• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.3-12
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• 2019

Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.300-300
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• 2018

최근 우리나라는 봄철 지속적으로 가뭄이 발생하는 추세로 모니터링과 더불어 가뭄 피해를 경감할 수 있도록 가뭄해석 기법이 필요하다. 이를 위해 우선적으로 우리나라 실정에 적합한 가뭄지수를 산정하고, 개선을 통해 가뭄정보들이 수자원확보를 위한 관리와 정책에 활용되어야 한다. 이에 따라 본 연구에서는 국내 기존에 활용되고 있는 수문학적 가뭄지수인 개선된 지표수공급지수(MSWSI : Modified Surface Water Supply Index)를 선정하고 개선하였으며, 개선된 MSWSI를 이용하여 앙상블기법 기반의 확률론적 가뭄해석을 수행하였다. MSWSI의 개선에 있어서는 우선, 유역 내 공식적으로 수집되는 모든 수문기상인자를 조사하여 기존 MSWSI에서 적용한 강수량, 하천유량, 댐 유입량, 지하수량 4가지 인자와 사용 가능한 댐 저수위, 댐 방류량 인자를 추가하여 반영하였다. 또한 각 수문인자들에 대하여 인자별로 적합한 확률분포를 적용하였다. 또한 극심한 가뭄이 발생한 2006년과 2014년을 대상으로 비교 검토를 실시하고, 앙상블기반 확률론적 가뭄전망을 수행하고 검증하였다. 연구결과, 본 연구에서 개선한 MSWSI가 2006년과 2014년 발생한 가뭄현상을 더 잘 나타내는 것으로 분석되었다. 또한 실제 수문기상현상을 더욱 잘 반영하여 실제 가뭄과 유사한 가뭄결과로 분석되어, 개선된 MSWSI가 효용성이 있음을 확인하였다. 또한 앙상블 기반의 확률론적 가뭄전망 결과, 본 연구에서 개선한 MSWSI를 이용하였을 때 더 우수한 것으로 분석되었다. 대부분의 유역에서 실제 가뭄지수가 개선된 MSWSI를 이용한 가뭄전망 범위에 속하는 것으로 나타나, 본 연구에서 개선한 MSWSI를 활용한다면 보다 정확한 가뭄모니터링 수행이 가능하며, 가뭄전망의 정확성을 높일 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.319-319
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• 2012

최근 GIS의 발달로 지리정보를 정확하게 분석한 후 각종 수리 해석에 활발히 적용되고 있다. 수문지형학(Hydrogeomorphology)은 Rodriguez-Iturbe(1971)가 유역의 지형학적 인자를 기초로 하여 순간단위도를 유도하는 방법을 제시하는 것을 시작으로 Rodriguez-Iturbe와 Gonzalez-Sanabria(1982)가 지형학적 순간단위유량도(GIUH, Geomorphologic Instantaneous Unit Hydrograph) 매개변수와 유효우량만으로 함수를 표시하는 지형기후학적 순간단위유량도(GcIUH, Geomorphoclimatic Instantaneous Unit Hydrograph)를 유도하여 오늘날까지 발전해 오고 있다. GIS를 활용한 돌발홍수 및 지형학적 지형 기후학적 순간단위도 유도 및 한계유출량에 관한 연구에서 Sweeney(1992)는 돌발홍수능의 표준적인 산정 알고리즘을 제시하였고, Carpenter 등(1999)은 GIS와 연계하여 돌발홍수능을 산정하는데 중요한 한계유출량 산정방법에 관해 연구하였으며, 국내에서는 김운태 등(2002)은 GIS를 이용한 미소유역 규모의 한계유출량 산정 시스템을 개발한 바 있으며, 황보종구(2007)는 국내 유역에 적합한 GcIUH 산정방안에 관한 연구를 수행한 바 있다. 본 연구에서는 한국건설기술연구원에서 1995년부터 운영해 온 설마천 유역에 대하여 GIS 기법을 활용하여 강우-유출 해석시 GcIUH의 매개변수를 산정하여 유역에 적합한 돌발홍수 기준우량을 산정하는 것을 목적으로 하였다. GIS 기법의 적용결과를 통해 산정된 설마천 유역의 지형학적 특성은 <표 1>과 다음과 같다. 한편, 돌발홍수의 개념에서 한계유출량( )은 소하천의 제방을 월류하기 시작하여 홍수를 일으키기 시작할 때의 유효우량으로 정의되며, 유역전반에 걸쳐 균등하게 내리는 단위유효우량으로 인해 발생하는 직접유출 수문곡선이므로 제방이 가득 찬 상태의 유량 즉, 제방이 월류하기 시작할 때의 유량은 등류상태의 흐름을 해석하는 Manning의 공식으로부터 산정할 수 있으며(Chow et al., 1988), 설마천 유역의 경우 50년 빈도 홍수량에 해당하는 수위와 한계유량을 산정하였다. 향후 2011년 홍수 분석을 통해 한계유량 및 기준우량의 적합성을 평가하고 이를 바탕으로 설마천 유역의 돌발홍수예측을 위한 기준우량의 산정 등을 통해 산지 특성을 고려한 돌발홍수예측시스템 프로토타입을 개발하고자 한다.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.225-236
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• 2020

It is not easy to provide sufficient lead time for flood forecast in urban and small mountain basins using on-ground rain gauges, because the time concentration in those basins is too short. In urban and small mountain basins with a short lag-time between precipitation and following flood events, it is more important to secure forecast lead times by predicting rainfall amounts. The Han River Flood Control Office (HRFCO) in South Korea produces short-term rainfall forecasts using the Mcgill Algorithm for Precipitation-nowcast by Lagrangian Extrapolation (MAPLE) algorithm that converts radar reflectance of rainfall events. The Flash Flood Research Center (FFRC) in the Korea Institute of Civil Engineering and Building Technology (KICT) installed a flash flood forecasting system using the short-term rainfall forecast data produced by the HRFCO and has provided flash flood information in a local lvel with 1-hour lead time since 2019. In this study, we addressed the flash flood forecasting system based on the radar rainfall and the assessed the accuracy of the forecasting system for the recorded flood events occurred in 2019. A total of 31 flood disaster cases were used to evaluate the accuracy and the forecast accuracy was 90.3% based on the probability of detection.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.127-136
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• 2017

U-City laws are divided into three categories: intellectual laws, information superhighway laws, and integrated operation center laws. Previous studies have suggested that efficient infrastructure operation and management is necessary in Ubiquitous-City (U-City). However, infrastructure is often interpreted differently by different laws. The purpose of this study was to plan for the integrated operation of intelligent service facilities by comprehensively analyzing the law system of domestic intelligent service facilities and problems in operation and management based on this critical mind. For this, present conditions and problems of intelligent service facilities were found through interviews with people who are in charge of the law system and other practitioners. The necessity of integrated use, including city information generated from intelligent service facilities and installment locations, has been demonstrated. Government ministries and local governments have established various information systems using ICT and U-City laws that specify integrated management and operation, but do not clearly specify definitions for the specific responsibility and authority for main agents participating in facility operation. A system is needed to smoothly mediate the relevant divisions so that they can use installed equipment simultaneously for efficient operation in generating city information. This objective of this study was to prepare a unitary law system for efficient installment and management of intelligent service facilities by establishing a logically linked relationship among the relevant laws and regulations. This will provide a foundation for a management system that has an integrated linkage of intelligent service facilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.240-248
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• 2020

Over the past 20 years, brain science has developed rapidly thanks to new technologies such as functional magnetic resonance imaging (fMRI), leading to more accurate knowledge of human nature and behavioral changes. This knowledge is also actively applied in the field of management. This research aimed to gain insights into how neuroscience can be incorporated into management through the case of Midas IT Co. This construction software company has a separate organization with the purpose of studying brain science, and it makes and implements human resource management policies based on brain science. The founder Lee Hyung-woo has a humanist management philosophy, and the company's brain science research supports that philosophy. The case study method was adopted as the research method, and procedures such as interviews and direct observation, participation observation, and document information were carried out. The company's human resource management system can be explained by a brain science model called "SCARF", which combines various neuroscience discoveries. As this model suggests, the company has improved the trust and satisfaction of its members by reducing threat of status and by increasing certainty, autonomy, relationship, and fairness in the workplace, resulting in the creation of a platform for creativity, integrity, and high performance.

• Journal of the Korea Institute of Building Construction
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• v.17 no.1
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• pp.83-90
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• 2017

Recently, BIM has been actively adopted in construction projects and industries, and also integrated with Information and Communications Technology(ICT) such as cloud computing technology, sensor technology, 3D scanning and printing technology etc. However, it is very difficult to efficiently utilize BIM services, technologies and collaborate with each other because of differences of usage and requirements of technologies. Every participant in the same construction project has their own needs, requirements and details of the model in each phase. In order to enhance utilization BIM model, BIM services and technologies required in their project have to be clearly defined in the initial stage of the project. In order to support the owner to define the BIM level, BIM service level and application technologies are identified and guidelines how to define the level and technologies for their project purpose are suggested in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.152-152
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• 2017

최근 지속적인 심한 가뭄의 발생은 사회적 이슈가 되고 있으므로 가뭄을 감시할 수 있는 가뭄 모니터링 뿐만 아니라 경감할 수 있는 가뭄전망이 되어야 한다. 이를 위해 우선적으로 우리나라 실정에 맞는 최적화된 가뭄지수의 선정 혹은 개선이 필요하며, 다음으로 개선된 가뭄지수를 기반으로 한 다양한 가뭄정보들이 수자원확보를 위한 관리와 정책에 활용되어야 한다. 이에 따라 본 연구에서는 국내 기존에 활용되고 있는 수문학적 가뭄지수인 MSWSI를 개선하였으며, 개선된 MSWSI를 이용하여 앙상블기법 기반의 확률론적 가뭄전망을 수행하였다. 대상 유역은 낙동강 유역을 선정하였으며, 연구내용을 살펴보면, 첫 번째로 MSWSI의 개선에 있어서는 (1) 유역 내 공식적으로 수집되는 모든 수문기상인자를 조사하여 중권역 유역별로 기존 MSWSI에서 적용한 4개 인자(강수량, 하천유량, 댐 유입량, 지하수량) 뿐만 아니라 사용 가능한 적합한 인자(댐 저수위, 댐 방류량)를 추가 선정하여 반영; (2) 각 수문인자들에 대해 기존에는 정규분포만 적용하였으나 본 연구에서는 각각 인자별 적합한 확률분포를 추정하였다. 두 번째로 극심한 가뭄이 발생한 2006년과 2014년을 대상으로 개선된 MSWSI를 이용한 앙상블기반 확률론적 가뭄전망을 수행하고 검증하였다. 분석 결과를 살펴보면, 개선된 MSWSI를 과거 실측 수문기상자료를 이용하여 검증한 결과 기존 MSWSI보다 개선된 MSWSI가 과거 발생한 가뭄현상을 더 잘 나타내어 개선된 MSWSI가 효용성이 있음을 확인하였다. 또한 앙상블 기반의 확률론적 가뭄 전망 결과, 기존보다 개선된 MSWSI를 이용한 가뭄전망이 우수한 결과를 나타냈다. 또한 대부분의 유역에서 실제 가뭄의 가뭄지수가 개선된 MSWSI를 이용한 가뭄전망 범위에 속하는 것으로 나타났다.