• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• Korean Journal of Construction Engineering and Management
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• v.11 no.3
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• pp.3-12
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• 2010

Recently, workers on construction sites can hardly understand their tasks and the process of the tasks because the construction projects are becoming large and complex. Due to the complexity, workers need a tool that can help them understand their works and some paper-based manuals exist to support them. However, the existing paperbased manuals are not actively used by workers due to the low credibility of information on the manual. In particular, paper-based manual can not be updated frequently because those manuals have to be manually updated by experts. Thus, the credibility of information is decreased and the decrease let the users distrust information of the paper-based manual. Therefore, this research analyzed the feature of wiki-based system and suggested an wiki-based IETM(Interactive Electronic Technical Manual) system model that can be modified by users, and then conducted a survey through a prototype based on urban regeneration project. The result of the survey indicated that wikibased IETM can improve the stakeholder communication by reinforcing the process of creating knowledge as well as knowledge itself.

• The Journal of Information Technology
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• v.8 no.3
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• pp.83-103
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• 2005

The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing has unique characteristics that may impact the importance of factors that apply to it. in this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 51 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a regression analysis of the data identified relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations, resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementation's success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.499-505
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• 2009

Along with the changing pattern that the construction project is getting complicated, large-scaled and up-to-dated, necessity of efficient management of manpower and resources of the construction site is being increased. In particular, considering that the construction site requires a lot of labor force and in terms of the construction cost, labor cost shares 30-40%, labor management has become a very important factor. In this study, in order to support a stable and successful construction project implementation and supplement the existing system being utilized at the current site, construction site access management automation system based on hand vascular pattern, a biometrics system, is intended to be developed. Relevant theory for the system development and the problem of existing RFID system were evaluated and based on this findings, a system design and DB composition chart were envisaged. In addition, by applying this developed system to a number of sites, its result was analyzed

• International conference on construction engineering and project management
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• 2013.01a
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• pp.359-366
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• 2013

Although many research efforts have been conducted to address the effect of crew members' work skills (e.g., technical and planning skills) on work performance (e.g., work duration and quality) in construction projects, the relationship between skill and performance has generated a great deal of controversy in the field of management (Inkpen and Crossan 1995). This controversy can lead to under- or over-estimations of the overall project schedule, and can make it difficult for project managers to implement appropriate managerial policies for enhancing project performance. To address this issue, the following aspects need to be considered: (a) work performances are determined not only by individual-level work skill but also by the group-level work skill affected by work team members, each member's role, and any working behavior pattern; (b) work planning has significant effects on to what extent work skill enhances performance; and (c) different types of activities in construction require different types of work, skill, and team composition. This research, therefore, develops a system dynamics (SD) model to analyze the effects of both individual-and group-level (i.e., multi-level) skill on performances by utilizing the advantages of SD in capturing a feedback process and state changes, especially in human factors (e.g., attitude, ability, and behavior). The model incorporates: (a) a multi-level skill evolution and relevant behavior development mechanism within a work group; (b) the interaction among work planning, a crew's skill-learning, skill manifestation, and performances; and (c) the different work characteristics of each activity. This model can be utilized to implement appropriate work planning (e.g., work scope and work schedule) and crew management policies (e.g., work team composition and decision of each worker's role) with an awareness of crew's skill and work performance. Understanding the different characteristics of each activity can also support project managers in applying strategic work planning and crew management for a corresponding activity, which may enhance each activity's performance, as well as the overall project performance.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.41-54
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• 2024

Efforts to reduce on-site safety incidents have expanded, leading to active research in this domain. However, a systematic analysis to improve the utility of technology is lacking. In this study, we conducted a survey on the various institutional and technical improvement measures to promote the application of smart construction safety technology over three years after the implementation of the "Smart Safety Equipment Support Project." The results showed that financial constraint was the primary obstacle in the adoption of this innovation. Fostering a flexible environment in the utilization of management fees and financial support of projects was determined to aid in the extensive application of the technology. Ensuring cost efficiency and user-friendliness were principally necessary for technical enhancements in the smart construction safety technology. Technologies, such as VR/AR safety education, real-time location tracking, wearable devices, and innovation on streamlining safety-related work efficiency, had been anticipated to contribute to on-site safety. Operating a smart safety control center was expected to be beneficial in the systematic securing of data and reduction of safety blind spots. Effective methods had been suggested to overcome the barriers that hindered the development and application of smart construction safety technology. This study facilitates in the technological improvements in this field.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.47-56
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• 2019

Although the weapon systems are becoming more diverse and complex, they are progressing in a short development period and a longer test and evaluation period. The more difficult the given environment is, the more efforts and performance of quantitative target values can be made by development agencies to carry out stable projects. However, these target values of the Integrated Logistics Support are not specified in the requirements and being set during the system development phase. In this paper, application of MOEs, MOPs and TPMs for ILS are presented and provided the basis for carrying out systematic Verification & Validation activities. As a result that MOEs of the ILS were chosen as Availability and MOPs as Mission Reliability, Logistics Reliability, Maintainability and Supportability and TPMs as MTBF, MTBCF, MTTR and so on. In particular, it is appropriate tailoring and apply the TPMs considering the cost, schedule, scope of work and characteristics of the project.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.201-206
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• 2020

Diversification of project delivery methods (PDM) under ever-changing construction business environment has significantly changed the role of project participants. Active efforts to effectively sharing the roles and responsibilities have been observed in the project management offices (PMOs) among owner/operator organizations as well as engineering, procurement, construction and maintenance (EPCM) firms. In order for being effective in a holistic way throughout the project life-cycle, a PMO needs to have 'adequate management skills' as well as 'essential technical capabilities' in cooperating with many different participants. One of the well-known examples of the PMO's tool to support these skills and capabilities is the effective 'work packaging (WP)' that serves as a common basis integrating all relevant information in a structured manner. In an attempt to enhance the construction productivity, the concept of 'advanced work packing (AWP)' has been introduced by Construction Industry Institute (CII). The AWP enables productivity to be improved by early planning of construction packages in the design phase "with the end in mind". The purpose of this study is to identify and evaluate the 'variables' of advanced work packing (AWP) for life-cycle information integration. Firstly, an extended concept of advanced WP based on the CII AWP was defined in order to comprehend many different issues of business functions (e.g. cost, schedule, quality, etc.). A structured list of major components and variables of AWP were then identified and examined for practical viability with real-world examples. Strategic fits and managerial effectiveness were stressed throughout the analyses. Findings, implications and lessons learned are briefly discussed as well.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.

• Journal of the Korean Society of Systems Engineering
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• v.9 no.1
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• pp.47-53
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• 2013

The object of this study is to define systematically for outputs of Verification Process among the system life cycle process based on ISO/IEC 15288 for power supply system, which is one of the importance sub-systems to configure the LRT system. Furthermore, to prevent various problem in advance that can occur in the Transition LRT's power supply to be completed Integration. For this purpose, traceability of verification requirement and outputs. should be managed to use verification for system requirement and data processing tool. by system engineering techniques of system life cycle process based on ISO/IEC 15288 to LRT system.