• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.19-38
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• 2011

This study aims to apply a teaching-learning model using science oriented UCC created by students themselves(4C model) in a gifted students' project learning and investigate its effects in science-related affective property by gender in order to use UCC systematically in a gifted students' project learning course. After conducting of gifted students' using UCC project learning, We surveyed gifted students' recognition about it. Nonparametric test has done with the results of before and after science-related affective property tests of them. As results, gifted students took an active part in 'using UCC project learning'. Girls are more active and interested than boys whereas more boys felt a difficulty in creating UCC than girls. Girls' creativity was improved and anxiety about science was decreased whereas the results of boys were not statistically significant. Therefore, 'using UCC project learning' is more effective than tha of boys to girls.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.58-75
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• 2009

As practicalization and commercialization of the technologies invented from the national R&D(Research & Development) project has been emerging as an important issue, the need for a tool for R&D project management has been increased. Technology Readiness Levels model(TRL) has currently been used for R&D project management because it provides distinctive definition of the nine levels in the progress of technology development starting from the basic research level to the utilization level. However, it is difficult to adopt the model for a large-scale national R&D project in which multiple research projects are involved simultaneously. In addition, TRL demands evaluation of research projects done by relevant experts and offers no specific measures determining the level of technology development. This study uses Delphi method to develop the measurement system helping to determine technology readiness levels for the technologies invented in a large scale national R&D project. The proposed model includes definition and measurement scles for each level in TRL.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.

• Journal of Korean Society of Rural Planning
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• v.20 no.3
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• pp.89-100
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• 2014

The purpose of this study is to investigate whether the effect of the Strong Small Farm Development Project by Rural Development Administration is positively associated with participating farmers. The data that used in this study is a survey data that targets 442 farming households who have participated in the strong small farm development project. This study applies ordered-probit model to evaluate level of the participants' satisfaction of the project. This study found that participants' level of satisfaction is closely associated by satisfaction level of project contents that contains education and consulting, friendly attitude toward the project, active participation of the project, and understanding of the project's contents and their importances. Based on research findings, this research provides some implications of future upbringing policy for strong small farms and the principal point of the policy that leads to succeed in implementing the project when formulating agricultural policy in participants view. the strong small farms.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.196-203
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• 2022

The resource constrained scheduling problem (RCSP) constitutes one of the most challenging problems in Project Management, as it combines multiple parameters, contradicting objectives (project completion within certain deadlines, resource allocation within resource availability margins and with reduced fluctuations), strict constraints (precedence constraints between activities), while its complexity grows with the increase in the number of activities being executed. Due to the large solution space size, this work investigates the application of Genetic Algorithms to approximate the optimal resource alolocation and obtain optimal trade-offs between different project goals. This analysis uses the cost of exceeding the daily resource availability, the cost from the day-by-day resource movement in and out of the site and the cost for using resources day-by-day, to form the objective cost function. The model is applied in different case studies: 1 project consisting of 10 activities, 4 repetitive projects consisting of 40 activities in total and 16 repetitive projects consisting of 160 activities in total, in order to evaluate the effectiveness of the algorithm in different-size solution spaces and under alternative optimization criteria by examining the quality of the solution and the required computational time. The case studies 2 & 3 have been developed by building upon the recurrence of the unit/sub-project (10 activities), meaning that the initial problem is multiplied four and sixteen times respectively. The evaluation results indicate that the proposed model can efficiently provide reliable solutions with respect to the individual goals assigned in every case study regardless of the project scale.

• The Journal of Fisheries Business Administration
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• v.44 no.3
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• pp.103-109
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• 2013

This paper analyzed that the economic effectiveness of the artificial fish reef project in the Tae-an Marine Ranching. Benefit-cost(B/C) model used to indicate the effects of economic valuation. B/C model is based on the sub-models which are Benefit Cost Ratio(BCR), Net Present Value(NPV) and Internal Ration of Return(IRR). First, the Sum of Incremental Benefit and Cost for total vessel by year in Artificial Fish Reef Area(AFRA) estimated 2,381 million won. And then, using 5.5% discounting rates and the survey data, the sub-models showed economically feasible in the all of analysis and analyzed the results as follows. BCR is 2.66, NPV is 28,014million won, and IRR is 22.78%. In conclusion, these results indicated that the artificial fish reef project in Tae-an Marine Ranching would be increase the income of fishermen as well as fish biomass.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.359-364
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• 1999

Providing the reasonable construction cost at the initial stage of the rural development project, is a kety factor of the each step of project , such as propriety analysis , cost planning , design, and planning the progress of work. The explainable construction cost can be estimated at the early stage using the actual cost data by statistical analysis. In this study, the influence factors are extracted by factor analysis with the actual cost data of rural development project, object cost model is developed by multiple regression analysis, and verify the developed cost model by Monte-Carlo simulation .

• Journal of the Korea Institute of Building Construction
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• v.12 no.5
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• pp.518-527
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• 2012

This study uses a hybrid estimation tool for effective cost data management of building projects, and develops a realistic cost estimation model. The method makes use of newly available information as the project progresses, and project cost and percentage progress are analyzed and used as inputs for the developed system. For model development, case-based reasoning (CBR) is proposed, as it enables complex nonlinear mapping. This study also investigates analytic hierarchy process (AHP) for weight generation and applies them to a real project case. Real case studies are used to demonstrate and validate the benefits of the proposed approach. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.256-270
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• 2011

The study attempts to propose and test a causal research model using SEM (Structural Equation Model) to determine whether there is a relationship between six sigma champion's transformational leadership and belts' creativity based on the mediated effects of intrinsic motivation and project's learning and growth. The subjects of the study composed of 134 belts from manufacturing and service firms implemented six sigma. Empirical results show that transformational leadership is positively related to intrinsic motivation and project learning and growth. In addition, intrinsic motivation and project learning and growth are positively related to creativity. The results of the study imply that creativity of six sigma belts would be enhanced by implementation of six sigma projects and utilizing six sigma tools and methods.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.208-209
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• 2022

This study aims to analyze the risk factors caused by object damage and third-party damage loss in actual bridge construction based on past insurance premium payment data from major domestic insurers for bridge construction projects, and develop a quantitative loss prediction model. For the development of quantitative bridge construction loss model, the dependent variable was selected as the loss ratio, and the independent variable adopted 1) Technical factors: superstructure type, foundation type, construction method, and bridge length 2) Natural hazards: flood anf Typhoon, 3) Project information: total construction duration, total cost and ranking. Among the selected independent variables, superstructure type, construction method, and project period were shown to affect the ratio of bridge construction losses, while superstructure, foundation, flood and ranking were shown to affect the ratio of the third-party losses.