• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.23-35
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• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.76-82
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• 2019

This study has done to search for a solution to remove risk limitedly caused by separating weapon system acquisition from operation and maintenance at the view point of Logistic Commander who's responsible for stable operation and maintenance after acquiring weapon system. At the System development stage, unverified overhaul development plan may cause additional manpower and costs after the development, and furthermore it is likely to have risk to lower reliability of the military. Thus, research and development agency should write overhaul development plan at the System development stage, and it should be verified through evaluation and verification test. Secondly, during research and development, institutional supplementation is needed to calculate human and material resources writing overhaul development plan. Thirdly, it should be able to analyze proper operation & maintenance plan and cost for overhaul plan at the pre-investigation stage. Fourthly, the base which can develop overhaul concept and overhaul factors should be included in the need and need determination document. Lastly, for the weapon system which has small amount of high power figure, project management should be performed to be able to specify at the each acquisition level of weapon system to realize Article 28, clause 3 and 4 of Defense business law.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.94-106
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• 2012

In recent years, the risks and uncertainties associated with mixed used development in urban regeneration projects which have actively been implemented at home and abroad have been on the rise due to the uncertainties of the initial business plan, difficulty of financing, increase in total cost and schedule delay. To cope with rapid social and economic changes and optimize benefits, a risk-based configuration management process that considers life cycle is required, along with accurate planning in the early stage of the business. In addition, it is necessary to prepare measures that can respond to the evaluation and measurement of the configuration factors in relation to the business process. However, the focus of previous studies on configuration management in the field of construction was mainly on humanities and the sociological aspects such as organization, leadership, ideology and similar concepts. There has been limited research on the process and measurement and evaluation methods for configuration factors required in decision-making on the risks and changes that can occur in the actual project implementation phase. Accordingly, in this study, we defined risk-based configuration factors and developed a process and MECA/3DAM/CII methodology to measure and evaluate these factors so as to carry out systematic configuration management of mixed used development in urban regeneration projects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1460-1465
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• 2016

Lots of costs threaten the sustainability of the national health-guarantee system. Despite research by the national center for disease control and prevention on health care dynamics with its auditing systems, there are still restrictions of time limitation, sample limitation, and, target diseases limitation. Against this backdrop, using huge volume of total data, many technologies could be fully adopted to the preliminary forecasting and its target-disease expanding of health. With structured data from the national health insurance and unstructured data from the social network service, we attempted to design a model to predict disease. The model can enhance national health and maximize social benefit by providing a health warning service. Also, the model can reduce the advent increase of national health cost and predict timely disease occurrence based on Big Data analysis. We researched related medical prediction cases and performed an experiment with a pilot project so as to verify the proposed model.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.441-450
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• 2005

As game markets are rapidly growing, the cost and period of game development are both increasing. These imply that the game development projects require more professional management of the project. Game mechanics is an algorithm of the gameplay on a specific game-platform. Game mechanics is concentrated on engineering elements of the game and its quality should be continuously managed from the design phase to the implementation phase. In the design phase, useful methods that can analyze the quality of game mechanics are the simulations. There are several simulation methods of the game mechanics but each method has limited use range because of its characteristics. In this Paper, we survey the game mechanics simulation methods and analyze the characteristics of each method. By the analyzed results, the Petri net model simulation method is good for analyzing total quality of no-error, optimization, and play-balance of the game mechanics but others are not.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1319-1328
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• 2016

Since Ballast Water Management Convention has been effected, BWTS, applied to new-building vessels and existing vessels, have been developed from many countries with various treatment methods. However, BWTS is mainly typed Electrolysis, Ozone and UV type. Approximately 70 products have been type approved by the Flag Administrations. For the new-building vessels, the vessels' design and construction have been considered for arrangements and installations for BWTS. However, existing vessels which already construction had finished have problem with selection of BWTS type for installation and arrangement. The selection of the most economized BWTS system is important though, CAPEX has not been made any significant differences. However, OPEX is more important factor. Consequently, detail analysis of OPEX is the key to the selection of the most economized BWTS system and also it can be the purpose of this study. The feasibility study on the main three type of BWTS (Electrolysis, Ozone and UV type) for 175K Bulk Carrier and 57K Cargo ship has been conducted for this study. Because, these three type of BWTS have been the most frequently installed and used and the two type of object vessels are consist of the 40% of the world merchant ship market. For this study, interest rate, project duration (operation time after installation), maintenance cost and fuel oil price are considered as major factor of feasibility study. In addition, expecting Interest rates to sensitivity analysis conducted for more accurate feasibility study. For 175K Bulk carrier, ozone treatment system is more economical than other types. For 57K cargo ship, UV type is considered more economical than other types. However, it is concluded that electrolysis type is more suitable compare to installation space, total weight and electrical power consumption.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.439-459
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• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.

• Advances in Computational Design
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• v.4 no.2
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• pp.155-177
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• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.117-124
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• 2021

Based on a result of we research and analysis of this study, it was analyzed that the average annual cremators number using E-Haneul Funeral Information System among the five public cremation facilities in Jeollabukdo was 9,713 in total before the opening of public creation facilities in Jeongeup City (2013-2015), while the number was 12,159 after the opening of public cremation facilities in Jeongeup City (2016-2019); the number was increased by 2,446, compared to the opening period (2013-2015), with a large increase rate of 25.2%. In addition, the average annual cremation rate before the opening of public cremation facilities in Jeongeup City (from 2013 to 2015) was 71.6%, but the average annual cremation rate during the period after the opening (from 2016 to 2019) was 81.5%, which was a large increase rate of 9.9% compared to period before the opening of the facilities. Based on research results above, we have presented policy suggestions in order to increase the efficiency of operation and management of public cremation facilities by local governments as follows. First, in order to prepare for the increase in demand for cremation due to the increase in cremators number, a policy promotion for the expansion of "public cremation facilities" should be carried out as soon as possible, focusing on local governments whose supply has reached the limit. Second, in order to support the expansion and construction of public cremation facilities, the government subsidy rate and government subsidy at the level of current 70%, provided by the central government, should be further expanded. Third, overcoming theNIMBY conflict overlocation for public cremation facilities, theutilization rate should be enhanced, through the joint construction and facility operation of the public cremation facilities between local governments, and the ef iciency of the project implementation should be improved through the jointsharing of the facility operation cost.

• 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.