• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.4
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• pp.107-117
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• 2014

This study tests homogeneity and performs multiple comparison analysis among treatment levels of each factor group through t-test by materials and analysis of variance by structural type and service period. For that descriptive statistical analysis is performed for static and dynamic response characteristics and their ratios of calculated versus measured values based on a good many safety assessment reports for bridges. Homogeneity and post hoc test based on descriptive statistical analysis provide the measures for homogeneity identification among comparison groups in addition to the statistical reference values such as central tendency, variation and shape. This study is expected to be valuable for structural integrity assessment and design by comparing the measured and calculated values with the reference values for the homogeneous group identified, which can help the engineers review the adequacy of the values and put the group database to practical use.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.127-134
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• 2009

This study aims to provide an optimal model for the layout of multiple tower cranes and material stockyards which have multiple candidate positions. In a high-rise building construction, the positional allocation of tower cranes and material stockyard has an effect on the travel time of material hauling. In addition, in case of using multiple tower cranes, specific location of a tower crane allocated to each material determines the efficiency of the works. Current optimal model limited to the optimization of position of single tower crane and material stockyards. This study suggests optimal model both for the positions of multiple tower cranes and material stockyards. Layout of multiple tower cranes requires additional allocation of each crane to each material hauling and control on the minimum distance between tower cranes. This optimization model utilizes genetic algorithm to deal with complex interaction on the candidate positions of multiple tower cranes, material stockyards, and types of materials. In order to identify its utility, case study was performed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.50-68
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• 2024

This study developed a bus route sketch (BRS) methodology for utilizing bus route design and operation steps in practice and evaluated the feasibility of the method. The BRS methodology consists of three steps: transportation zoning suitable for the provider and users of bus transit service; determining the bus operation route based on established transportation zones and path combination; optimizing the operation route based on the estimation of route alternatives in terms of the multi-performance measures from the standpoints of bus-transit service provider and user. The results of a case study showed that the estimation scores from the perspectives of provider and user were improved significantly from 8.83 and 7.13 to 9.50 and 9.89, respectively. Because the BRS method was designated and developed to be suitable for field application for route planning and operation, the method can be used instantly and directly to estimate and adjust the on-operation bus transit line and route design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.564-570
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• 2019

Although some studies have been attempted to utilize 3D spatial information for fire safety and disaster management, it is still not enough to apply it to actual work. Especially, in case of multi-use facilities, many facilities are more vulnerable to rapid response in the event of a disaster due to complexity of facilities, diversity of usage, and specificity of users. In this paper, we propose a method to develop a 3D safety status information platform that combines 3D spatial information and time - varying safety status information for efficient disaster management of multi-use facilities. In detail, first, we analyze the use cases of existing disaster management platform and the needs of business users. Second, based on the analyzed results, target facilities were selected and possible scenarios were created. Finally, we developed platform architecture design and service development strategy. The research results will be used as a basis for future 3D safety status information platform development. This will contribute to improving the safety of multi-use facilities and minimizing damage to disaster vulnerable groups.

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.249-264
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• 2011

A multi-Gaussian kriging approach extended to space-time domain is presented for uncertainty modeling as well as time-series mapping of environmental variables. Within a multi-Gaussian framework, normal score transformed environmental variables are first decomposed into deterministic trend and stochastic residual components. After local temporal trend models are constructed, the parameters of the models are estimated and interpolated in space. Space-time correlation structures of stationary residual components are quantified using a product-sum space-time variogram model. The ccdf is modeled at all grid locations using this space-time variogram model and space-time kriging. Finally, e-type estimates and conditional variances are computed from the ccdf models for spatial mapping and uncertainty analysis, respectively. The proposed approach is illustrated through a case of time-series Particulate Matter 10 ($PM_{10}$) concentration mapping in Incheon Metropolitan city using monthly $PM_{10}$ concentrations at 13 stations for 3 years. It is shown that the proposed approach would generate reliable time-series $PM_{10}$ concentration maps with less mean bias and better prediction capability, compared to conventional spatial-only ordinary kriging. It is also demonstrated that the conditional variances and the probability exceeding a certain thresholding value would be useful information sources for interpretation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.95-114
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• 2022

This study presented the possibility of automatic frost observation and the related image data acquisition through the design and installation of a Multiple-sensor based Frost Observation System (MFOS). The MFOS is composed of an RGB camera, a thermal camera and a leaf wetness sensor, and each device performs complementary roles. Through the test operation of the equipment before the occurrence of frost, the voltage value of the leaf wetness sensor increased when maintaining high relative humidity in the case of no precipitation. In the case of Gapyeong- gun, the high relative humidity was maintained due to the surrounding agricultural waterways, so the voltage value increased significantly. In the RGB camera image, leaf wetness sensor and the surface were not observed before sunrise and after sunset, but were observed for the rest of the time. In the case of precipitation, the voltage value of the leaf wetness sensor rapidly increased during the precipitation period and decreased after the precipitation was terminated. In the RGB camera image, the leaf wetness sensor and surface were observed regardless of the precipitation phenomenon, but the thermal camera image was taken due to the precipitation phenomenon, but the leaf wetness sensor and surface were not observed. Through, where actual frost occurred, it was confirmed that the voltage value of leaf wetness sensor was higher than the range corresponding to frost, but frost was observed on the surface and equipment surface by the RGB camera.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.54-64
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• 2015

The modular construction has several advantages such as high quality of product, safe work condition and short construction duration. The manufacturing planning of modular construction should consider time frame of manufacturing, transport and erection process with limited resources (e.g., modular units, transporter and workers). The manufacturing planning of multi modular construction project manages the modular construction's characteristics and diversity of projects, as a type of modular unit, modular unit quantities, and date for delivery. However, current modular manufacturing planning techniques are weak in dealing with resource interactions and each project requirement in multi modular construction project environments. Inefficient allocation of resources during multi modular construction project may cause delays and cost overruns to construction operation. In this circumstance, this research suggest a manufacturing planning model for schedule optimization of multi project of modular construction, using genetic algorithm as one of the powerful method for schedule optimization with multiple constrained resources. Comparing to the result of the existed schedule of case study, setting optimized scheduling for multi project decrease the total factory producing schedule. By using proposed optimization tool, efficient allocation of resource and saving project time is expected.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Korean journal of communication and information
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• v.42
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• pp.7-43
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• 2008

In this paper, a new viewpoint and practical education method were presented on educational culture related to today's religions and media. For this purpose, this paper considered the theories of religious media pedagogic and the concept of symbo1ic didactics relating to religious symbols in popular culture. In this paper, a total of eight cases of applying symbolic didactics were developed using the example of "The Da Vinci Code", based on the theoretical framework of religious media education and symbolic didactics. For this, the education methods and contents of religious media education were integrated with the teaching plan model of "action and development oriented media education". In order for this education to be applied effectively, experimental studies have to be carried out verifying the learning effects regarding this education. In particular, education for teachers who will tarry out this education is needed. This is because, in media education, the efficiency of education is significantly affected by the capacity of the one who is teaching.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.395-409
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• 2009

The objective of this paper is to illustrate that kriging can provide an effective framework both for integrating remote sensing data and for uncertainty modeling through a case study of sediment grain size mapping with remote sensing data. Landsat TM data which show reasonable relationships with grain size values are used as secondary information for sediment grain size mapping near the eastern part of Anmyeondo and Cheonsuman bay. The case study results showed that uncertainty attached to prediction at unsampled locations was significantly reduced by integrating remote sensing data through the analysis of conditional variance from conditional cumulative distribution functions. It is expected that the kriging-based approach presented in this paper would be efficient integration and analysis methodologies for any environmental thematic mapping using secondary information as well as sediment grain size mapping.