• 전자공학회논문지
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• 제50권8호
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• pp.245-249
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• 2013

In this paper, we propose two rate control algorithms for multi-view extension of HEVC with two rate control algorithms adopted in HEVC and analyze the multi-view rate control performance. The proposed multi-view rate controls are designed on HEVC-based multi-view video coding (MV-HEVC) platform with consideration of high-level syntax, inter-view prediction, etc. not only for the base view but also for the extended views using the rate control algorithms based on URQ (Unified Rate-Quantization) and R-lambda model adopted in HEVC. The proposed multi-view rate controls also contain view-wise target bit allocation for providing the compatibility to the base view. By allocating the target bitrates for each view, the proposed multi-view rate control based on URQ model achieved about 1.83% of average bitrate accuracy and 1.73dB of average PSNR degradation. In addition, about 2.97% of average bitrate accuracy and 0.31dB of average PSNR degradation are achieved with the proposed multi-view rate control based on R-lambda model.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.177-180
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• 1997

Outliers, unexpected extraordinary observations that look discordant from most observation in a data set are commonplace in various kinds of data analysis. Since the effect of outliers on model identification could be serious, the aim of this paper is to present some ways of handling outliers in given data set and to specify a model in the presence of outliers. A procedure based on neural network which identifies outliers, removes their effects, and specifies a model for the underlying process is proposed. In contrast with traditional parametric methods requiring to estimate the model's structure and parameters before detecting outliers, the proposed procedure is a nonparametric method without the estimation of model's structure and parameters before handling outliers and could be applied for real problems in the presence of outliers. The proposed methodology is performed as followings. Firstly, outliers are detected and the detected outliers replace the prediction values using outliers detection neural network. The data set removing the effect of outliers is retraining using neural network. Therefore the effects of outliers are removed and the modeling precision can be improved. Experimental results show that the proposed method is suitable for predicting data set in the presence of outliers.

• 전기학회논문지
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• 제62권9호
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• pp.1199-1208
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• 2013

In recent years, the development of application programs for distribution system analysis and control has been essential part for distribution management system (DMS). In this paper, we propose the common database for application programs of distribution management system. The proposed database model has several characteristics as followings. First, the proposed database model is designed for the common use of almost the whole distribution application software. The static equipment model and dynamic type tables are mixed and the parallel table structure is applied. Second, the linked list structure of database are used for the fast processing of applications. The database model includes the hierarchy and non-hierarchy distribution system structure. Third, the reduction method of distribution database is applied. For this, we present the network reduction rules. The basic concept of reduction rules are the electrical unification of successive line section which has not lateral branches and the removal of simple lateral branches which has no devices and other laterals. Proposed database model is tested for the Jeju system of Korea Electric Power Corporation (KEPCO). Through the test, we verified that the proposed database structure can be effectively used to accomplish the distribution system operation.

• 산업공학
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• 제23권2호
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• pp.176-181
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• 2010

Warranty claim data analysis is a useful tool for the manufacturer because it contains many useful informations regarding reliability of the product in the real-world environments. Because of the nature of uncertainty and the incompleteness of data, some bias patterns are observed on warranty claim rate known as 'spikes'. Two types of spikes are considered. One is due to manufacturing-related failures. The other is caused by customer's behavior. This paper proposes a model by considering two types of spikes. Warranty claim data is analyzed with the proposed model. To represent spikes observed on the early warranty period, we classify failures into manufacturing-related failures and usage-related failures. Uniform distribution is assumed for the time delayed to diagnose and report by customers. By reducing maximum value of the delayed time by customers, the proposed model characterizes customer's rush in the vicinity of the warranty expiration limit. Experimental results by using the real warranty claim data show that the proposed model is better than the existing one in respect to MSE(Mean Squared Error). Moreover it is expected to estimate the failure rate more realistically with proposed model because it considers the delayed time to diagnose and report by customers.

• Computers and Concrete
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• 제17권1호
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• pp.29-51
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• 2016

Tension-stiffening is the contribution of concrete between the cracks to carry tensile stresses after cracking in Reinforced Concrete (RC) members. In this paper, a tension-stiffening model has been proposed for computationally efficient nonlinear analysis of RC flexural members subjected to service load. The proposed model has been embedded in a typical cracked span length beam element. The element is visualized to consist of at the most five zones (cracked or uncracked). Closed form expressions for flexibility and stiffness coefficients and end displacements have been obtained for the cracked span length beam element. Further, for use in everyday design, a hybrid analytical-numerical procedure has been developed for nonlinear analysis of RC flexural members using the proposed tension-stiffening model. The procedure yields deflections as well as redistributed bending moments. The proposed model (and developed procedure) has been validated by the comparison with experimental results reported elsewhere and also by comparison with the Finite Element Method (FEM) results. The procedure would lead to drastic reduction in computational time in case of large RC structures.

• Wind and Structures
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• 제19권6호
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• pp.623-647
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• 2014

In this paper, a probability distribution which is consistent with the observed phenomenon at the roof corner and, also on other portions of the roof, of a low-rise building is proposed. The model is consistent with the choice of probability density function suggested by the statistical thermodynamics of open systems and turbulence modelling in fluid mechanics. After presenting the justification based on physical phenomenon and based on statistical arguments, the fit of alpha-stable distribution for prediction of extreme negative wind pressure coefficients is explored. The predictions are compared with those actually observed during wind tunnel experiments (using wind tunnel experimental data obtained from the aerodynamic database of Tokyo Polytechnic University), and those predicted by using Gumbel minimum and Hermite polynomial model. The predictions are also compared with those estimated using a recently proposed non-parametric model in regions where stability criterion (in skewness-kurtosis space) is satisfied. From the comparisons, it is noted that the proposed model can be used to estimate the extreme peak negative wind pressure coefficients. The model has an advantage that it is consistent with the physical processes proposed in the literature for explaining large fluctuations at the roof corners.

• International Journal of Concrete Structures and Materials
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• 제2권2호
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• pp.123-136
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• 2008

A new plastic-damage constitutive model applicable to lightweight concrete (LWC) and normal weight concrete (NWC) is proposed in this paper based on both continuum damage mechanics and plasticity theories. Two damage variables are used to represent tensile and compressive damage independently. The effective stress is computed in the Drucker-Prager multi-surface plasticity framework. The stress is then computed by multiplication of the damaged part and the effective part. The proposed model is coded as a user material subroutine and incorporated in a finite element analysis software. The constitutive integration algorithm is implemented by adopting the operator split involving elastic predictor, plastic corrector and damage corrector. The numerical study shows that the algorithm is efficient and robust in the finite element analysis. Experimental investigation is conducted to verify the proposed model involving both static and dynamic tests. The very good agreement between the numerical results and experimental results demonstrates the capability of the proposed model to capture the behaviors of LWC and NWC structures for static and impact loading.

• 대한기계학회논문집A
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• 제21권10호
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• pp.1683-1693
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• 1997

In this paper, a new nonlinear dynamic model is derived for a 2-dimensional overhead crane based on a new definition of 2-degree-of-freedom swing angle, and a new anti-swing control law is proposed for the crane. The dynamic model and control law take simultaneous travel and traverse motions of the crane into consideration. The model is first linearized for small motions of the crane load about the vertical stable equilibrium. Then the model becomes decoupled and symmetric with respect to the travel and traverse axes of the crane. From this result, a decoupled anti-swing control law is proposed based on the linearized model via the loop shaping and root locus methods. This decoupled method guarantees not only fast damping of load-swing but also zero steady state position error with optimal transient response for the 2-dimensional motion of the crane. Finally, the proposed control method is evaluated by controlling the simultaneous travel and traverse motions of a 2-dimensional prototype overhead crane. The effectiveness of the proposed control method is then proven by the experimental results.

• Smart Structures and Systems
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• 제21권5호
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 정보교육학회논문지
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• 제15권2호
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• pp.265-275
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• 2011

이 연구는 초 중등 교원을 대상으로 혁신확산모형에서 제안하는 혁신 속성 변인들을 기반으로 디지털교과서의 수용을 결정하는 요인을 규명하고, 정보기술수용모형(TAM)을 보다 확장된 모형으로 제안하고 검증하고자 수행되었다. 이를 위해 관찰가능성, 적합성, 주관적 규범을 외생변인으로, 유용성과 사용용이성, 사용의도를 내생변인으로 설정하는 연구모형을 제안하였다. 연구결과 관찰가능성, 적합성, 주관적 규범은 교사의 디지털교과서 사용의도에 영향을 미치는 주요한 외재적 변인이며, 본 연구에서 제안한 확장된 정보기술수용모형은 적합함을 검증하였다.