engineers in 1994, there have been lots of progresses in a hardware system as well as an interpretation tool. The hydrofracturing system of first generation was the pipe-line type, and it has been developed to a wire-line system at their second generation. The current up-to-date system is more compact and is able to be operated by all-in-one system. With a progress in a hardware system, the software for analyzing in-situ stress regime has also been progressed. The shut-in pressure, which is the most ambiguous parameter to be obtained from hydrofracturing pressure curves, can now be acquired automatically from the various methods. While the hardware and software for hydrofracturing tests are being developed during the last decade, the author could accumulate the field test results which can cover the almost whole area of South Korea. Currently these field data are used widely in a feasibility study or a preliminary design step for tunnel construction in Korea. Regarding the difficulties in a site selection and a test performance for the in-situ stress measurement at an off-shore area, the in-situ stress regime obtained from the field experiences in the land area can be used indirectly for the design of a sub-sea tunnel. From the hydrofracturing stress measurements, the trend of magnitude and direction of in-situ stress field was shown identically with the geological information in Korea.

• 한국산학기술학회논문지
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• 제7권2호
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• pp.257-263
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• 2006

취업자의 현장실습 효과에 대해 청운대학교 신소재응용화학과를 졸업한 취업자들의 사례를 조사 연구하였다. 설문조사지는 일반현황 8개 항목과 함께 현장실습 실시 3문항, 문제점 파악 10 문항, 효과 분석 9 문항으로 구성하였다. 2001년-2004년 졸업자중 회수율 67%이었으며 40명의 설문조사 응답지를 분석한 결과, 문제점은 실습업체 선택의 기회가 적었으며 산업체의 현장실습 운용이 체계적이지 못하였다. 현장실습의 효과는 현장실습과 학교 전공수업은 관련성이 많았으며, 진로선택에 도움이 되었다. 취업 후 현재의 회사업무와도 많은 관련이 있었다.

• 대한전자공학회논문지
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• 제27권5호
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• pp.747-755
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• 1990

In this paper, we presented a method of constructing a multiplier and an inverse element generator over finite field GF(3**m). We proposed the multiplication method using a descending order arithmetics of mod F(X) to perform the multiplication and mod F(X) arithmetics at the same time. The proposed multiplier is composed of following parts. 1) multiplication part, 2) data assortment generation part and 5) multiplication processing part. Also the inverse element generator is constructed with following parts. 1) multiplier, 2) group of output registers Rs, 3) multiplication and cube selection gate Gl, 4) Ri term sequential selection part. 5) cube processing part and 6) descending order mod F(X) generation part. Especially, the proposed multiplier and inverse element generator give regularity, expansibility and modularity of circuit design.

• 정보관리연구
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• 제33권2호
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• pp.33-48
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• 2002

본 연구는 연속간행물 선정과 평가에 관한 방법을 살펴보고, 포항공과대학교 SCI 게재논문의 참고문헌 분석을 통하여 학술지 구독의 투자효용성을 평가함으로써, 이용도에 근거한 연속간행물 선정과 장서관리의 기준을 제공하고자 한다.

• 센서학회지
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• 제32권5호
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• pp.313-319
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• 2023

In this study, we propose a method to improve the accuracy of acoustic odometry using optimal frame interval selection for Fourier-based image registration. The accuracy of acoustic odometry is related to the phase correlation result of image pairs obtained from the forward-looking sonar (FLS). Phase correlation failure is caused by spurious peaks and high-similarity image pairs that can be prevented by optimal frame interval selection. We proposed a method of selecting the optimal frame interval by analyzing the factors affecting phase correlation. Acoustic odometry error was reduced by selecting the optimal frame interval. The proposed method was verified using field data.