• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2529-2539
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• 2013

The Korean construction industry has led the miraculous economic boost of Korea by providing solid domestic infrastructures such as highway, roads, and airports. It also played a critical role in global construction market and eaned more than 500 billions dollars in terms of their accumulated international orders. However, domestic construction market has significantly decreased in recent years due to the domestic political environments and global economic crisis. Therefore, the importance of international construction market cannot be more emphasized to the Korean construction market in order for the sustainable growth. There has been, however, little research in the area of identifying required competency elements for the Korean construction industry to stay successful in the global market. The main purpose of this study is to identify elements of core competency to increase global competitiveness for Korean construction industry. Core global construction competency elements were derived from the internal and external environmental analyses along with the extensive literature review, expert interviews and a survey. This study utilized the Importance-Performance Analysis (IPA) and a gap analysis in providing insights on the status competitiveness of the Korean construction industry in terms of required global core competency elements. The analysis shows that project management and financial management are the main areas for improvements required to engineering contractors while construction contractors need to take a more balanced approach among technical, project management, and financial management in order to increase their global competencies.

• Journal of the Korea Institute of Building Construction
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• v.15 no.5
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• pp.507-514
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• 2015

In recent years, the number of construction projects carried out to repair and reinforce newly built structures and facilities has been on the rise compared to the number of new construction projects, accounting for more than 90 percents of all construction projects carried out by specialty construction companies. However, as some of the ordering parties fill out the required tasks incorrectly, the wrong information on construction bids is announced, and the specialty construction companies that hold a license and technology are unable to get the job at the right time. As such, it is critical to prevent unnecessary time and expense related to the correction of incorrect bid announcements by providing accurate information and definitions, because the tasks of each specialty construction work stipulated in the framework act of construction industry are vague. Therefore, the causes and problems were analyzed based on the correction cases of bid information, and a plan that can address the problem will be proposed. The result of this study can be utilized as fundamental data to achieve an institutional improvement in the bidding service for the specialty construction companies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.1
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• pp.25-31
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• 2017

The objective of this study is to find the failure factors of venture companies. We analyze 210 troubled venture companies, all of which have been under guarantee from the Korea Technology Finance Corporation over the last three years. Methods of analysis for failure factors are as follows. First, we categorize the failure factors into the four different types based on growth and profitability indicators in the financial statements of targeted venture companies. Then we analyzed the failure factors of the subject companies based on the troubled guarantee reports made by the Korea Technology Finance Corporation. If a venture company under its guarantee program falls into insolvency, the Korea Technology Finance Corporation make the troubled guarantee report to find out the failure factors and evaluate the recovery potentials. We identify 374 failure factors of venture companies through the analysis. The most prominent among them are deteriorating of business environments (79 factors) and decreasing or withdrawing orders from major suppliers (54 factors) due to bankruptcies or change in business plans. They are followed by slowing collection of accounts receivable (31 factors), dropping or frozen product price (24 factors) due to intensifying competition and escalating pressures from major suppliers, rising raw material costs both at home and abroad (21 factors). In addition, the nuclear power plant disaster in Japan, shut-down of the Kaesong Industrial Complex and subsequent lawsuits, delay in technology development projects, high cost-low efficiency management structure, etc., are also revealed as new factors causing trouble for venture companies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.73-77
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• 1996

정보는 의사결정자들의 수주에 있을 때 기업에 있어 강력한 경쟁무기가 된다. 의사결정자들의 정보에 대한 이러한 필요성을 충족시키기 위해서 데이타는 운영시스템(Operational System)에서 추출되어 데이타웨어하우스에 저장된다. 데이타웨어하우스는 핵심 비지니스영역(key business dimension)에 의해 정리된 historical data를 저장한다. 이러한 의사결정자들을 위한 데이타웨어하우스 정보의 전달은 기존의 클라이언트/서버 시스템 하에서는 많은 지원을 요구한다. 즉 기존 클라이언트/서버 시스템 하에서는 사용자들의 접근을 위해 데이타가 추출되고 조직화되어지고 나면, 반드시 분석 소프트웨어가 각 사용자의 컴퓨터에 설치되어야 하고 외부의 사용자를 위한 새로운 운영자가 고용되어야 한다. 사용자의 다양한 요구 그리고 계속적 사용자의 교체는 사용자 지원에 있어 심각한 기업부담으로 작용한다. 또한 클라이언트/서버 시스템에서는 기업외부의 정보 이용자들에게 정보를 제공하는데 있어 장소적 한계점을 가지고 잇다. 인트라넷과 인터넷은 이러한 클라이언트/서버 시스템 환경의 문제에 대해 해답을 제시한다. 인트라넷은 데이타웨어하우스로의 접근을 간단히 할뿐만 아니라 의사결정자들의 정보의 공유와 상호분석의 새로운 단계를 제공한다. 그리고 인터넷은 기업 외부 어디에서나 기업이 제공하는 정보를 이용하고자 하는 사람들에게 접근의 편의성을 제공한다. 즉 데이타웨어하우스의 목표와 인트라넷, 인터넷의 목표는 데이타로의 손쉬운 접근이라는 점에서 동일하다. 이러한 점에 착안하여 인트라넷과 인터넷하에서 운용되는 데이타웨어하우스 시스템 구축을 위한 방안을 제시하고자 한다.다(학생군:8.16kg 작업자군:12.9kg). 심박수를 이용한 생리학적 연구에서는 평균 심박수가 거의 100 이하를 유지하므로써 피실험자들이 8시간 작업기준으로 보아 무리가 없는 최대허용 하중을 결정하였음을 보였다. 또한 각 운반작업에 대한 최대허용 하중을 예측하는 회귀모형을 제시하였다.아직 정립되어 있지 않은 분산 환경하에서의 관계형 데이타베이스의 데이타관리의 분류체계를 나름대로 정립하였다는데 그 의의가 있다. 또한 이것의 응용은 현재 분산데이타베이스 구축에 있어 나타나는 기술적인 문제점들을 어느정도 보완할 수 있다는 점에서 그 중요성이 있다.ence of a small(IxEpc),hot(Tex> SOK) core which contains two tempegatlue peaks at -15" east and north of MDS. The column density of HCaN is (1-3):n1014cm-2. Column density at distant position from MD5 is larger than that in the (:entral region. We have deduced that this hot-core has a mass of 10sR1 which i:s about an order of magnitude larger those obtained by previous studies.previous studies.업순서들의 상관관계를 고려하여 보다 개선된 해를 구하기 위한 연구가 요구된다. 또한, 준비작업비용을 발생시키는 작업장의 작업순서결정에 대해서도 연구를 행하여, 보완작업비용과 준비비용을 고려한 GMMAL 작업순서문제를 해

• Korean Journal of Psychosomatic Medicine
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• v.15 no.1
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• pp.22-28
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• 2007

The pregnancy and postpartum period appear to be a time of heightened vulnerability for the development of major depression in some women. Postpartum depression affects 10% of women within a few weeks immediately postpartum. Postpartum depression is associated with disturbances in the mother-infant relationship, which in turn have an adverse impact on the course of child cognitive and emotional development. Depression during pregnancy is also common, although it has been relatively neglected. Psychopathological symptoms during pregnancy have physiological consequences for the fetus. Understanding the aetiology of perinatal depression requires integrating of multiple psychosocial and biological risk factors. The treatment of depressed pregnant women requires skilled decision making by psychiatrists. Risk-benefit analysis is appropriate method for intervention fur depression in pregnancy. Effective treatments for depression in pregnancy include psychotherapy, antidepressant medication and electroconvulsive therapy. In treatment of postpartum depression, the biological, psychological, and social interventions are included. Prescribing antidepressants(such as fluoxetine), estrogen in severe and chronic cases, and counselling can be effective for improving maternal mood and aspects of infant outcome. Ongoing research is directed to further elucidating neurohormonal and psychosocial contributions to depression during pregnancy or postpartum. Screening for risk factors and symptoms for depression need to be incorporated into antenatal and pediatric clinics.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.105-114
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• 2013

Recently, foreign direct investment of Korea has increased significantly. Foreign direct investment is motivated by various reasons and renewable energy investments in foreign countries can be performed by many causes. Korean companies can enjoy the export of products, related EPC contracts, acquisition of the knowledge of the project management technique, pre-occupying effect of the market and profit itself. Wind power projects have biggest share in the investment amounts among the renewable energy business. So, in this study, one wind farm project was selected and supposed to be invested in China, USA, Germany and UK at the same time and the effect of electricity price, corporate income tax, inflation rate and interest rate of debt were analyzed. The result showed that investing in Germany is most profitable because of the highest electricity price and electricity price and debt interest rate are the most sensitive factors for IRR. This approach would be helpful to make decisions in investing foreign wind power projects.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.1-9
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• 2023

In order to carry out construction work, it is urgent to introduce a proper wage system so that the cost burden of projects that have been won due to bleeding competition among original government buildings based on low-priced bids can be transferred to subcontractors. Purpose: Construction with illegal multi-level industrial structure needs to improve the wage reduction environment leading to order (100%) → original contractor (80%) → subcontractor (65%) → load contractor (65%) and aims to ensure wages for end workers. Method: Investigate the current status of labor cost appropriate payment plan in the construction industry, and investigate the case of the appropriate wage system (P.W) in the United States. In addition, the effect and direction of the appropriate wage system are presented. Result: Individual minimum wage security was also mentioned in the Constitution, and many researchers suggested that only the introduction of an appropriate wage system could solve the problem of reducing worker labor and ensure quality and safety. Conclusion: The proper wage system in the construction industry will block illegal multi-level and illegal foreign work, improve the labor environment in the construction market, create an influx of young workers, and have a significant impact on the construction industry's competitive structure, safety, and quality.

• Industry Promotion Research
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• v.9 no.2
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• pp.69-75
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• 2024

Korea has entered the ranks of advanced countries in terms of economic size and technological competitiveness. However, its industrial accident fatality rate remains among the lowest in OECD countries, and recent incidents such as various building collapses have resulted in numerous deaths of workers or citizens, reminiscent of accidents in developing countries. According to the 2022 Industrial Accident Status Analysis by the Ministry of Employment and Labor, out of the 874 fatalities in work-related accidents in 2022 across all industries, 402 were in the construction industry, accounting for approximately 46% of all fatalities. In particular, the construction industry's fatality rate stands at 1.61, significantly higher than the overall industry fatality rate of 0.43, indicating its severity. Construction ranks highest in terms of fatality rates, with mining at 12.18 and fishing at 1.80. When categorizing construction projects into private and public, private projects show significantly higher figures in terms of contracts, contract amounts, accident numbers, and fatalities compared to public projects. However, unlike public agencies, many private clients lack adequate safety and health activities and lack established safety and health systems. This study aims to raise awareness among private clients about the need to establish safety and health systems and enhance safety and health activities, and to discuss the direction of future development of advanced safety and health practices among private clients.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.