• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.97-100
• /
• 2015

Analysis of construction tender documents in overseas projects is a very important issue from a risk management point of view. Unfortunately, majority of construction firms are biased by winning contracts without in-depth analysis of tender documents. As a result, many contractors have incurred loss in overseas projects. Although a lot of risk analysis techniques have been introduced, most of them focus project's external unexpected risks such as country conditions and owner's financial standing. However, because those external risks are difficult to control and take preemptive action, we need to concentrate on project inherent risks. Based on this premise, this paper proposes a project-oriented risk mining approach which could detect and extract project risk factors automatically before they are materialized and assess them. This study presents a methodology regarding how to extract potential risks which exist in owner's project requirements and project tender documents using state of the art data analysis method such as text mining, data mining, and information visualization. The project-oriented risk mining approach is expected to effectively reflect project characteristics to the project risk management and could provide construction firms with valuable business intelligence.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.39-40
• /
• 2015

As international construction market increases, the importance of risk management in international construction project is emphasized. Unfortunately, current risk management practice does not sufficiently deal with project risks. Although a lot of risk analysis techniques have been introduced, most of them focus on project's external unexpected risks such as country conditions and owner's financial standing. However, because those external risks are difficult to manage and take preemptive action, we need to concentrate on project inherent risks. Based on this premise, this paper proposes a project-oriented risk mining approach which could detect and extract project risk factors automatically before they are materialized. This study presents a methodology regarding how to extract potential risks which exist in owner's project requirements and project tender documents using state of the art data analysis method such as text mining. The project-oriented risk mining approach is expected to effectively reflect project characteristics to the project risk management and could provide construction firms with valuable business intelligence.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.601-605
• /
• 2009

The objective of this research is to develop a knowledge discovery framework which can help project teams discover useful patterns to improve energy efficient building design. This paper utilizes the technology of data mining to automatically extract concepts, interrelationships and patterns of interest from a large dataset. By applying data mining technology to the analysis of energy efficient building designs one can identify valid, useful, and previously unknown patterns of energy simulation modeling.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.37-38
• /
• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Asian Journal of Innovation and Policy
• /
• v.5 no.2
• /
• pp.197-207
• /
• 2016

This paper seeks to measure the monetary value of technical development in the deep seabed manganese nodule mining by applying the compound option model (COM). The COM is appropriate for the project in terms of its decision-making structure and embedded uncertainty. The estimation results show that the deep seabed mining project has more economic potential than shown by the previously obtained results from the discounted cash flow (DCF) analysis. In addition, it is reasonable to invest in the project taking the various uncertainty factors into consideration, because the ratio of the value to the cost of the project is far higher than one. This information can be utilized in national ocean policy decision-making.

• Proceedings of the IEEK Conference
• /
• 2001.10a
• /
• pp.659-663
• /
• 2001

In Japan, the municipal solid waste, which amounts to 50 million tons, is generated every year and most of it is incinerated. The bottom and fly ashes are disposed to the registered disposal areas under the provisions of The Waste Disposal and Public Cleaning Law. Especially, as the fly ash from the municipal waste incineration (the primary fly ash) contains heavy metals (lead, zinc, etc) and dioxins, it cannot be disposed directly without decontamination, such as moiling, cementation, chelating and dissolving processes provided in the law. However, these procedures for decontamination, except melting, are not enough for dioxins. Even in case of melting, the fly ash from the process (the secondary fly ash) contains high concentration of heavy metals (e.g., Zn; 1-20%, Pb; 1-10%). For these reasons, Metal Mining Agency of Japan (MMAJ), a governmental organization, started a four-year project to develop the treatment technologies of these fly ashes in 1999. The purpose of the project is to establish the integrated technologies to recover the valuable metals from, and to decontaminate, the primary and secondary fly-ashes in the practical scale by utilizing the existing metallurgical processes and facilities, along with the energy saving and the reduction of the environmental impact.

• The Journal of the Petrological Society of Korea
• /
• v.18 no.4
• /
• pp.371-379
• /
• 2009

A famous foreign mining company in Argentina, Yamana Gold, its profile including company history, current and future mining projects, and production are introduced in this paper for the Korean mining companies those are sincerely looking for reliable collaborative partners to deliver the practical company informations.

• The Journal of the Petrological Society of Korea
• /
• v.18 no.3
• /
• pp.269-278
• /
• 2009

A famous foreign mining company in Argentina, Barrick Gold, its profile including company history, current and future mining projects, and production are introduced in this paper for the Korean mining companies those are sincerely looking for reliable collaborative partners to deliver the practical company informations.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.11-17
• /
• 2022

Design-bid-build (DBB) is the most common project delivery method among highway projects. State Highway Agencies (SHAs) usually apply a low-bid approach to select contractors for their DBB projects. In this approach, the Federal Highway Agency suggests SHAs heighten contractors' competition to lower bid prices. However, these attempts may become ineffective due to collusive bidding arrangements among certain contractors. One common strategy is the rotation of winning bidders of a group of contractors who bid on many of the same projects. These arrangements may also be specific to a particular region or vary in time. Despite the practices' adverse effects on bidding outcomes, an effective model to detect red-flag bidding patterns is lacking. This study fills the gap by proposing a novel framework that utilizes pattern mining techniques and statistical tests for unusual pattern detection. A case study with historical data from an SHA is conducted to illustrate the proposed framework.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.spc
• /
• pp.1-8
• /
• 2023

To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: 'equipment,' 'smart,' and 'eco-friendly.' Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.