• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.597-608
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• 2008

Marketing has been used the power of data and information technology in the pursuit of personal marketing of products and service to customers, based on their preferences and needs. We analyzed the performance of twenty six combined(RFM and Confidence) response modeling methods that were proposed by Zahavi and Levin(l997) and Sho, et al.(1999). As a result, we were able to increase about 3.5%p. forecasting accuracy of customers response through combination with confidence(C) that is able to consider characteristics of product than using the single RFM model that is practically the most widely used.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.425-433
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• 2009

Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

• The Journal of Society for e-Business Studies
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• v.1 no.2
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• pp.77-92
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• 1996

In recent years, the manufacturing industry begins to demand the PDM which integarates design and manufacturing information concurrently to reduce the time-to-market of new products. However, current commercialized PDM tools have drawbacks in representing by relational data modeling a variety of data types such as CAD files, images, audio, long text, etc. For this reason, object-oriented approaches are suggested as an alternative. In this paper, using one of object-oriented approaches, Rumbaugh's OMT(Object-Modeling Technique), we propose a data model of drawing information management systems essential for PDM. The scope of the model is limited to the information management for drawings, parts, and product structures. Static, dynamic and functional models are suggested in detail. In the models, the drawing status is classified into on-progress, approved, disposed, and released. Also, parts are classified into products, assemblies, and components.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1597-1600
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• 1991

In this paper, we describe a notion of sensor modeling method in multisensor data fusion using fuzzy set theory. Each sensor module is characterized by its fuzzy constraints to specific features of environment. These sensor fuzzy constraints can be imposed on multisensory data to verify their degree of truth and compatibility toward the final decision making. In comparison with other sensor modeling methods, such as probabilistic models or rule-based models, the proposed method is very simple and can be easily implemented in intelligent robot systems.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.294-305
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• 2004

Highly detailed geometric models are rapidly becoming commonplace in computer graphics and other applications. These complex models, which is often represented as complex1 triangle meshes, mainly suffer from the vast memory requirement for real-time manipulation of arbitrary geometric shapes without loss of data. Various techniques have been devised to challenge these problems in views of geometric processing, not a representation scheme. This paper proposes the new mesh structure for the compact representation and the efficient handling of the highly complex models. To verify the compactness and the efficiency, the memory requirement of our representation is first investigated and compared with other existing representations. And then we analyze the time complexity of our data structure by the most critical operation, that is, the enumeration of the so-called one-ring neighborhood of a vertex. Finally, we evaluate some elementary modeling functions such as mesh smoothing, simplification, and subdivision, which is to demonstrate the effectiveness and robustness of our mesh structure in the context of the geometric modeling and processing.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.50-57
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• 2003

In this paper, an automated design and 3-D modeling system of an axial fan and a boss for cooling towers was developed. API and parametric design Provided by a commercial solid-modeler are engaged to automate modeling process. Design data of the boss are assumed to be given by a user with design experiences while the fan from the fan design program using three-dimensional flow analysis. An algorithm avoiding the interferences between fans and a boss is developed. The design data are registered on the database not only to remove duplicate design but also to transfer the data to ERP system.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.25-40
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• 1996

Modeling of systems for intensive knowledge-based processing requires a modeling methodology that makes efficient access to the information in huge data base models. The proposed level access mothodology is a modeling approach applicable to systems where data is stored in a hierarchical and modular modules of active memory cells(processor/memory pairs). It significantly reduces the effort required to create discrete event simulation models constructed in hierarchical, modular fashion for above application. Level access mothodology achieves parallel access to models within the modular, hierarchical modules(clusters) by broadcasting the desired operations(e.g. querying information, storing data and so on) to all the cells below a certain desired hierarchical level. Level access methodology exploits the capabilities of object-oriented programming to provide a flexible communication paradigm that combines port-to-port coupling with name-directed massaging. Several examples are given to illustrate the utility of the methodology.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4E
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• pp.28-36
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• 1996

In this paper, we propose a new evaluation methodology which can more clearly show the performance of the allophone modeling algorithm generally used in large vocabulary speech recognition. The proposed evaluation method shows the running characteristics and limitations of the modeling algorithm by testing how the variation of phonetic environments of training data affects the recognition performance and the desirable number of free parameters to be estimated. Using the method, we experiment results, we conclude that, in vocabulary-independent recognition task, the phonetic diversity of training data greatly affects the robustness of model, and it is necessary to develop a proper measure which can determine the number of states compromizing the robustness and the precision of the HMnet better than the conventional modeling efficiency.