• 연구논문집
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• s.27
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• pp.47-55
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• 1997

Fatigue life prediction of mechanical components is necessary to develop new products, which is very expensive and time-consuming. This paper reviews technologies proposed for computation of dynamic stress in mechanical components. The methods based on multibody dynamics are considering more real operational conditions than other methods. The technology for fatigue life prediction without the prototype for experiment results in cost and time saving. This technology can be applied to design of various mechanical components like carbody.

• ETRI Journal
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• v.35 no.2
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• pp.270-280
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• 2013

A fast intra-prediction method is proposed for High Efficiency Video Coding (HEVC) using a fast intra-mode decision and fast coding unit (CU) size decision. HEVC supports very sophisticated intra modes and a recursive quadtree-based CU structure. To provide a high coding efficiency, the mode and CU size are selected in a rate-distortion optimized manner. This causes a high computational complexity in the encoder, and, for practical applications, the complexity should be significantly reduced. In this paper, among the many predefined modes, the intra-prediction mode is chosen without rate-distortion optimization processes, instead using the difference between the minimum and second minimum of the rate-distortion cost estimation based on the Hadamard transform. The experiment results show that the proposed method achieves a 49.04% reduction in the intra-prediction time and a 32.74% reduction in the total encoding time with a nearly similar coding performance to that of HEVC test model 2.1.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.497-502
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• 2002

Conditional branches can severely limit the performance of instruction level parallelism by causing branch penalties. 2-level adaptive branch predictors were developed to get accurate branch prediction in high performance superscalar processors. Although 2 level adaptive branch predictors achieve very high prediction accuracy, they tend to be very costly. In this paper, set-associative cached correlated 2-level branch predictors are proposed to overcome the cost problem in conventional 2-level adaptive branch predictors. According to simulation results, cached correlated predictors deliver higher prediction accuracy than conventional predictors at a significantly lower cost. The best misprediction rates of global and local cached correlated predictors using set-associative caches are 5.99% and 6.28% respectively. They achieve 54% and 17% improvements over those of the conventional 2-level adaptive branch predictors.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.61-74
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• 2003

This study(II) apply to the A city by using the optimal rehabilitation model based on the deterioration prediction of the water distribution system proposed the study(I). The deterioration prediction model divides factors into 14 factors with digging and experiment and 9 factor without digging and experiment and calculate the deterioration degree. The application results of the deterioration prediction model show that a difference of the deterioration degree according to factor numbers is within 1~2%. Also, the model can predict the deterioration degree of each pipe without digging and experiment. The optimal rehabilitation model is divided into the optimal residual durability of each deterioration factor and budget constraint or not. The application result is as follow: the rehabilitation time and cost increase according to the increasing of the optimal residual durability. When compared the model with budget constraint and model without budget constraint, the former model increase the cost of total contents. In case of budget constraint, the increasing tendency is concluded that the pipe rehabilitation is executed in same budget every year in condition that every rehabilitation cost do not exceed the every year budget within the optimal residual durability.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.12-15
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• 2015

Size of building has a direct relationship with building cost, energy use and space maintenance cost. Therefore, minimizing building size during a project development is of paramount importance against such wastes. However, incautious reduction of building size may result in crowded space, and therefore harms the functionality despite the fact that building is supposed to satisfactorily support users' activity. A well-balanced design solution is, therefore, needed at an optimum level that minimizes building size in tandem with providing sufficient space to maintain functionality. For such design, architects and engineers need to be informed accurate and reliable space-use information. We present in this paper a conceptual framework of an agent-based space-use prediction simulation system that provides individual level space-use information over time in a building in consideration of project specific user information and activity schedules, space preference, ad beavioural rules. The information will accordingly assist architects and engineers to optimize space of the building as appropriate.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.702-703
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• 2015

Currently, according to the climate change, serious damage by Typhoon has been occurred in the world. In this respect, the research on the damage prediction model to minimize the damage from various natural disaster has been conducted in several developed countries. In the case of U.S, various damage prediction models of buildings from natural disasters have been used widely in many organizations such as insurance companies and governments. In South Korea, although studies regarding damage prediction model of hurricane have been conducted, the scope has been only limited to consider the property of hurricane. However, it is necessary to consider various factors such as socio-economic, physical, geographical, and built environmental factors to predict the damages. Therefore, to address this issue, correlation analysis is conducted between various variables based on the data of hurricane from 2003 to 2012. The findings of this study can be utilized to develop for predicting the damage of hurricane on buildings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.186-192
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• 2009

With the proliferation of ubiquitous computing we have witnessed the wide application of many wireless sensor networks into various areas because of easy installations and low-cost merits. The commercially available equipments for monitoring and predicting cracks in the mountain regions are still burden for us in terms of the installation complexity and the cost. Alternatively we in this paper design and implement a pilot slop-crack monitoring and prediction system which is based on low-cost commercial sensor networks. The proposed system is easy to install on cliffs, slopes, rocks, and banks and may minimize the destruction of the original geographical forms. Expected is that its installation and maintenance costs may reduce to the half of those of existing systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.154-163
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• 2014

In this paper, there is suggested a fast intra prediction mode decision method in HEVC. To reduce the number of candidates in rough mode decision (RMD) process and rate-distortion optimization (RDO) process, the edge information and relative RMD cost are utilized. The experiment results show that the proposed method reduces encoding run-time by 26.81% with a negligible coding loss of 0.79% BD-rate on average.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.111-116
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• 2006

The objective of this research is to develop an assesment system for BTL Project. A new method for the prediction of construction and maintenance cost in the educational facilities has been considered and under development by the authors. This paper explains the current BTL assesment method used by most local district office of education and lists its potential problems. Main conceptual modules in the new Assesment System are shown in this paper. Also, viable results of each module are discussed in this paper.