• 한국BIM학회 논문집
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• 제11권3호
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• pp.22-33
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• 2021

In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

• 한국건축시공학회지
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• 제11권3호
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• 한국태양에너지학회 논문집
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• 제34권4호
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• pp.101-109
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• 2014

The Consultation about Energy Use Plan is prescribed by the Energy Use Rationalization Act. This study calculated the Standard Data for Energy Use Plan of Industry Complex by the 9th Korean Standard Industrial Classification Divisions so that the energy demand reflecting the industrial technology change and characteristics of Manufacturing Divisions would predict. To achieve this aim, analysis on thousands of data in Energy Consumption Report Forms reported from industries which annual consumption of energy exceeds 2,000toe from 2009 to 2010 was carried out. The results showed that calculated overall mean fuel basic unit decrease, electricity basic unit increase and energy basic unit increase compared to that of the Notification No. 2002-130 of the Ministry of Commerce, Industry and Energy, therefore it means that heat source of energy facilities transferred from fuel to electricity. Also resultingly suggests that the related notification, code etc. are amended as soon as possible.

• 정보관리학회지
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• 제20권1호
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• pp.165-198
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• 2003

본 연구는 문헌정보학 분야 연구논문에서 저자들의 이론 활용 정도를 분석하기 위하여 한국문헌정보학회지와 정보관리학회지를 대상으로 지난 30년간 연구된 654편의 논문에 대한 내용분석이 이루어 졌다. 주요 연구내용은 연구논문의 연대별 생산성, 세부주제영역별 생산성, 연구에 활용된 이론의 유형과 근원, 개별 이론별 활용도, 세부주제 영역별 활용도, 학회지별 활용도 등에 대한 개념적 연구와 실증적 연구가 수행되었다. 이를 위하여 이론의 개념적 기준 설정과 문헌정보연구의 세부주제영역에 대한 새로운 분류 체계, 특히 이론의 활용성을 평가하기 위한 기준으로 ‘이론 활용 5단계’ 모델을 제시하였다.

• 헤리티지:역사와 과학
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• 제56권2호
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• pp.282-294
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• 2023

국제적으로 근현대 유산의 조경적 가치에도 주목하고 이를 전승하기 위한 노력이 전개되고 있지만, 아직 우리나라는 근현대 조경유산의 등록문화재 등록이 미미한 실정이며 이와 관련한 제도개선 방안에 대해서도 논의된 바가 거의 없다. 이에 따라 본 연구는 근현대 조경유산도 법제도권 내에서 보호받고 그 가치가 조명될 수 있도록 등록문화재 제도의 등록기준과 분류체계 개선 방안을 모색하였다. 현재 등록문화재의 등록기준은 유산의 유형별로 규정되어 있지 않고 포괄적인 단일 기준으로 규정되어 있다. 유산의 조경적 가치가 검토될 수 있도록 등록기준이 별도로 마련되어야 한다. 영국과 일본의 유사 제도를 참조하여 등록기준은 첫째, 조경문화의 발전을 이해하는데 중요한 가치를 지니고 있는 것, 둘째 시대를 반영하거나 특징짓는 조경이 잘 남아있는 것, 마지막으로 주요 작가의 작품, 중요한 인물 또는 역사적 사건과 관련된 것으로 규정되어야 한다. 분류체계는 기연구된 대분류-중분류-소분류의 건조물 문화재 분류체계와 정합성을 이루면서 근현대 조경유산의 세부 유형이 구체적으로 명시되어야 한다. 대분류는 건조물 분류체계를 따르되 중분류에 단일 조경유산이라고 할 수 있는 공원 및 녹지, 광장, 정원이 추가되어야 한다. 건조물 유산과 결합된 정원 등의 조경유산은 건조물의 중분류를 토대로하여 소분류에 세부 유형이 명시되어야 한다. 이러한 분류체계는 향후 전수 조사되어야 할 등록 가능성이 있는 근현대조경유산의 분류 근거로도 활용될 수 있을 것이다.

• 한국조경학회지
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• 제30권6호
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• pp.128-140
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• 2003

The purpose of this research was to present characteristics for the classification of biotopes and classification method of biotopes as basic data for ecological landscape planning in Metropolitan Daegu. The results of this study were as follows. 1) The study identified fifteen characteristics for classification of biotopes. Ecological landscape characteristics were divided into structural and functional factors. There are six structural factors such an inclination, and nine functional factors such as temperature. 2) The study area was separated into sixty eight biotope types. For example, an industrial district was divided into two biotope types: a biotope type of an industrial district with abundant green space, and a biotope type of an industrial district with scarce green space. 3) In the result of cluster analysis using the average linkage method between groups, biotope groups were divided into fifteen clusters and biotope groups were divided into seven clusters. Each cluster was named according to the features of a descriptive statistics analysis. For example, cluster 8 was identified as a biotope type with an impermeable pavement rate of more than 90 percent and an afforestation rate under 10 percent. 4) Fifteen biotope groups were converted to land use patterns for remote application and utilization of urban biotope in city planning. Biotope groups of a building area beyond an intermediate floor with an afforestation rate under 20-30 percent was converted to a land use pattern such as a tall apartment complex or commercial district. When examining the characteristics that were established in this research, there was a limit to achieve the objective of grade-classification because of a lack of related basic data. The research of landscape ecological characteristics for the classification of biotopes could not be completed due to a lack of time and resources, thus the study of ecological landscape characteristics will be accomplished over time.

• 한국구조물진단유지관리공학회 논문집
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• 제4권4호
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• pp.129-140
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• 2000

Retaining wall is a constructed structure in order to construct road, rail, building for effective use and obtainments of the limited ground. Recently, many kinds of research have been actively developed for a standardization and information to the maintenance and management of bridge, tunnel, road. With the works of database construction of that, many kinds of data with respect to statistics is cumulated. Database work of retaining wall is wholly lacking and lagged behind in the works of database construction. This paper suggests classification system on inspection data. On the basis of that, code work with classification system was practised and DB program of inspection data of retaining wall was developed. And input work for a data of maintenance and management was practised. The purpose of this paper is to suggest a kind of statistics data and investigate a characteristics of inspection using statistic data on retaining wall.

• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.580-584
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• 2006

Material information for environment may be useful to accomplish mobile robot localization. A procedure to classify a set of indoor materials (glass, steel, wood, aluminum and concrete) with the reflected signal of ultrasonic sensor is proposed in this paper. The main idea is to use material-specific reflection characteristics for the recognition of material type. To achieve the classification task, we modeled reflected signal as a maximum amplitude with respect to distance. In this way, we can generate echo signal models for the given materials and these models are used to compare with the current sensor reading. The experimental results show that the proposed method may give material information during map building task of mobile robot.

• 한국전산구조공학회논문집
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• 제33권2호
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• pp.73-79
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• 2020

BIM 도구는 설계프로세스에서 기술의 사용이 증가하면서 그에 따른 정보표준체계가 필요하게 되었다. 건설이 완료된 결과(Result) 분류는 25종 단위시설에 327종의 유형, 결과를 구성하는 객체는 174종의 Part와 207종의 Component로 분류하고 있다. 선행연구에서는 도로와 하천 분야 대상으로 속성분류체계를 대분류 4종, 중분류 13종, 소분류 58종, 속성정보 333종으로 분류하였고, 객체분류에 따른 대량의 속성정보를 입력하는 것의 소요 시간을 줄이는 것이 관건이었다. 따라서, Revit 플러그인과 같은 외부 응용 프로그램 개발을 통해 구체적이고 반복적인 작업에 자동화가 필요하다. BIM 속성분류체계를 따르면서 사용자의 생산성과 편의성을 강화할 수 있는 BIM 속성입력 프로그램을 구현하였다.

• 대한원격탐사학회지
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• 제36권1호
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.