• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.317-324
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• 2006

Performance-based design concept is needed to evaluate the seismic capacity of building. In this study, the method estimating the performance point of the spatial structures based on capacity spectrum method (CSM) is proposed. And for efficient evaluation for the performance point of the spatial structures, the algorithm to convert spatial structural system to ESDOF system is simulated Its efficiency is confirmed by comparing with time history analysis of full model. And dynamic behaviors of spatial structures are examined by using this method. At last, evaluation of structural performance according to variation of stiffness after plastic deformation on the substructures is carried out.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1697-1705
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• 2008

Several studies made for wireless mesh networks aim to optimize the capacity for wireless networks. Aside from protocol improvements, researches were also done on the physical layer particularly on modulation techniques and antenna efficiency schemes. This paper is concerned with the capacity improvements derived from using spatial diversity with smart adaptive array antennas. The use of spatial diversity, which has been widely proposed for use in cellular networks in order to lessen frequency re-use, can be used in mesh networks both to minimize co-channel interference (CCI) and enable multiple transmissions. This paper aims to study the capacity region and bounds in using smart antennas for single-channel multi-radio systems in relation to the number of spatial diversity or sectors as defined by the beam angle $\beta$.

• Architectural research
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• v.19 no.2
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• pp.27-33
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• 2017

Advances in information and mobile technologies have changed the traditional firm ways of working very flexible, collaborative and innovative, resulting in the changes in work place structures and layouts. Despite the growing body of literature examining the novel ways of working, which is called smart work, there is little academic attentions paid to the spatial aspects of new work places, namely smart offices and smart work centers. This research explores the spatial changes of work places that improve business efficiency and collaboration among workers suitable for the novel ways of working. Conducting in-depth field surveys on selected cases, we analyzed the changes in spatial structure and operation policies of smart offices and smart work centers. From this survey, we observed that the new work places under study take various novel spatial forms and they have flexible operating policies such as flexible seating and flexible work hours. We also found that it would be difficult to change existing business practices and typical ways of performing tasks, without changing the bureaucratic spatial designs and layouts. Future studies are suggested to examine how spatial structures and layouts of offices have impacts on space utilization, collaboration, creativity, and job satisfaction.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.59-67
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• 1998

A quick and automatic detection with no harm to the goods is very important task for improving quality control, process control and labour reduction. In real fields of industry, defect detection is mostly accomplished by skillful workers. A narrow band eliminating spatial filter having characteristics of removing the specified spatial frequency is developed by the author, and it is proved that the filter has an excellent ability for on-line and real time detection of surface defect. By the way,. this spatial filter shows a ripple phenominum in filtering characteristics. So, it is necessary to remove the ripple component for the improvement of filter gain, moreover efficiency of defect detection. The spatial filtering method has a remarkable feature which means that it is able to set up weighting function for its own sake, and which can to obtain the best signal relating to the purpose of the measurement. Hence, having an eye on such feature, theoretical analysis is carried out at first for optimal design of narrow band eliminating spatial filter, and secondly, on the basis of above results spatial filter is manufactured, and finally advanced effectiveness of spatial filter is evaluated experimentally.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.223-233
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• 2021

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

• Journal of the Korean Institute of Educational Facilities
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• v.16 no.5
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• pp.11-18
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• 2009

This study examines the issue of space management of university facilities by an assessment model as part of efforts to deal with the crisis of universities. To this end, the study addressed efficiency issue and structural problems using assessment model factors, with the aim of figuring out legitimacy and allocating methods for this purpose. Selected model factors included utilization ratio, residual ratio, vacancy ratio, and occupancy ratio, while for the latter, we investigated into the present situations of space use, focusing on construction, design, and living dimensions. As a result, the study suggested that in the future universities will resort to extension and rebuilding or new building for their facilities. To ensure space efficiency without conflict, we should follow legitimacy of space allocation and composition, building quality university facilities, creating quality environment, preventing tuition from rising or Improving welfare to keep pace with the new era.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.42-49
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• 2008

A wavelet method is presented in order to improve the computational efficiency of two dimensional unsteady flow problems while maintaining the order of accuracy of conventional CFD schemes. First, by using the interpolating wavelet transformation including decomposition and thresholding, an adaptive dataset to a solution is constructed. Then, inviscid and viscous fluxes are calculated only at the points within an adaptive dataset, which enhances the computational efficiency. Second, thresholding step is modified to maintain the spatial and temporal accuracy of conventional CFD schemes automatically by selecting the threshold value between user-defined value and the magnitude of spatial or temporal truncation error. The wavelet method suggested in this study is successfully applied to various unsteady flow problems and it is shown that the computational efficiency is enhanced with maintaining the computational accuracy of CFD schemes.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.42-49
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• 2008

A wavelet method is presented in order to improve the computational efficiency of two dimensional unsteady flow problems while maintaining the order of accuracy of conventional CFD schemes. First, by using the interpolating wavelet transformation including decomposition and thresholding, an adaptive dataset to a solution is constructed. Then, inviscid and viscous fluxes are calculated only at the points within an adaptive dataset, which enhances the computational efficiency. Second, thresholding step is modified to maintain the spatial and temporal accuracy of conventional CFD schemes automatically by selecting the threshold value between user-defined value and the magnitude of spatial or temporal truncation error. The wavelet method suggested in this study is successfully applied to various unsteady flow problems and it is shown that the computational efficiency is enhanced with maintaining the computational accuracy of CFD schemes.

• Spatial Information Research
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• v.19 no.1
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• pp.117-126
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• 2011

Recently, AR applications provide location-based spatial information by GPS. Also, the spatial information is displayed by the angle of the camera. So far, traditional spatial indexes in spatial database field retrieve and filter spatial information by the minimum bounding rectangle (MBR) algorithm.(ex. R-tree) MBR strategy is a useful technique in the geographic information systems and location based services. But MBR technique doesn't reflect the characteristics of spatial queries in AR. Spatial queries of AR applications have high possibility of the dead space area between MBRs of non-leaf node and query area. We propose triangle node filtering algorithm that improved efficiency of spatial retrieval used the triangle node filtering techniques by exclusion the dead space. In this paper, the proposed algorithm has been implemented on PostgreSQL/PostGIS. Experimental results show the spatial retrieval that using the proposed algorithm better performance than the spatial retrieval that of the minimum bounding rectangle algorithm.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.278-287
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• 2019

Spatial information extraction is to retrieve static and dynamic aspects in natural language text by explicitly marking spatial elements and their relational words. This paper proposes a deep learning approach for spatial information extraction for Korean language using a two-step bidirectional LSTM-CRF ensemble model. The integrated model of spatial element extraction and spatial relation attribute extraction is proposed too. An experiment with the Korean SpaceBank demonstrates the better efficiency of the proposed deep learning model than that of the previous CRF model, also showing that the proposed ensemble model performed better than the single model.