• Title/Summary/Keyword: 건축공사

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Analysis characteristics of surface runoff rate of Nae-seong catchment at Nakdong River (낙동강 내성천유역의 표면유출비 특성분석)

  • Chang, Hyung Joon;Lee, Hyo Sang;Min, Byung Yun;Jo, Guk-Hui;Lee, Mu-Gyeong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.440-440
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    • 2015
  • 최근 급증하는 기후변화 영향으로 인한 자연재해의 위험이 증대되고 있다. 이러한 자연재해 중 가뭄은 그 빈도수나 피해의 규모가 홍수보다 작아 관련된 연구가 제한적이므로 유역의 특성을 반영한 장 단기 유출특성의 면밀한 검토가 요구되며, 향후 이를 반영한 홍수유출모형의 개발이 필요하다. 본 연구에서는 유역 수자원산정의 기초연구로서 낙동강 내성천 유역을 대상으로 유역의 유출수문자료를 구축하고 장기기저흐름지수(BFI: Base Flow Index), 표면유출지수(1-Base Flow Index)를 산정하여 유역의 유출특성을 분석하였다. 내성천유역은 낙동강 상류유역으로 본류길이는 110.69km, 유역면적은 $1,815.28km^2$이며, 분수계의 능선부가 대체로 1,000m이상의 고도를 나타내고, 유역분지의 평균 해발고도는 318.2m이다. 또한 영주댐이 검설 중에 있으며, 향후 댐 건설이 수자원에 끼치는 영향등을 분석 할 수 있는 유역이다. 본 연구에서는 내성천 유역을 분석하기 위해서 8개의 수위관측지점을 선정한 후, 2001년부터 2012년 기간의 일 유량자료를 바탕으로 유출비를 산정하였다. 내성천 8개 소유역의 유역 장기유출비를 분석한 결과 기저흐름지수는 0.24~0.47, 표면유출지수는 0.53~0.76의 분포를 나타내었다. 표면유출비는 미호(0.76), 월호(0.53), 점촌(0.71)유역을 제외한 5개 유역에서 0.62~0.65의 분포를 나타내었으므로 낙동강 상류인 내성천유역의 표면유출비로 0.63을 제시할 수 있을 것으로 판단된다. 향후 다수의 낙동강유역을 추가분석하여, 낙동강유역의 고유 유출특성을 제시 할 수 있을 것으로 기대된다.

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Case Study for Preventing Construction Site Fall Accidents (건설현장 추락사고 예방을 위한 사례 연구)

  • Choi, Du Ho
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.6
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    • pp.81-88
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    • 2019
  • Recently, the government has shown a decrease in disaster accidents throughout the industry and construction industry due to various efforts to reduce disasters. However, the fall accidents in the construction industry are not decreasing but increasing. In particular, the fall accident caused by scaffolding is low each year, but the disaster intensity is very high in that it directly leads to the death of workers. Scaffolding working environment in domestic construction industry is very poor. Moreover, scaffold workers in small construction sites are not subject to safety oversight and control. Therefore, this study is the installation and non-installation of the vertical lifeline, which is the most fundamental problem to be prevented during the study, to prevent the fall of the moon scaffold. In addition, it is hoped that it will be a solution for preventing accidents in construction site construction through the identification of various causes of disasters such as rope loosening, rope breaking, and fixed point failure.

Experiment of Air-Shower to Reduce Particulate Matter in Apartment Housing (공동주택에서 미세먼지 저감을 위한 에어샤워 성능실험)

  • PARK, JIN CHUL;Chung, Hong Goo
    • Land and Housing Review
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    • v.12 no.2
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    • pp.91-97
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    • 2021
  • High levels of fine dust is an increasing health concern in major cities such as Seoul. To improve the indoor air quality of apartments, this study examined the ability of an air shower system installed in an apartment unit to remove fine dust (as defined by ISO 12103-A2) from various clothing items of building occupants entering their apartment. Results of the experiment indicate that an air shower system is effective in removing final dust from clothing after one pass through the system. The fine dust removal efficiency for various clothing items was 74% for a dress suit, 70.6% for hiking clothes, 63.3% for knit-wear, 50.5% for a cotton t-shirt, and 38.8% for a coat. Fine dust removal efficiency increased with a second and third pass through the air shower system by an average of 9.1 and 13.9 percentage points respectively compared to a single pass through the system.

Electrical fire prediction model study using machine learning (기계학습을 통한 전기화재 예측모델 연구)

  • Ko, Kyeong-Seok;Hwang, Dong-Hyun;Park, Sang-June;Moon, Ga-Gyeong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.6
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    • pp.703-710
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    • 2018
  • Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

Assessment of National and Regional Plans Using Integrated Management Index of Korea National Planning and Environmental Planning for Present Status Evaluation (국토계획과 환경계획 통합관리 지표의 적용을 통한 통합관리 현황 평가)

  • Heo, Han-Kyul;Lee, Dong-Kun;Sung, Hyun-Chan;Heo, Min-Ju;Park, Jin-Han
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.22 no.4
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    • pp.81-91
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    • 2019
  • Integrated management of Korea national and environmental planing for sustainable development is suggested, and basic research is needed. In this study, national and regional plans were assessed using 'integrated management index of Korea national planning and environmental planning' to grasp the current status of integrated management on Korea national planning and environmental planning. As a result of the assessment, it was found that both national and regional plans need to improve considering the natural ecology part and water resource and quality part. In addition, it was derived that the detailed contents of the indicator can not be reflected according to the characteristics in the higher-level plan. Therefore, it has been found necessary to include proclamatory contents so as to be able to establish a detailed plan that reflects environmental goals in the lower-level plan.

Object Classification and Change Detection in Point Clouds Using Deep Learning (포인트 클라우드에서 딥러닝을 이용한 객체 분류 및 변화 탐지)

  • Seo, Hong-Deok;Kim, Eui-Myoung
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.2
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    • pp.37-51
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    • 2020
  • With the development of machine learning and deep learning technologies, there has been increasing interest and attempt to apply these technologies to the detection of urban changes. However, the traditional methods of detecting changes and constructing spatial information are still often performed manually by humans, which is costly and time-consuming. Besides, a large number of people are needed to efficiently detect changes in buildings in urban areas. Therefore, in this study, a methodology that can detect changes by classifying road, building, and vegetation objects that are highly utilized in the geospatial information field was proposed by applying deep learning technology to point clouds. As a result of the experiment, roads, buildings, and vegetation were classified with an accuracy of 92% or more, and attributes information of the objects could be automatically constructed through this. In addition, if time-series data is constructed, it is thought that changes can be detected and attributes of existing digital maps can be inspected through the proposed methodology.

A Study on Meaning, Typology, and Characteristics of a Home in the Metaverse (메타버스에서 나타나는 주거의 의미, 유형 및 특성 연구)

  • Rhee, Jee Heon;Cha, Seung Hyun
    • Land and Housing Review
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    • v.13 no.4
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    • pp.91-103
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    • 2022
  • Home has significant meaning in the real world. In contrast, there's a lack of interest in homes in the Metaverse compared to other architectural spaces. This study aims to establish the concept of a home in the Metaverse based on meaning, typology, and characteristics of real-world homes. For this purpose, previous research and existing models of real- world homes were analyzed and case studies and a survey were conducted of homes in the Metaverse. As a result of the research, a model of home in the Metaverse is proposed based on physical, social, and personal models. Modifying one's dwelling, a refuge from the outside world, and self-expression/personalized space was also identified as the most significant characteristic of a home in the Metaverse. The results of this study will be helpful in future Metaverse virtual world research and development of Metaverse service platforms.

Establishment of BIM-LCC Analysis System for Selecting Optimal Design Alternative using Open KBIMS Libraries (개방형 KBIMS 라이브러리를 활용한 최적설계대안 선정을 위한 BIM-LCC분석 시스템 구축)

  • Lee, Chun-Kyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.153-161
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    • 2020
  • Building information modeling (BIM) is a smart construction technique that is recognized as essential for current construction facility projects. The Public Procurement Service (a construction project-ordering agency) announced a plan to introduce BIM and has required changing the operation of projects by using BIM design information. LCC analysis is essential for items, quantity, and cost information of the construction, and it is expected that efficient work will be achieved by using BIM design information. In this study, a BIM-LCC analysis system was established for selecting optimal design alternatives by actively using open KBIMS libraries. The BIM-LCC analysis system consists of a single alternative and an optimal alternative LCC analysis, but it has a limitation in that only the architecture and machine libraries have been applied. However, by applying BIM, practical use and work efficiency can be expected. In order to use the method as an LCC analysis support tool with BIM design information in the future, it will be necessary to collect user opinions and improve the UI.

Analysis of Ventilation Impact in Multi-Family Residential Building Utilizing TOPSIS Method (다기준 의사결정방법을 이용한 공동주택 내 환기장치 종류별 효과분석)

  • Park, Kyung-Yong;Kim, Gil-Tae;Kim, Tae-Min;Ji, Won-Gil;Kwag, Byung-Chang
    • Land and Housing Review
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    • v.13 no.3
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    • pp.107-113
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    • 2022
  • With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.

Helmet and Mask Classification for Personnel Safety Using a Deep Learning (딥러닝 기반 직원 안전용 헬멧과 마스크 분류)

  • Shokhrukh, Bibalaev;Kim, Kang-Chul
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.3
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    • pp.473-482
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    • 2022
  • Wearing a mask is also necessary to limit the risk of infection in today's era of COVID-19 and wearing a helmet is inevitable for the safety of personnel who works in a dangerous working environment such as construction sites. This paper proposes an effective deep learning model, HelmetMask-Net, to classify both Helmet and Mask. The proposed HelmetMask-Net is based on CNN which consists of data processing, convolution layers, max pooling layers and fully connected layers with four output classifications, and 4 classes for Helmet, Mask, Helmet & Mask, and no Helmet & no Mask are classified. The proposed HelmatMask-Net has been chosen with 2 convolutional layers and AdaGrad optimizer by various simulations for accuracy, optimizer and the number of hyperparameters. Simulation results show the accuracy of 99% and the best performance compared to other models. The results of this paper would enhance the safety of personnel in this era of COVID-19.