• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.123-130
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• 2006

Recently, Korean government promotes BTL(Build-Transfer-Lease) for their public construction project to apply private sector's experience and finance initiatives. Many of public buildings and civil infrastructure projects were planned to be delivered by BTL and it helps to continue public projects under tight budget conditions. Since the characteristics of BTL projects, creative ideas for the project function, performance and its LCC (Life Cycle Cost) become more important than usual public work project. This paper introduces the systematic "VE job Plan" application techniques for BTL project and shows the process. This study shows the application of "VE job Plan" for BTL project to help decision making and value improvement. Also, Project cost was estimated by LCC (Life Cycle Cost) analysis. Technical "FAST diagram"was developed and used to find major functions of the project. So, it helps to improve performance of functions and make creative ideas. FAST diagram also help to find relationships between functions and cost. A case study (Daegu Art Gallery BTL Project) was conducted using proposed "VE job Plan. Study demonstrates how value management helps save money and increase functional performance. Researcher found that project can save cost and improve performance of functions significantly by using appropriate VE analysis process at appropriate time.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.457-464
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• 2008

In the real-world operational environment, most of text classification systems have the problems of insufficient training documents and no prior knowledge of feature space. In this regard, $Na{\ddot{i}ve$ Bayes is known to be an appropriate algorithm of operational text classification since the classification model can be evolved easily by incrementally updating its pre-learned classification model and feature space. This paper proposes the improving technique of $Na{\ddot{i}ve$ Bayes classifier through feature weighting strategy. The basic idea is that parameter estimation of $Na{\ddot{i}ve$ Bayes considers the degree of feature importance as well as feature distribution. We can develop a more accurate classification model by incorporating feature weights into Naive Bayes learning algorithm, not performing a learning process with a reduced feature set. In addition, we have extended a conventional feature update algorithm for incremental feature weighting in a dynamic operational environment. To evaluate the proposed method, we perform the experiments using the various document collections, and show that the traditional $Na{\ddot{i}ve$ Bayes classifier can be significantly improved by the proposed technique.

• Journal of the Korean Geosynthetics Society
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• v.15 no.1
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• pp.59-70
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• 2016

The purpose of this study is to review that the VE techniques can be used as a selection tool of borrow pit locations. The analysis of the soil investigation report is performed for the selection of proposed borrow pit site on a large-scale residential development area. Possible earthwork volume of mining is estimated and the weighting matrix evaluation is applied to the VE techniques. After determining the evaluation items for VE assessment, important degree was calculated. The Rating and evaluation of performance is carried out on a proposed borrow pit site. And, development priority has to be decided for a proposed borrow pit sites. As a result, the relative construction cost is closely related to the haulage distance. As the haulage distance increases, the relative construction cost will be increased. Therefore, it was confirmed quantitatively that haulage distance has a significant impact on the select of borrow pits. Also, it was found that the condition of borrow pits itself is important, but it cannot be ignored the impact of the life cycle cost for the selection of optimal borrow pit sites.

• Journal of Korean Electronics
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• v.5 no.6
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• pp.98-100
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• 1985

• Construction Engineering and Management
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• v.1 no.3 s.3
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• pp.36-38
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• 2000

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.85-92
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• 1993

This study aimed at the improvement of the conventional methods of Velue Engineering Function Analysis, the most important phase of VE processes, through Quality Function Development and Analytic Hierarchy Process. This study was performed in both theory and study. In the theoretical study, the necessity and the fitness of the connection between VE and QC techniques were studied. The use of Function Requirement Coefficients in Quality Function Development makes the more objective Function Evaluation possible.

• Korean Journal of Construction Engineering and Management
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• v.5 no.3 s.19
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• pp.106-113
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• 2004

Most construction project managers should focus on the reasonable cost-down with same quality and function-enhancement with same cost for the value-added construction project delivery in construction industry. Especially, a building structure construction is one of the most important processes to affect the total cost and schedule in building construction project. It means that the process has the possibility of project cost-down or quality-enhancement among the whole project life-cycle. This research focuses on the importance of underground structure of building project by increasing underground use ratio in the urban building construction projects nowadays. This research adopts VE method for the improvement of cost and time by process and analysis dimension modeling on the underground building structure construction, and verifies it throughout the case study, This research is the basic study on the improvement of underground building works through the value engineering method in construction industry.

• 기술발표회
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• s.2006
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• pp.279-291
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• 2006

This study shows decision-making process for selection of cutoff wall on a wastewater treatment project. There are 10 different cut-off wall methods So, we examine the site to gather information for find appropriate methods. After using that information, 10 cutoff wall methods are reviewed for analysis. Through brainstorming, four alternatives are selected for design VE item. Following the standard VE process, we established performance criteria and evaluated function score(F) using questionnaire. The questionnaires, brainstorming and AHP method for weighting on performance criteria and evaluate function score increased the reliability of this selection process. Water Jet method, one of four methods, has the best function score(F=92.71) and the lease construction cost(as cost index 1,000). The value score also highest as 92.7, so we select the method. The result is value innovation type In addition, the authors try to calculate the environmental burden in selection process using LCA. We cannot conduct the full LCA as defined ISO, so perform Simple LCA In LCA result, the cut-off grouting has the least environmental burden as index 9.09E+01 and Water Jet method has following as the second. To selection best method to specific area and purpose, design VE/LCG process used as useful tool and it is needed to develop integrated method that evaluate VEILCC and LCA as one-set process.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.122-132
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• 2005

The importance of design value engineering in construction projects recently is rising, which deal about in reduction of cost and improvement of quality. Especially, From half of this year 2005, It is predicted that the value engineering is necessary to be carried out in the projects having project cost more than 10 billion won. In increasing importance of value engineering, we require a way by which we accomplish value engineering systemically and effectively though it is not common in domestic situation. So, this case study shows a way in carrying out value engineering effectively. As the way is to apply QFD(Quality Function Deployment) in pre-study work of design value engineering, this is expected to contribute as function analysis and reflect the requirement of users or owners.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.100-102
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• 2005

인터넷 환경에서의 B2B Market Place의 출현은 판매자와 구매자와의 다자간 거래를 가능하게 하였다. 이러한 기반에서 상품정보를 포함하는 전자 카탈로그의 활용은 나날이 증가하고 있다. 그러나 동일한 상품에 대한 분류체계와 기준이 다르므로 전자카탈로그에 대한 재분류는 고비용을 초래하는 필수 불가결한 문제로 남게 되었다. 본 연구에서는 이러한 문제를 해결하기 위해 기계학습 기법을 이용한 $Na\ddot{i}ve$ Bayesian classifier 모델을 사용하였다 학습 데이터를 생성해야 하는 $Na\ddot{i}ve$ Bayesian 알고리즘 적용 시 전자 카탈로그는 일반 문서보다 상대적으로 학습 정보가 적으므로 데이터 모델의 확장을 통해 학습 정보를 생성하여 이러한 단점을 보완하였다. 전자 카탈로그 자동분류에 있어서 효과적이고 풍부한 양의 학습 데이터를 생성하는 것이 분류 정확도 향상에 중요한 영향을 미침을 실험을 통해 확인하였다.