• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.440-447
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• 2011

Selecting a suitable place is to determine the attributive conditions and qualified areas for the aim as factors and is to be fulfilled systematically for selecting the area which satisfies all these. This research tries to achieve a rational suitability analysis of residential development using the GIS modeling method and the hierarchical analysis process. A spatial and attributive analysis has been systematized for selecting a suitable place for the study and GIS analysis model has been used for the effective conclusion drawing for different levels. As a next step, a quantitative and qualitative evaluation index was created through complex consideration of the criteria and decision factors of the location selection, and weights were added depending on the relative importance of these factors. In particular, 3D terrain model simulation method has been used in order to reflect the aesthetic factors of the scenery which is an element of the subjective evaluation factors and considered qualitative and subjective evaluation factors which were not considered for the existing AHP technique. After the research, a location that satisfies complex requirements was found rapidly and accurately through the GIS model and hierarchical analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.9-16
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• 2002

This paper proposes a new 3D modeling technique using disparity-motion relationship and feature points. To generate the 3D model from real scene, generally, we need to compute depth of model vertices from the dense correspondence map over whole images. It takes much time and is also very difficult to get accurate depth. To improve such problems, in this paper, we only need to find the correspondence of some feature points to generate a 3D model of object without dense correspondence map. The proposed method consists of three parts, which are the extraction of object, the extraction of feature points, and the hierarchical 3D modeling using classified feature points. It has characteristics of low complexity and is effective to synthesize images with virtual view and to express the smoothness of Plain regions and the sharpness of edges.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.125-136
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• 2011

Ground-level ozone, an air pollutant that is monitored by the Environmental Protection Agency (EPA), damages human health by irritating the respiratory system, reducing lung function, damaging lung cells, and aggravating asthma and other chronic conditions. In March 2008, the EPA strengthened ozone standards by lowering acceptable limits from 84 parts per billion to 75 parts per billion. Here epidemiologic data is used to study the effects of ozone regulation on human health and assessed how various regulatory standards for ozone may affect nonaccidental mortality, including respiratory-related deaths during ozone season. The assessment uses statistical methods based on hierarchical Bayesian models to predict the potential effects of the different regulatory standards. It also analyzes the variability of the results and ho they are impacted by different modeling assumptions. We focused on the technical an statistical approach to assessing relationship between new ozone regulations and mortality while other researches have detailed the relationship between ozone and human mortality. We shows a statistical correlation between ozone regulations and mortality, with lower limits of acceptable ozone linked to a decrease in deaths, and projects that mortality is expected to decrease by reducing ozone regulatory standards.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.217-220
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• 2001

The fuzzy equalization method does not require the usual learning step for generating fuzzy rules. However it is heavily depend on the given input-output data set. So, we adapt an hierarchical scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership functions obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to the Rice taste data and got better results than previous ones.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.529-547
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• 2011

This paper presents the global-local finite cover method (GL-FCM) that is capable of analyzing structures involving local heterogeneities and propagating cracks. The suggested method is composed of two techniques. One of them is the FCM, which is one of the PU-based generalized finite element methods, for the analysis of local cohesive crack growth. The mechanical behavior evaluated in local heterogeneous structures by the FCM is transferred to the overall (global) structure by the so-called mortar method. The other is a method of mesh superposition for hierarchical modeling, which enables us to evaluate the average stiffness by the analysis of local heterogeneous structures not subjected to crack propagation. Several numerical experiments are conducted to validate the accuracy of the proposed method. The capability and applicability of the proposed method is demonstrated in an illustrative numerical example, in which we predict the mechanical deterioration of a reinforced concrete (RC) structure, whose local regions are subjected to propagating cracks induced by reinforcement corrosion.

• Journal of the Korean Society of Safety
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• v.12 no.1
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• pp.60-70
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• 1997

Since, human error is a major factor contributing to disaster during start-up of operation in Boiler plant. it is necessary to develop an automation system which prevent mode of operation that are known to be dangerous and to bring a loss of energy. The aim of this study is to suggest a model for the computer-aided synthesis of operation sequence as a part of automation system for start-up operation. Synthesis is accomplished by the formation of a hierarchical network of goals which decide sequence of operations. Hierarchical Network is formed by using method which upper goals ( i.e. upper operation al situation) are classified by the function of themselves into lower goals (i.e. lower operational situation). Knowledge for deciding operation sequence is generated by putting In order the knowledge of hazard operation and energy management.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.19-35
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• 2006

We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.5-5
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• 1992

The DEVS(discrete event system specification) formalism describes a discrete event system in a hierarchical, modular form. DEVSIM++ is C++ based general purpose DEVS abstract simulator which can simulate systems to be modeled by the DEVS formalism in a sequential environment. We implement P-DEVSIM++ which is a parallel version of DEVSIM++. In P-DEVSIM++, the external and internal event of models can be processed in parallel. To process in parallel, we introduce a hierarchical distributed simulation technique and some optimistic distributed simulation techniques. But in our algorithm, the rollback of a model is localized itself in contrast to the Time Warp approach. To evaluate its performance, we simulate a single bus multiprocessor architecture system with an external common memory. Simulation result shows that significant speedup is made possible with our algorithm in a parallel environment.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1105-1112
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• 2002

Nowadays the information exchange based on XML such as B2B electronic commerce is spreading. Therefore a systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for concerning the connection between XML application and relational databases. But because XML data has hierarchical structure and relational databases can store only flat-structured data, we need to make a conversion rule which changes the hierarchical architecture to a 2-dimensional format. Accordingly the modeling methodology for storing such structured information in relational databases is needed. In order to build good quality application systems, modeling is an important first step. In 1997, the OMG adopted the UML as its standard modeling language. Since industry has warmly embraced UML, its popularity should become more important in the future. So a design methodology based on UML is needed to develop efficient XML applications. In this paper, we propose a unified design methodology for XML applications based on relational database using UML. To reach these goals, first we introduce a XML modeling methodology to design W3C XML schema using UML and second we propose data modeling methodology for relational database schema to store XML data efficiently in relational databases.