• International conference on construction engineering and project management
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• 2009.05a
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• pp.1260-1265
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• 2009

Topographical features in South Korea is characterized that 70% of territory is composed of the mountains that can experience intense rainfall during storms in the summer and autumn. Efficient planning and management of landscape becomes utmost important since the cutting slopes in the mountain areas have been increased due to the limited construction areas for the roadway and residential development. This paper proposed an efficient way of slope management for the landslide risk by developing Web-GIS landslide risk management system. By deploying the Logistic Regression Analysis, the system could increase the prediction accuracy that the landslide disaster might be occurred. High resolution survey technology using GPS and Total-Station could extract the exact position and visual shape of the slopes that accurately describe the slope information. Through the proposed system, the prediction of damage areas from the landslide could also make it easy to efficiently identify the level of landslide risks via web-based user interface. It is expected that the proposed landslide risk management system can support the decision making framework during the identification, prediction, and management of the landslide risks.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.841-846
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• 2009

Recently, the construction industry is getting more complex and sophisticated having the characteristics of a mega project. Mega project pursues a value that can't be gained with an approach of seeing a project as just a simple sum of different parts but a mutual combination. However, the current manuals can't fulfill the needs for supporting, therefore, need a tool to support the decision making and an IETM is expected to take this role. Despite the a lot of expected advantages of IETM, it is still difficult to apply because of the frequent changes of information of detailed process and its complexity. In this research, as part of developing an IETM, we aim to propose a system frame which is based on the analysis of processes of a project. It is basic part of IETM to give information to users and IETM consists of normal mode that offers general information about the urban regeneration project and user-specified mode that gives classified and reorganized information to user. For supporting these functions, IETM should be stored in a form that can classify the information about urban regeneration project and be tagged with meaningful tags. Moreover IETM developers have to consider the interoperability of IETM because it ultimately should be coordinated with overall Project Management System like an iPMIS. We used XML for solution of interoperability because it stores information as just text-file that doesn't need a special form.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1150-1153
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• 2005

The orders of Design-Build Delivery System (DBDS) in a large and public construction project have been increasing. Single Source Responsibility (SSR) for design and construction, which contributes to quality improvement of design and construction, has been performed. The DBDS performs SSR for design and construction, but, it has not maximized effect because of the dissatisfied alternative analysis procedures which are based on constructability evaluation and the information system in the design step. In this research, Constructability Evaluation Factors (CEFs) that must be evaluated, investigated, and reflected in the basic design step for design-build projects. The CEF proposed and the business process of each conductor has been systematized. To propose constructability evaluation factors, first classify drawing information by the constructability evaluation sphere. CEFs must be proposed to evaluate factors according to interference among work items. Second, applicable CEFs must be classified by preference ranking and weight. Third, the values of constructability factors in accordance with building elements and work items, need to be calculated. Finally, the CEFs proposal will support rational decision making, design cost reduction, and quality improvement through the values for constructability of building elements and work items.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.105-117
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• 2022

This study tested SVM(support vector machine), RF(random forest), and ANN(artificial neural network) machine-learning models that can predict net irrigation water requirements in paddy fields. For the Jeonju and Jeongeup meteorological stations, the net irrigation water requirement was calculated using K-HAS from 1981 to 2021 and set as the label. For each algorithm, twelve models were constructed based on cumulative precipitation, precipitation, crop evapotranspiration, and month. Compared to the CE model, the R² of the CEP model was higher, and MAE, RMSE, and MSE were lower. Comprehensively considering learning performance and learning time, it is judged that the RF algorithm has the best usability and predictive power of five-days is better than three-days. The results of this study are expected to provide the scientific information necessary for the decision-making of on-site water managers is expected to be possible through the connection with weather forecast data. In the future, if the actual amount of irrigation and supply are measured, it is necessary to develop a learning model that reflects this.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.389-397
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• 2022

As the Jordanian government is in the process of implementing accrual-based IPSAS, this study aims to provide academics' perspectives on the effective implementation of accrual-based IPSAS in Jordan to authorities and regulators. The findings of a survey of 124 accounting professors at Jordanian institutions reveal that adopting accrual-based IPSAS will aid in presenting the realistic financial status of governmental bodies, with various advantages to adopting accrual-based IPSAS (e.g., enhance assets and liabilities management, decision-making process, transparency, expenditures management). On the other side, we discovered that change is met with reluctance because the majority of public-sector accountants are untrained and unqualified to apply the accrual-based IPSAS. Another main challenge is the cost of implementing the accrual-based IPSAS in the Jordanian public sector is very high. To address these issues, employees should be motivated by providing suitable training programs, reward systems, and top management support and commitment to a successful transition. Finally, we suggested that Jordanian governments commit to using IPSAS in the public sector to increase residents' socioeconomic advantages. Public sectors should implement IPSASs for improved management, transparency in financial reporting, accountability, and regulatory and supervisory agencies.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.50-59
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• 2020

The 21st century is witnessing a rapid growth of tall buildings in urban centers globally to create more urban space for an anticipated urban population. Tall buildings, however suffer from incessant delays and sometimes total abandonment. Consequently, this study investigated and ranked the causes of delay in tall building projects, while focusing on the Gulf Cooperation Council (GCC) countries. Initially, 36 common delay causes investigated globally were categorized into 9 groups, and then further ranked utilizing the Relative Importance Index (RII) through a questionnaire survey. Tall building professionals in the GCC countries (Saudi Arabia, United Arab Emirates, Bahrain, Kuwait, Oman and Qatar) were contacted. The respondents' categories include Consultants, Contractors, and Clients' Representatives/Facility Managers. The results reveal that the top three causes include "client's cash flow problems/delays in contractor's payment", "contractor's financial difficulties", and "poor site organization and coordination between various parties". The findings from this study could help construction professionals develop guidelines and controls for delay mitigation, as well as support them in risk-based decision making in the planning of tall building projects.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.459-462
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• 2015

Korean construction industry made a huge growth over several decades. However, domestic construction market has shrunk in recent years due to the domestic political environments and global economic crisis. Today, the international construction markets become more important to be investigated, and demands for international construction study have risen. The purpose of this study is to search for measures to compare the potential of Southeast Asian countries' construction markets and select strategic target countries where the Korean construction companies pursue to explore for future investments. The research team investigated a range of selection factors which can represent the construction market condition of each country. These factors included the size of the construction industry, economic growth potential, current relationship with Korea, the level of infrastructure development, political situation, etc. After collecting data, each selection factor was scored by experts' analyses and the total score was given to each country. As a result, the rating identified attractive countries for future investments: Myanmar, Vietnam, and Sri Lanka. For the target countries, analytical methods were used for in-depth market analysis that can provide comprehensive insight and strategic clue for development of short-/mid-/long-term roadmap and action plans. The research findings would be used to support rational decision making of construction investment advancing to the Southeast Asian economic growth.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.570-575
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• 2013

Enhancing utilization of buildings is gaining in importance in response to a challenging economy; thus, there is a need for a method that analyzes space, user, and user activity in an integrated way to provide project stakeholders with utilization information to support their decision-making about buildings. Conventional methods, such as architectural programming and post-occupancy evaluation, lack a formal relationship between user activity and other information, and therefore, are coarse-grained. This relationship has been formalized by two relatively new methods that provide fine-grained utilization information: workplace planning and space-use analysis. We characterize these two methods with focuses on their usage in different phases (i.e., planning, design, occupancy), required information that needs to be gathered, and the achievement and limitations in terms of three criteria, i.e., consistency, efficiency, and transparency. This characterization would not only help project stakeholders select and use a method that best meets their purposes for enhancing utilization of their buildings, but also provide researchers with promising research topics regarding enhancing utilization of buildings.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.352-358
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• 2013

As amount of information in construction industry is growing, the role of information system in project management is becoming increasingly important. With the emerging IT application to the advancing construction industry, construction project management system with advanced technology has been progressed vigorously to improve construction productivity and management efficiency. Recently, a web-based Project Management Information System (PMIS) is developed to support decision-making process by efficiently managing project related information generated from various discipline. Many firms are in the process of developing the PMIS system or already have been applied the system to various projects. However, PMIS is still in its early stage of development to be applied at industrial plant construction projects that process management is significantly emphasized for the successful execution of the project. With the complexity of the industrial plant projects, the industry practitioners need to be able to visualize the construction schedule information to manage the project efficiently. This study suggests methodologies for improving PMIS specialized for industrial plant piping construction projects to estimate the baseline schedule and performance measurement more accurately by developing a framework for the piping construction projects. By using this developed system, the researchers expect that piping construction projects will be more efficiently managed on a real-time basis through measuring progress of piping at each and every state of progress milestone and provide management with opportunities to forecast the level of efforts required to execute the remaining work scope in a timely manner