• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.549-557
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• 2022

Due to harsh conditions of construction site, understanding of current feature of terrain and other infrastructures is critical issue for site managers. However, because of difficulties in acquiring the geographical information of the construction sites such as large sites and limited capability of construction workers, comprehensive site investigation of current feature of construction site is not an easy task for construction managers. To address these circumstances of construction sites, this study deduce difficulties and applicabilities of unmanned aerial vehicle in the area of construction site management. To confirm applicability of UAV in civil construction project, case study have been conducted on the road construction project. The result of case study proved that the developed system is one of promising technologies that has been studied in construction site management. To improve applicability of UAV for construction and process management information, law and technical issues will be an important area of future study.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.

• Journal of the Korean Geographical Society
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• v.36 no.5
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• pp.561-577
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• 2001

Urban spatial structure is closely related to the spatial distribution of urban economic activities. The spatial distribution pattern is no more than an aggregated expression of the location and/or relocation behavior of individual firms and establishments. In this respect, it is important to identify and examine the factors that affect the spatial behavior of individual firms for a more comprehensive understanding of urban space. Agglomeration economies are one of the most prominent urban economic phenomena in the modern metropolitan area. Most firms in an urban space seek external economies through the spatial clustering of their activities. Agglomeration economies feature prominently in the analysis of urban economic structure across urban areas. While the agglomeration economies between cities focus at the macro-scale of analysis, such economies within any given city focus more on the micro geographical scale. There have been a number of researches on agglomeration economies, among which there are relatively few approaches based on an intra-urban context. This proper explores the agglomeration economies at the micro scale and tries to reseal the spatial realization of the agglomeration economies within and between sectors. Three sectors are considered in the analysis; manufacturing, retail and service. The model is based on simultaneous equation systems combined with spatially weighted variables and estimated by the KRP estimators.

• The Research Journal of the Costume Culture
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• v.20 no.6
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• pp.923-936
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• 2012

Apparel companies define their target customers to integrate consumers' needs into their product development processes. The sizing standards play a significant role in ready-to-wear garment business. Consumers' body build and sizes are different according to gender, age, and body type. The consumers' morphological feature of the one geographical area has changed with immigration, aging, and lifestyle change. In this study the way of defining body types in the standard garment sizing systems published in USA., UK, Germany, Japan, and Korea were compared. The results of this study show that most of the systems classified the body types by the index value. The chest-waist drop value was used for men's body type classification. Women's body types were defined by hip proportion. The hip-bust drop value was used for it. German and European garment sizing systems provide a wide range of men's body types. US men's garment sizes are developed for very conservative body type. US women's garment sizing system has had clearly defined women's body types. The Misses body types projected in the US garment sizing system had changed as women's waist girth got bigger compared to the past. In 2011 the US Misses sizes were divided into Curvy Misses size and Straight Misses size by the hip-waist drop value. The Curvy Misses sizes have smaller waist girth and larger hip girth than the Straight Misses sizes.

• Journal of the Korean Geotechnical Society
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• v.21 no.1
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• pp.115-121
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• 2005

At present, continual road constructions to connect from city to city are needed due to the geographical feature of Korea that about $70\%$ of the territory is mountainous area. Thus, the generation of large cut-slope has been inevitably formed. As a means of reinforcement on the cut-slope, in case of destructive disasters such as a snowstorm, pile embedment method is widely adopted. The pile embedment method is to resist possible move of soil by embedding piles from the surface to the immovable ground and then delivering the load from the piles to the immovable ground. In this study this writer analyzes the limitation of empirically used pile construction depth and its spacing through the numerical analysis. As a result, he suggests the most effective pile construction depth and space.

• Journal of the Korean housing association
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• v.21 no.5
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• pp.137-144
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• 2010

The purpose of this study is to clarify locational characteristics and the road systems of existing 22 old settlements in Cheongju downtown of Korea. These old settlements are classified largely into two types by geographical feature; Hill type located in ridge and Valley type in the valley from the ridge. The Hill type is further categorized into San-rock located on ridge and Gogae located on hillside, and the Valley type into closed large and small valley, that is, Daegok and Sogok by the shape and size of the valley. The road systems are classified into outer road, approaching road, inner road, and side road. In San-rock type villages, Inner road is changed side roads by new arterial road, and new ones become inner road. The outer road are almost cut off, but side roads maintain. In the case of the Gogae type, main road becomes inner road, maintain old hierarchical road, and in other cases, villages are formed around side roads derived from main road, and outer road and inner road are cut off. Among the Valley type, Daegok type maintains old hierarchical road, while for Sogok type, outer roads are cut off, and new roads are outer road.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.423-430
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• 2017

Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.27-38
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• 1996

Non-scale digital map have important role in the field of GIS and other application area which using geographical data in recently against conventional map restricted by scale and information. The main objective of this study is to develope the automated map production system for small scale map in conjuction with generalization techniques in a digital environment. We will intend to develope algorithms and programs for each generalization operators based on specific terrain feature with vector data. This study will be performed aspects related to an data model development of generalization process, focussing on priority for processing sequency with maintaining vector topology, and error analysis for generalized digital data.

• Advances in Energy Research
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• v.7 no.1
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• pp.53-66
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• 2020

Before the industrial revolution architecture has been shaped by the natural and cultural inputs. Local constraints become more effective determinants of architecture in the rural contexts because by being disengaged from the webs of transportation and communication, rural settlements have achieved sustainability in difficult conditions. The examples of rural settlement and architecture have provided sustainability through integration with natural inputs within the geographical context because they have reached the goals of ecological design within the local constraints. Although this feature of the rural cultural landscapes has been emphasized frequently, tangible standards could not be developed in order to interpret their ecological design principles from the perspectives of the contemporary building sector and planning. However, the historical experience indicates that the sustenance of ecological performance can be possible as a result of integrated planning at the overall scale of the settlement. Therefore, the existing standards are not qualified for interpreting the rural contexts. This study develops a method for analysing, interpreting and evaluating traditional rural settlements and certifying new implementations in the rural environments in the light of the given literature review, discussion and methodological proposal.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.939-959
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• 2006

This paper studies the introduction of flood quota system for efficient flood prevention. In the present system where local governments decide its flood prevention independently, the optimal flood prevention in a river basin can not be achieved. Thus, the flood quota system is necessary. In deciding the flood quota for each local government in a river basin, its social and economic characteristics as well as geographical feature of the area should be considered. In order to promote the cooperation among local governments in a river basin, the flood quota is necessary to be accompanied with the trading system of the quota.