• Proceedings of the KSR Conference
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• 2005.05a
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• pp.646-654
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• 2005

The crossing construction under railroad have two methods which are cut and cover and trenchless method. First, cut and cover method is an extremely limited method concerning non-running time. Whereas, trenchless method is free from restriction such as train speed and running time, and has the strong points of safe and rapid construction. Front Jacking method, one of the trenchless methods, is frequently applied recently due to its stability during construction and vantage of assuring schedule reliability. The procedure is that after minimizing interlocking friction with structure and earth pressure due to jacking the small steel tube, pulling the precast box manufactured at the field in the ground using PC strand and hydraulic Jack. This method is able to be applied regardless of section size and length of box and condition of soil. And that is also pro-environmental. This paper presents the case of Daejeon E. W. perforate Road Project applied with the Front Jacking method.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1681-1698
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• 2011

According to the demands of the times, Inchon international airport railroad opened up step by step but It is situation that much government subsidies are paid because It does not competitive power with road traffic by decline of schedule speed. Inchon international airport railroad users will convert by other transportation and minimize damage their time as travel time is prolonged. Therefore, need high speedization of airport railroad, this may act big role competitive power security as well as airport railroad activation with another public transportation. Thus, this paper suggests that a high speedization possibility section in the sections of airport railroad and train speed elevation effect analysis by roadbed, railroad, system improvement and the most efficient operation intervals analyzing each vehicles (AREX (120km/h), KTX (230km/h), EMU(Electric Multiple Unit, 180km/h) train running pattern.

• Journal of the Korean Society of Systems Engineering
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• v.7 no.2
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• pp.7-11
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• 2011

A high-speed railway system represents a typical example of large-scale multi-disciplinary system, consisting of subsystems such as rolling-stock, electrical hardware, electronics, control, information, communication, civil technology etc. The system design and acquisition data of the large-scale system must be the subject under strict configuration control and management. Systems engineering technology development project for Korea next generation High-speed Electric Multiple Unit (HEMU) system in progress is a national large system development project that is not only a large-size and complex but also multi-disciplinary in nature. Therefore, all stakeholders must understand and share the functional and performance requirements of HEMU throughout its life-cycle phases. Also in the test and evaluation phase, all systems requirements must be verified. In 2011, the prototype train manufacturing will be completed. It will do test run on the commercial line and all systems requirements are verified until 2012. For the system verification, the test and evaluation process have to be established before the test trial run. Using a systems engineering tool, the system design database(SDD) with requirements traceability and development process management in the course of the development have to be established. This paper represents the test and evaluation process development based on the SEMP(Systems Engineering Management Plan) developed in the design stage. The test and evaluation process is refined and updated in comparison to the design stage one. The test and evaluation process consists of procedure, test and evaluation method and schedule. So through this process, it is defined that each systems requirements is verified on which test and about what time.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.89-97
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• 2004

The Korea Air Force(KAF) has operated freight flights based on the prefixed time and route schedule, which is adjusted once in a month. The major purpose of the operation of freight flights in the KAF is to distribute necessary supplies from the home air base to other air bases. The secondary purpose is to train the young pilots to get more experiences in navigation. Each freight flight starts from and returned to the home air base everyday except holidays, while it visits several other air bases to accomplish its missions. The study aims to forecast freight demand at each base by using time series analysis, and then it tried to optimize the cost of operating flights by solving vehicle routing problem. For more specifically, first, several constraints in operating cargos were defined by reviewing the Korea Air Force manuals and regulation. With such constraints, an integer programming problem was formulated for this specific routing problem allowing several visits in a tour with limitation of maximum number of visits. Then, an algorithm to solve the routing problem was developed. Second, the time series analysis method was applied to find out the freight demand at each air base from the mother air base in the next month. With the forecasted demands and the developed solution algorithm, the oprimum routes are calculated for each flight. Finally, the study compared the solved routing system by the developed algorithm with the existing routing system of the Korea Air Force. Through this comparison, the study proved that the proposed method can provide more (economically) efficient routing system than the existing system in terms of computing and monetary cost. In summary, the study suggested objective criteria for air routing plan in the KAF. It also developed the methods which could forecast properly the freight demands at each bases by using time series analysis and which could find the optimum routing which minimizes number of cargo needed. Finally, the study showed the economical savings with the optimized routing system by using real case example.

• Cartoon and Animation Studies
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• s.37
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• pp.491-508
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• 2014

As number of making 3D feature animation films is increasing, 3D production pipeline become more complicated and more artists are needed than before. Major studios in foreign countries, in burden of producing high quality films with limited amount of budget and time, have been handling such difficulties by hiring technical directors in each department such as animation, rigging, cloth hair, and effect. Technical director is new occupation which appears after trend of producing animation is changed from 2D to 3D. Importance of technical director is increasing in respect to studios' needs which are related to complication in production time, manpower, budget, and production pipeline. This research is based on the researcher's work experience as an animation TD at Walt Diseny Animation Studio and Sony Pictures Imageworks, interview with working professionals, and related books and thesis. It focuses on the role of animation technical director in Disney's 3D feature animation film from two perspectives, 'Designing Production Pipeline' and 'Analyzing Problem of Shot'. Animation technical directors design and test production pipeline so that they can detect and solve problems that may arise in production process as early as possible. They not only analyze numerous problems of characters or shots limited to animation department but also in other departments such as modeling, mapping, character rigging, cloth, hair, lighting, rendering, software development in order to support artists to complete their shots according to the production schedule. In accordance with recent trend of increasing number of 3D feature animation film production in South Korea and collaboration with foreign studios outside of South Korea, it is vital to train animation technical directors who can develop production pipeline, analyze various problems of shots and characters to escalate efficiency in production.

• 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.