• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.723-735
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• 2003

This research focuses ell an approach for the building of a requirements model for the development of large-scale information systems. It will suggest a set of requirements engineering processes as a procedure of the implementation for building the requirements model. It will also emphasise the evaluation requirements model aimed to refine and complete the requirements model by the different user groups as a cross reference. This paper provides an advanced user-construction requirements within the Event Flow Diagram as a set of requirements engineering process.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.88-89
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• 2014

A vector-photo is a photography which contain image and 5W1H information. Objects pictured and an image in a vector-photo can be linked by 5W1H information in the vector-photo. This study discuss a positioning module to link between vector-photos and 3D BIM model. The module developed in this study can be utilized in a system that can link the vector-photos with objects in BIM model.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.153-161
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• 2002

Recently our government operates earned value management system (EVMS) for improving work management system of the construction projects over specific scale. The EVMS is based on the integrated management between construction cost and schedule. the existing systems, however, are focused on the cost management by using work quantity. This study suggests a work management model to integrate construction cost with activity information. The model introduces a work task concept as a tool that can connect construction rest to activity information. The suggested model in this study is verified by using actual data for the applicability to practical construction projects.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.41-52
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• 2019

The purpose of the work is to develop a simple solar irradiance prediction model using a deep learning method, the LSTM (long term short term memory). Other than existing prediction models, the proposed one uses only the cloudiness among the information forecasted from the national meterological forecast center. The future cloudiness is generally announced with four categories and for three-hour intervals. In this work, a daily irradiance pattern is used as an input vector to the LSTM together with that cloudiness information. The proposed model showed an error of 5% for learning and 30% for prediction. This level of error has lower influence on the load prediction in typical building cases.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.565-572
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• 2014

A systematically structured 3D information model can be effectively utilized in many application fields. This study presents the methodology of generation and application of the city information model, which is suited for the management of the flood damage information. To ensure the interoperability and re-usability of the information, this study develops application methodology to utilize the information attributes included in the CityGML as an open standard data schema and extension methodology for additional information attributes. Also, an effective combining method for topography and building model was proposed. Using the data extracted from the combined information model based on a real flood damage case, it was shown that the numbers of casualties and isolation during a flood can be predicted and as a result, the applicability of the data model on flood damage estimation is naturally verified.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.153-154
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• 2012

The accuracy of cost estimation at an early stage in school building project is one of the critical factors for successful completion. So many method and techniques have developed that can estimate construction cost using limited information available in the early stage. Among the techniques, Support Vector Machine(SVM) has received attention in various field due to its excellent capacity for self-learning and generalization performance. Therefore, the purpose of this study is to verify the applicability of cost prediction model based on SVM in school building project at the early stage. Data used in this study are 139 school building cost constructed from 2004 to 2007 in Gyeonggi-Do. And prediction error rate of 7.48% in support vector machine is obtained. So the results showed applicability of using SVM model for predicting construction cost of school building projects.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.53-59
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• 1997

Current CAD systems used in the AEC community have some critical problems. One of them is that they hardly support design collaboration. Thus designers and engineers are hard to transfer design knowledge from one discipline to another. What we need is a common building database which creates and manages building plans/models and relevant design knowledge consistently and effectively. This paper presents a powerful CAD editor, called UNIFORM, which is being developed. Currently UNIFORM includes three main modules: a plan generator, a 3-D model generator, and component databases. A plan generator, called UNIFORM PLANNER, creates a plan which contains semantically-rich information of building. Each component in the plan can be presented in various ways and connected to component databases that contain knowledge of building components such as windows, doors, walls, etc. Based on the plan UNIFORM MODELER, another module of the program, generates a three dimensional building model which could be a multiple-story building. One of the main ideas behind the system is that it generates and maintains a common building form that can be easily delivered to other members of the project team. Thus it is expected to increase system integration, team interactions, and productivity.

• ETRI Journal
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• v.33 no.4
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• pp.537-546
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• 2011

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

• The Journal of Information Systems
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• v.31 no.4
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• pp.75-100
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• 2022

Purpose Recently, hyper-realistic virtual influencers have received much attention in the field of corporate marketing. However, there is a lack of research that suggests specific processes affecting behavioral intentions through trust and attachment between virtual influencers and consumers. In addition, previous studies have failed to consider the characteristics of hyper-realistic virtual influencers. Therefore, this study investigates the effects of trust and attachment to hyper-realistic virtual influencers on consumers' behavioral intentions based on the trust-building model. Design/methodology/approach Based on the previous research, seven antecedent factors for trust-building were derived: Reality, Attractiveness, Awareness, Interactivity, Professionalism, Social Presence, and Predictability. Next, the survey was conducted on Chinese people who had experienced interacting with hyper-realistic virtual influencers on social network services within the last 3 months at the time of data collection. A total of 326 respondents were used for the final analysis and hypotheses were tested using a structural equation model technique. Findings The results of this study are as follows. First, this study confirmed that reality, attractiveness, awareness, social presence, and predictability as antecedent factors for trust-building of hyper-realistic virtual influencers have a positive effect on trust. Second, this study confirmed that trust in hyper-realistic virtual influencers has a significant positive effect on attachment. Lastly, this study confirmed that trust and attachment to the hyper-realistic virtual influencer significantly and positively affect relationship retention and purchase intentions.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.3
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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.