• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1693-1705
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• 2013

To restore old aqueduct in Korea which is a irrigation bridge to supply water in paddy field area, it is needed to estimate approximate costs of restoration because the basic design for estimation of construction costs is often ruled out in current system. In this paper, estimating models of construction costs were developed on the basis of performance data for restoration of RC aqueduct bridges since 2003. The regression analysis (RA) model and case-based reasoning (CBR) model for the estimation of construction costs were developed respectively. Error rate of simple RA model was lower than that of multiple RA model. CBR model using genetic algorithm (GA) has been applied in the estimation of construction costs. In the model three factors like attribute weight, attribute deviation and rank of case similarity were optimized. Especially, error rate of estimated construction costs decreased since limit ranges of the attribute weights were applied. The results showed that error rates between RA model and CBR models were inconsiderable statistically. It is expected that the proposed estimating method of approximate costs of aqueduct restoration will be utilized to support quick decision making in phased rehabilitation project.

• Journal of The Korea Institute of Healthcare Architecture
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• v.3 no.4
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• pp.35-49
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• 1997

The percentage of postnatal disabled people and elderly population is rapidly increased by the industrialization, and the improvement of medical technology. The disparity between the city and rural area is in the way to disabled people who need rehabilitation. To solve these problems, Community Based Rehabilitation(CBR) is suggested by WHO. In this study, at first, the CBR model considering the specific characteristics of AnSan City are presented. Secondly, the first, the second, and the third rehabilitation facilities in AnSan City are classified by the CBR model. Thirdly, the estimation of optimum space for physical therapy and occupational therapy at rehabilitation center and public health center are sugested, which are the second level rehabilitation facilities. There are some differences in the distribution of population between new and old area in AnSan City. In other words, the subject population of CBR program in old area is relatively higher than that of new area. So, the CBR program for AnSan City must reflect their regional characteristics. In this study, the therapeutic boundaries of second level rehabilitation facilities is decided through the survey of physical therapists and occupational therapists in general hospitals and nursing homes.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.433-436
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• 2002

본 논문은 인터넷상에서 전자우편물을 자동으로 생성하기 위한 에이전트에 관한 연구로서, 사례기반추론(Case-Based Reasoning:CBR) 모델을 통하여 우편물 발송자의 특성에 적응하는 에이전트의 설계 방안을 제안한다. 먼저, 지능형 에이전트와 사례기반 추론에 관하여 간략하게 조사한 후, 전자우편분석 에이전트, 색인 에이전트, 검색엔진 등으로 구성되는 다중 에이전트 시스템을 보여준다. 특히, 인공지능 기법 중의 하나인 사례기반추론의 유사도 계산 방식과 새로운 CBR 처리주기를 이용하여 전자우편물을 자동으로 생성하는 에이전트 시스템을 제안한다. 그리고 Databases와 Case-Bases를 설명하고 전자우편 자동생성 에이전트를 위한 CBR 처리주기를 제안한다. 그 다음, 에이전트와 사례 연구를 위한 프로토타입을 제공한다. 향후, Data-Mining 기법의 연구는 이 시스템이 사용자의 다양한 취향에 적응할 수 있는 유용한 시스템으로 발전하는데 도움이 될 것이다.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.1-14
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• 2007

Case-based reasoning (CBR) is one of the most widely applied data mining techniques and has proven its effectiveness in various domains. Since CBR is basically based on k-Nearest Neighbors (NN) method, the value of k affects the performance of CBR model directly. Once the value of k is set, it is fixed for the lifetime of the CBR model. However, if the value is set greater or smaller than the optimal value, the performance of CBR model will be deteriorated. In this research, we propose a new method of composing the NN set using similarity scores as themselves, which we shall call s-NN method, rather than using the fixed value of k. In the s-NN method, the different number of nearest neighbors can be selected for each new case. Performance evaluation using the data from UCI Machine Learning Repository shows that the CBR model adopting the s-NN method outperforms the CBR model adopting the traditional k-NN method.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.115-121
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• 2010

To evaluate the engineering characteristics of aggregate base materials, cyclic triaxial, CBR and permeability tests were performed for 15 samples. The CBR values of aggregate base materials have wide range from 32 to 110(average 81) and the amount of swelling in submerged conditions has below 0.04mm. The Modulus of aggregate base materials were significantly affected by volumetric stress, linear volumetric model was best for fitting. The modulus of aggregate base materials were determined within range of 100MPa~600MPa, 80~270 and 0.1~0.6 for model coefficient $k_1$ and $k_2$ respectively. The empirical correlation model was suggested that prediction the modulus from the basic properties obtained from particle size distribution test and compaction test. The coefficient of determination of the proposed correlation model was 0.423 for model coefficient $k_1$, 0.920 for model coefficient $k_2$ and 0.872 for modulus with stress level.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.40-48
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• 2014

As CBR(Chemical, Biological, and Radiological) attack increases, the importance of CBR protective facilities is being emphasized. When CBR warfare emerges, a task force team, who exist outside of CBR protective facility, should enter the CBR protective facility through neutralizing process in CCA(Contamination Control Area) and TFA(Toxic Free Area). If a bottleneck occurs in the process or zones, the task force team cannot enter the CBR protective facility efficiently and may cause inefficiency in its operation performance or result in casualties. The current design criteria of the CBR protective facility is only limited to ventilation system and it does not consider how much time it takes to enter the facility. Therefore, this research aims to propose the entering time estimation model with discrete event simulation. To make the simulation model, the procedure performed through CCA and TFA is defined and segmented. The actual time of the procedure are measured and adapted for the simulation model. After running the simulation model, variables effecting the entering time are selected for alternatives with adjustments. This entering time estimation model for CBR protective facility is expected to help take time into consideration during the designing phase of CBR protective facility and help CBR protective facility managers to plan facility operation in a more realistic approach.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.432-437
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• 2002

As the working design process of Turn-Key projects is a basic process for the final contract, this process has lots of business decision to be made. Because such results of business decision can be the basis on contract documents, it is the step which needs a through management for Turn-key project. But in case of domestic construction companies, because those are not organized process of working design process, project manager has had lots of trouble at each process to make the business decision. As a means of settling the problems, this research is initiated. First, working decision management process is identified and generalized by interviews with project managers. Second, cases that actually happened in the project are investigated and categorized. Third, response plan to solve the problems and check lists to prevent the problems are suggested. Finally, the process, cases, response plan, and check list are integrated using CBR for future reuse.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.451-462
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• 2008

Recently, with the advent of applications using locations of moving objects, it becomes crucial to develop efficient index schemes for spatio-temporal databases. The $TPR^*$-tree is most popularly accepted as an index structure for processing future-time queries. In the $TPR^*$-tree, the future locations of moving objects are predicted based on the CBR(Conservative Bounding Rectangle). Since the areas predicted from CBRs tend to grow rapidly over time, CBRs thus enlarged lead to serious performance degradation in query processing. Against the problem, we propose a new method to adjust CBRs to be tight, thereby improving the performance of query processing. Our method examines whether the adjustment of a CBR is necessary when accessing a leaf node for processing a user query. Thus, it does not incur extra disk I/Os in this examination. Also, in order to make a correct decision, we devise a cost model that considers both the I/O overhead for the CBR adjustment and the performance gain in the future-time owing to the CBR adjustment. With the cost model, we can prevent unusual expansions of BRs even when updates on nodes are infrequent and also avoid unnecessary execution of the CBR adjustment. For performance evaluation, we conducted a variety of experiments. The results show that our method improves the performance of the original $TPR^*$-tree significantly.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.9-14
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• 1998

멀티미디어를 실시간으로 서비스하는 비디오 서버의 설계 시, 네크워크 가용공간, 버퍼 공간 및 디스크 전송률 등이 고려되어야 하며, 특히 버퍼 공간과 디스크 전송률을 동시게 고려하는 기법이 제시되었지만, VOD 서버에서는 보통 MPEG데이터가 VBR 형식으로 되어 있기 때문에 CBR로 모델링하면 시스템의 가용성이 떨어지게 된다. 또한 수용제어를 위한 버퍼 예약기법에서는 VBR 형태로 데이터를 모델링하는 기법들이 제시되었지만, 이 경우에도 디스크 전송률을 계산할 때는 CBR형식으로 가정하거나 아예 고려를 하지 않기 때문에 역시 시스템 자원을 효율적으로 사용할 수 없다. 본 논문에서는 VBR 비디오 서버의 설계를 위하여 서버에서 처리되는 각 스트림들을 하드 실시간 태스크 모델로 모델링하고 실시간 태스크들을 효율적으로 처리할 수 있는 실시간 스케쥴링 알고리즘을 제안한다. 이 실시간 스케쥴링 알고리즘을 디스크 액세스의 승인제어, 디스크 스케쥴링, 버퍼 관리에 이용하므로서 연속성을 보장할 수 있는 효율적인 VBR 연속 미디어 서버를 설계할 수 있다. 비디오 서버의 성능은 시뮬레이션을 이용하여 분석하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.588-594
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• 2005

사례기반추론(Case-Based Reasoning)은 다양한 예측 문제에 있어서 성공적으로 활용되고 있는 데이터마이닝 기법 중 하나이다. 사례기반추론 시스템의 예측 성능은 예측에 사용되는 최근접이웃(Nearest Neighbor)을 어떻게 설정하느냐에 따라 영향을 받게 된다. 따라서 최근접 이웃을 결정짓는 k 값의 설정은 성공적인 사례기반추론 시스템을 구축하기 위한 중요 요인 중 하나가 된다. 최근접 이웃의 설정에 있어서 대부분의 선행 연구들은 고정된 k 값을 사용하는 사례기반추론 시스템은 k 값을 크게 설정할 경우 최근접 이웃 안에 주어진 오류를 일으킬 수 있으며, k 값이 작게 설정된 경우에는 유사 사례 중 일부만을 예측에 사용하기 때문에 예측 결과의 왜곡을 초래할 수 있다. 본 이웃을 결정함에 있어서 Similarity Threshold를 이용하는 s-NN 방법을 제안하였다. 본 연구의 실험을 위해 UCI(University of california, Irvine) Machine Learning Repository에서 제공하는 두 개의 신용 데이터 셋을 사용하였으며, 실험 결과 s-NN 적용한 CBR 모델이 고정된 k 값을 적용한 전통적인 CBR 모델보다 더 우수한 성능을 보여주었다.