• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.150-158
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• 2006

The purpose of this study is to evaluate environment-friendly planning feature in Environment-friendly Certificated apartments and to use the basic planning data of housing. Seven Environment-friendly Certificated apartments have been analyzed. The findings of this study are as follows: Environment-friendly planning features are categorized into 4 items; floor planning feature, material planning feature, universal planning feature and environmental planning feature. Among floor planning features, natural sunlight, built-in closets, and differentiated floor plans are well considered, but the flexible floor plan for resident's lifestyle and green space are lack. Among material planning features, environment-friendly finishing materials, environment-friendly products and energy-efficient double-pane windows are well considered, but implementation for resource savings using recycled materials are lack. Among universal design planning features, removal of threshold and installation of safety device in bathroom are not well considered. Among environmental planning features, usage of alternative energy like solar energy are not applied. The environment-friendly planning features in interior space should be introduced in diverse ways.

• Atmosphere
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• v.23 no.4
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• pp.401-412
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• 2013

East Asia experienced extremely cold weather in January 2011, while the previous December and the following February had normal winter temperature. In this study National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data are used to investigate the characteristic features observed in the meteorological fields such as temperature, sea-level pressure, geopotential height, and wind during this winter period. In January the planetary-wave pattern is dominated by stationary-wave form in the mid-to-high latitude region, while transient waves are significant in the previous month. To understand the planetary-wave features quantitatively, harmonic analyses have been done for the 500-hPa geopotential height field. In the climatological-mean geopotential heights the wave numbers 1, 2, and 3 are dominant during the whole winter. In January 2011 the waves of number 1, 2, and 3 are dominant and stationary as in the climatological-mean field. In December 2010 and February 2011, however, the waves of number 4, 5, and 6 play a major role and show a transient pattern. In addition to the distinctive features in each month the planetary-wave patterns dependent on the latitude are also discussed.

• KIEAE Journal
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• v.14 no.6
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• pp.43-52
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• 2014

Hospital design technology of Korea has recently been exported to underdeveloped countries through the EDCF business. This business reflects our high technology of the hospital design and the regional features that reflect the natural environments, the architectural features and the architectural technology of underdeveloped countries. In accordance with the trend of the global environmental-friendly design market, introduction of environmental-friendly design is needed in the project of hospital for underdeveloped countries. A result of examining the Bangladesh case, the hospital design for the underdeveloped countries already contains a lots of environmental-friendly design elements which have lots of effect. In addition, these environmental elements already contains the advantage and efficiency of operation. Thus, for the success of the hospital design project of the international assistance business, it is necessary actively to discover the environmental-friendly design elements of the region, and to survey the environmental-friendly construction of the region and to make the guidelines of environmental-friendly hospital design during the feasibility study phase.

• Proceedings of the KSRS Conference
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• v.1
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• pp.181-183
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• 2006

Digital topographic map in Korea contains layers of spatial and attribute data for 8 land features such as railroads, watercourses, roads, buildings and etc. Some of the layers such as building and forest don't include any information about height, which can be just prepared by interpretation of remote sensed data or field survey. LiDAR(Light Detection And Ranging) data using active pulse and digital camera provides data about height and form of land features. LiDAR data can be used not only to extract the outline of land features but also to estimate the height. This study presents technical availability for extraction and estimation of land feature's outline and height using LiDAR data which composes of natural and artificial land features, and digital aerial photograph which was taken simultaneously with the LiDAR. The estimated location, outline and height of land features were compared with the field survey data, and we could find that LiDAR data and digital aerial photograph can be a useful source for estimating the height of land features as well as extracting the outline.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.548-551
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• 2007

Among components of digital topographic maps used officially in Korea, only contours have 3D values except buildings and trees that are demanded in landscape planning. This study presented a series of processes for 3Dreconstructing landscape features such as terrain, buildings and standing trees using LiDAR (Light Detection And Ranging) data and aerial digital photo graphs. The 3D reconstructing processes contain 1) building terrain model, 2) delineating outline of landscape features, 3) extracting height values, and 4) shaping and coloring landscape features using aerial photograph and 3-D virtual data base. LiDAR data and aerial photograph was taken in November 2006 for $50km^{2}$ area in Sorak National Park located in eastern part of Korea. The average scanning density of LiDAR pulse was 1.32 points per square meter, and the aerial photograph with RGB bands has $0.35m{\times}0.35m$ spatial resolution. Using reconstructed 3D landscape features, visibility with the growing trees with time and at different viewpoints was analyzed. Visible area from viewpoint could be effectively estimated considering 3D information of landscape features. This process could be applied for landscape planning like building scale with the consideration of surrounding landscape features.

• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Smart Structures and Systems
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• v.15 no.2
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• pp.395-408
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• 2015

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

• Journal of the Korea Furniture Society
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• v.21 no.1
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• pp.54-61
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• 2010

This study was carried out to identify the differences of some macro and microanatomical features between Eunsasi poplar (Populus tomentiglandulosa T. Lee) and Konara oak (Quercus serrata Thunb.). Anatomical features such as vessel and fiber diameter, cross sectional area of ray parenchyma and endwall pit aperture diameter in ray parenchyma were compared. Differences of anatomical features between two species were found statistically significant. Earlywood vessel diameter in poplar and oak increased from pith to bark while it was found almost stable in latewood. Fiber diameter in poplar was higher than oak fiber. Ray area and the pit aperture diameter in endwall of ray parenchyma were found higher in oak than those in poplar.