• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.297-305
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• 2021

A contractor or a main contractor is a company with full capacity to construct all project's works for the owner. A subcontractor is an organization that works with the main contractor to execute and complete work packages for the project. Selecting an effective subcontractor will help the efficiency and success of any projects in the construction industry. Therefore, this study identified subcontractor evaluation factors in Vietnam by collecting questionnaire survey data from engineers and staffs in the construction industry project environment. An exploratory factor analysis (EFA) was then performed to identify the critical factors when evaluating and selecting the subcontractor in construction projects. Moreover, when considering the impact level in terms of the average value, the research results showed that the most critical concern was the subcontractor's reputation. Furthermore, the top five factors affecting the sub-contractor evaluation and selection are (i) reputation, (ii) price, (iii) construction techniques, (iv) ability to implement projects according to commitments, and (v) subcontractor competence (the team of workers, technician staff, engineers with full capacity according to regulations). These research results provide an overall perspective that will help main contractors develop suitable subcontractors' evaluation and selection factors in their projects in the construction industry.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• 한국건설관리학회논문집
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• 제5권6호
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• pp.72-79
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• 2004

기존의 CPM 관리방식은 정해진 시간과 비용 내에서 프로젝트를 완료하기 위한 목적으로 건설분야에 활용되어 공기지연이 발생하지 않도록 관리하는데 초점을 두고 있으나, 조기 완공을 유도하지는 못하여 왔다. 기존의 CPM 공정계획의 경우에 학생증후군(Student Syndrome)과 파킨슨법칙(Parkinson's Law)이 작용할 경우 조기 완공의 효과를 얻기는 어렵다. 본 연구는 건설 프로젝트의 공기 산정에 제약이론(Theory of Constraints)을 적용하였으며, 이는 공정계획에서의 새로운 관리기법을 개발하는데 사용되어온 Critical Chain을 일컫는다. 이러한 Critical Chain의 개념은 기존 공정계획 방법에서의 문제점을 해결하기 위하여 이용되었다 본 논문에서는 기존 공정계획 방법의 문제점을 해결하기 위하여 Critical Chain의 개념을 적용하여 확률적인 공기산정과 공정버퍼(buffer)를 이용한 공정계획 합리화 방안을 제시하였다.

• 패션비즈니스
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• 제21권3호
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• pp.1-13
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• 2017

Ralph Rucci, the first American designer who presented official collections at Paris Couture since Mainbocher, is known for his innovative dressmaking techniques and sculptural forms. Accompanied by literature survey, this study examines the aesthetics of Ralph Rucci's designs by content analysis of his works, Rucci's designs since his debut collection of 1994 until he left the Chado Ralph Rucci label in 2014 and his returning collection under the new label, RR331, in 2016. Ralph Rucci developed his creative designs by the following strategies: First, he reinvents the couture tradition of Balenciaga and $Gr{\grave{e}}s$ into progressive and functional American couture in that he gives consideration to a wearer's movements and comforts. Second, Rucci constructs architectural volume based on human anatomy and architectonic strategies, with the attention to three-dimensional quality of the space built between the body and a garment. Third, he conducts engineered construction summarized by his original 'suspension' techniques, which function as both ornamentation and construction.

• 인간식물환경학회지
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• 제23권3호
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• pp.347-362
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• 2020

Background and objective: It is difficult to conclusively determine the exact cause of tree defects since multiple causes are involved such as climate change, plantation, tree quality and planting time, construction, planting base, drainage, sunshine conditions, maintenance, and microclimate. The data related to landscaping construction defects are scattered or fragmented by companies and years, but not managed systematically by the defect information management system. Most of the earlier studies associated with tree defects in apartment complexes suggested defect rates after examining tree defects in the completed construction site and proposed fragmentary and subjective conclusions about the causes of defects observed in trees with high defect rates. It is proposed to continue to conduct studies on the establishment and analysis of systematic databases to identify the exact causes of tree defects and measures to improve, and the need to accumulate systematic data in the construction process where many defects arises. This study was conducted to reduce the defects of trees planted in apartment complexes. Methods: Main factors related to tree defects were subdivided based on the results of literature review and a defect investigation at the completion site, and tree history management items were selected and subdivided during the construction stage. Results: The criteria for the preparation of subdivided items were obtained, and the tree history management checklist was written for the site under actual construction and a systematic database was established. Items that are categorized based to the causes of defects include the location of nurseries, date, tree quality, site conditions, planting techniques, microclimates, and maintenance. Conclusion: This study suggested tree history management items based on the tree defects that can be identified at the construction stage and applied them to the selected study site, which differentiates this study from earlier studies. It will be necessary to conduct a comprehensive and objective time series analysis on tree defects that occur over time by continuously monitoring and collecting data after construction.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.904-911
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• 2022

Occlusion is one of the most challenging problems for computer vision-based construction monitoring. Due to the intrinsic dynamics of construction scenes, vision-based technologies inevitably suffer from occlusions. Previous researchers have proposed the occlusion handling methods by leveraging the prior information from the sequential images. However, these methods cannot be employed for construction object detection in non-sequential images. As an alternative occlusion handling method, this study proposes a data augmentation-based framework that can enhance the detection performance under occlusions. The proposed approach is specially designed for rebar occlusions, the distinctive type of occlusions frequently happen during construction worker detection. In the proposed method, the artificial rebars are synthetically generated to emulate possible rebar occlusions in construction sites. In this regard, the proposed method enables the model to train a variety of occluded images, thereby improving the detection performance without requiring sequential information. The effectiveness of the proposed method is validated by showing that the proposed method outperforms the baseline model without augmentation. The outcomes demonstrate the great potential of the data augmentation techniques for occlusion handling that can be readily applied to typical object detectors without changing their model architecture.

• 대한안전경영과학회지
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• 제22권3호
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• pp.53-60
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• 2020

This study aims to find the causal relationship between the effects of apartment inhabitants' life management and administrative management on housing satisfaction. The study results are as follows. Firstly, life management showed to have a positive effect on life satisfaction. In other words, the better the management of public order and facilities, the higher the satisfaction of housing satisfaction. Thus, the principal agent of management needs to increase inhabitants' housing satisfaction through education and training on developing life management techniques. Secondly, administrative management showed to have a positive effect on life satisfaction. Thus, the more accurate the completion documents and management transfer process necessary for administrative management, the higher the cost-cutting effects of accounting, construction, and service contracts, the more transparent the resident agreement process in accordance with management policies, the more transparent the election process of building representatives and resident representatives, and the higher the effects of energy saving, the higher the housing satisfaction of inhabitants. This revealed that the principal agent of management needs to increase housing satisfaction through education and training on developing administrative management techniques because the level of administrative management had a positive effect on housing satisfaction. As a result, in order to create reliability between inhabitants and the principal agents of management, the transparency of administrative management such as document disclosure must be ensured, thus improving the housing satisfaction of inhabitants.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 춘계 학술논문 발표대회
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• pp.155-156
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• 2018

Apartment houses are now a popular form of general housing, and the construction techniques and materials quality used to construct apartments are also continuously evolving as if they were representative. However, issues concerning flaws are constantly being reported in the press. This study attempts to analyze the trend of conflicts related to defects and to analyze the types of defects received in the apartment building, to suggest the development of the integrated defect management system, and to develop the construction based on the development of the system.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.839-846
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• 2022

Traditionally, the construction industry has shown low labor productivity and productivity growth. To improve labor productivity, it must first be accurately measured. The existing method uses work-sampling techniques through observation of workers' activities at certain time intervals on site. However, a disadvantage of this method is that the results may differ depending on the observer's judgment and may be inaccurate in the case of a large number of missed scenarios. Therefore, this study proposes a model to automate labor productivity measurement by monitoring workers' actions using a deep learning-based pose estimation method. The results are expected to contribute to productivity improvement on construction sites.