• 정보관리학회지
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• 제20권1호
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• pp.93-119
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• 2003

정보추구행태를 연구한 문헌에서 제시된 모형들을 검토하고, 비교 ·분석하여, 정보추구행태에 관한 경험적 연구 설계에 활용할 수 있는 일반적 모형들을 제시하였다. 어떤 복합적 상황, 직업, 역할, 학문 영역에도 적용할 수 있는 모형에 초점을 맞추어 선택하였다. 논의된 모형은 Wilson(1981. 1996), Krikels(1983). Dervin(1983, 1996), Ellis(1989), Ellis, Cox와 Hall(1993), Kuhlthau(1991), Leckie, Pettigrew와 Sylvain(1996), Johnson(1997)에 의해 제시된 모형들이다. 모형이 구축된 시점을 중심으로 연대순으로 살펴보고, 비교 · 분석하였다.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.96-102
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• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

• Communications for Statistical Applications and Methods
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• 제22권5호
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• pp.507-518
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• 2015

It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

• 한국도서관정보학회지
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• 제32권2호
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• pp.121-144
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• 2001

정보경제학의 탄생과 개념정의 및 연구분야를 간략히 살펴본 후, 정보경제학의 논의와 이해를 위해 반드시 검토되어야 하는 주요개념인 정보경제, 자원, 불확실성과 정보의 가치를 비교적 상세히 고찰하였다. 아울러 모델의 간략한 역사와 모델을 에워싸고 있는 문제점을 검토해 보고, 특히 문헌정보학의 실제와 이론연구의 진단과 실험도구로서 대단한 잠재력을 갖고 있는 사회과학에 관련된 약간의 모델적용을 규명해 보았다.

• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1531-1541
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• 2013

This paper proposes a new method of VaR forecasting using the conditional autoregressive VaR (CAViaR) models and information criteria. Instead of using a single CAViaR model, we propose to utilize several candidate CAViaR models during a forecasting period. By adopting the Akaike and Bayesian information criteria for quantile regression, we can update not only parameter estimates but also the CAViaR specifications. We also propose extended CAViaR models with a constant location parameter. An empirical study is provided to examine the performance of the proposed method. The results suggest that our method shows more stable performance than those using a single specification.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.830-835
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• 2005

4D models help construction planners to develop and evaluate construction plans. However, current analyses using 4D models are mainly visual and limit the quantitative comparison of construction alternatives. This paper explores the usefulness of extracting quantitative information from 4D models to support time-space analyses. We use two 4D models of an industry test case to illustrate how to analyze 4D content quantitatively (i.e., work space areas and distances between concurrent activities). This paper shows how these two types of 4D content can be extracted from 4D models to support 4D-based-analysis and novel presentation of construction planning information. We suggest further research to formalize the content of 4D models to enable comparative quantitative analyses of construction planning alternatives. Formalized 4D content will enable the development of reasoning mechanisms that automate 4D-model-based analyses and provide the information content for informative presentations of construction planning information.

• 한국CDE학회논문집
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• 제18권4호
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• pp.299-307
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• 2013

Introduction of PLM in domestic shipyards is being retarded as ship PLM has yet to firm up return of investment and process integration. To implement a ship PLM system, it is required to share ship CAD model data in various design and manufacturing environments. Lightweight CAD models provide a promising solution for sharing CAD models in the product life cycle, which can expedite implementation of ship PLM in domestic shipyards in the near future. Compared to proprietary CAD models, it is easy for lightweight CAD models to be interfaced with various application systems and be connected to manufacturing information. In this paper, the reason why lightweight CAD models are necessary to implement a ship PLM system is addressed and current implementation results are introduced.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권2호
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• pp.87-95
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• 2015

In this study, we pursue a new direction for system modeling by introducing the concept of granular models, which produce results in the form of information granules (such as intervals, fuzzy sets, and rough sets). We present a rationale and several key motivating arguments behind the use of granular models and discuss their underlying design processes. The development of the granular model includes optimal allocation of information granularity through optimizing the criteria of coverage and specificity. The emergence and construction of granular models of type-2 and type-n (in general) is discussed. It is shown that achieving a suitable coverage-specificity tradeoff (compromise) is essential for developing granular models.

• 대한음성학회지:말소리
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• 제67호
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• pp.79-102
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• 2008

In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

• 상하수도학회지
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• 제28권6호
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• pp.669-679
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• 2014

3D-based BIM(Building Information Modeling) technologies can be utilized effectively as a means of systematic management of facility information for safety assurance and effective maintenance of waterworks facilities. In this study, BIM models of water treatment facilities that can be used as basic data for BIM-based maintenance of waterworks facilities were developed. Information exchange and generality of the developed BIM models were evaluated by conducting interoperability analysis of IFC(Industry Foundation Classes) conversion models. In addition, the application of COBie(Construction Operations Building information exchange) was recommended as an effective countermeasure to deal with technical limitation regarding exchange and utilization of facilities-related information through current IFC models. The results of this study can contribute to the development of BIM-based maintenance system for waterworks facilities.