• 한국디지털건축인테리어학회논문집
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• 제10권3호
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• pp.11-18
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• 2010

Cost estimation through fast and correct quantity take offs are crucial in the process of construction project. The existing methods for cost estimation are mainly based on 2D-based drawings and the estimation result tends to be different according to the estimator's experience, the quality and quantity of used information and estimation time. To solve these problems, the domestic construction industry have recently tried to use the data extracted from 3D data modeling based on BIM(Building Information Modeling) in order to achieve more accurate and objective cost estimation. However it tends to increase dramatically the quantity of information that can be used in cost estimation by estimators. Therefore in order to achieve quality information data from 3D data modeling, the characteristics of the project should be reflected on the 3D model and it is most important to extract information only for cost estimation from the whole 3D model fast and accurately. Thus this study aims to propose the 3D modeling method through Data Normalization which maximizes the usability of 3D Data modeling in cost estimation process.

• Journal of Information Technology Applications and Management
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• 제18권4호
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• pp.95-118
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• 2011

In developing information systems, conceptual modeling is among the most fundamental means. The importance attributed to conceptual modeling has not only given rise to a lot of modeling methods, but also to the "yet another modeling approach (YAMA)" syndrome and the "not another modeling approach (NAMA)" hysteria. Criticism of conceptual modeling methods usually targets their lacking of theoretical foundations. In response to such criticism, various approaches towards theoretical foundations of conceptual modeling have been proposed so far. One of the recent responses to the quest for theoretical foundations of conceptual modeling is the reference to the philosophical ontology. The currently most prominent of diverse approaches towards ontological foundations of conceptual modeling appears to be the Bunge-Wand-Weber (BWW) ontology. Recent approaches attempt to regard BWW ontology as another conceptual data model as well as a criterion for evaluating various conceptual models. However, unfortunately, relatively few researches have been made on interoperability between the Entity-Relationship (ER) model, which is the most dominant conceptual data model, and ontology based model. In this paper, we investigate the interoperability between ontology and the ER model. In detail we (i) reclassify components of ER model with respect to ontology concepts, (ii) identify some components that cannot be directly represented in ontology notation, and (iii) present alternative representations to the components to acquire ontologically clear ER diagrams. Additionally, we (iv) present a set of mapping rules for converting the ontologically clear ER diagram into the corresponding ontology. In a case study, we show the process of converting an ER diagram for a concise Project Management System (PMS) into the ontologically clear ER diagram and the corresponding ontology. We also describe an experiment that we undertook to test whether users understand the Ontologically-Clear ER diagram better.

• Spatial Information Research
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• 제22권6호
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• pp.33-43
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• 2014

최근 실내공간에서 활동하는 인구가 증가함에 따라 3차원 실내공간정보에 대한 관심이 높아지고 있다. 실내공간정보를 포함하는 3차원 실내공간 모델링은 LoD 4 (Level of Detail 4) 수준의 객체지향 형태로 수행되고 있으며, 원시자료에 따라 준공도면, 레이저스캐닝, BIM데이터와 카메라를 이용하여 모델링 데이터를 구축할 수 있다. 3차원 실내공간 모델링을 수행하기 위해 정립된 프로세스는 실내공간 모델링 데이터 구축작업의 기반이 되며 구축된 모델링 데이터는 실내공간 보행자 내비게이션, 시설물관리 및 재난관리 등 다양한 어플리케이션에서 활용가능하다. 그러나 정립된 실내공간 모델링 프로세스 기반으로 수행되는 작업이 매우 복잡하고 모델링 작업에 많은 시간이 소비되어 효율적인 모델링을 하는데 한계가 있다. 따라서 본 연구에서는 효율적인 실내공간 모델링 수행 지원을 목적으로 원시자료의 활용도 평가를 제안한다. 기존 3차원 실내공간 모델링 프로세스 분석을 통해 활용도 평가를 위한 필요요건을 정의하고, 검증 방법을 제안한다. 또한 제안된 방법은 서울시 3차원 실내공간 모델링 프로젝트에서 사용된 준공도면을 적용하여 수행한다.

• Food Science and Biotechnology
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• 제18권1호
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• pp.137-142
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• 2009

One of the most important aspects of conducting this microbial risk assessment (MRA) is determining the model in microbial behaviors in food systems. However, to fully these modeling, large expenditures or newly laboratory experiments will be spent to do it. To overcome these problems, it has to be considered to develop the new strategies that can be used data in the published literatures. This study is to show whether or not the data set from the published experimental data has more value for modeling for MRA. To illustrate this suggestion, as example of data set, 4 published Salmonella survival in Cheddar cheese reports were used. Finally, using the GInaFiT tool, survival was modeled by nonlinear polynomial regression model describing the effect of temperature on Weibull model parameters. This model used data in the literatures is useful in describing behavior of Salmonella during different time and temperature conditions of cheese ripening.

• Biotechnology and Bioprocess Engineering:BBE
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• 제11권1호
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• 정보처리학회논문지A
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• 제8A권1호
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• pp.63-69
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• 2001

In this paper, we present an interactive 3D character modeling and animation including a data management tool for editing the animation. It includes an animation editor for changing animation sequences according to the modified structure of 3D object in the object structure editor. The animation tool has the feature that it can produce motion data independently of any modeling tool including our modeling tool. Differently from conventional 3D graphics tools that model objects based on geometrically calculated data, our tool models 3D geometric and animation data by approximating to the real object using 2D image interactively. There are some applications that do not need precise representation, but an easier way to obtain an approximated model looking similar to the real object. Our tool is appropriate for such applications. This paper has focused on the data management for enhancing the automatin and convenience when editing a motion or when mapping a motion to the other character.

• Journal of Information Processing Systems
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• 제6권3호
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• pp.385-402
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• 2010

Most of the data warehouse (DW) requirements engineering approaches have not distinguished the early requirements engineering phase from the late requirements engineering phase. There are very few approaches seen in the literature that explicitly model the early & late requirements for a DW. In this paper, we propose an AGDI (Agent-Goal-Decision-Information) model to support the early and late requirements for the development of DWs. Here, the notion of agent refers to the stakeholders of the organization and the dependency among agents refers to the dependencies among stakeholders for fulfilling their organizational goals. The proposed AGDI model also supports three interrelated modeling activities namely, organization modeling, decision modeling and information modeling. Here, early requirements are modeled by performing organization modeling and decision modeling activities, whereas late requirements are modeled by performing information modeling activities. The proposed approach has been illustrated to capture the early and late requirements for the development of a university data warehouse exemplifying our model's ability of supporting its decisional goals by providing decisional information.

• Geomechanics and Engineering
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• 제1권1호
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• pp.53-74
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• 2009

In recent years, several computer-aided pattern recognition and data mining techniques have been developed for modeling of soil behavior. The main idea behind a pattern recognition system is that it learns adaptively from experience and is able to provide predictions for new cases. Artificial neural networks are the most widely used pattern recognition methods that have been utilized to model soil behavior. Recently, the authors have pioneered the application of genetic programming (GP) and evolutionary polynomial regression (EPR) techniques for modeling of soils and a number of other geotechnical applications. The paper reviews applications of pattern recognition and data mining systems in geotechnical engineering with particular reference to constitutive modeling of soils. It covers applications of artificial neural network, genetic programming and evolutionary programming approaches for soil modeling. It is suggested that these systems could be developed as efficient tools for modeling of soils and analysis of geotechnical engineering problems, especially for cases where the behavior is too complex and conventional models are unable to effectively describe various aspects of the behavior. It is also recognized that these techniques are complementary to conventional soil models rather than a substitute to them.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.100-103
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• 2008

Recently Development of construction system that subjective operators share and control information efficiently based on the three-dimensional space and design information throughout life cycle of construction project is progressing dynamically. In case of civil structures which are infrastructure, Demand for structure of complex system which has multi-functions such as super and smart bridges and express rails is increasing and system development which computerizes and integrates process of structure design is in need. For that, research about link way between three dimensional modeling data and structure analysis programs should be preceded. In this research, therefore, research about interface design between three dimensional virtual modeling data to automate efficient civil-structure-design and nonlinear finite element analysis program which is made up of reinforced concrete material model that express material's character clearly.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.