• 융합보안논문지
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• 제19권3호
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• pp.61-70
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• 2019

최근 엄청난 계산 능력을 보여주는 양자 컴퓨터와 정보 접근성이 높고 비용이 낮은 클라우드 컴퓨팅에 대한 개발이 활발하게 이루어지고 있다. 이러한 양자 컴퓨터의 경우 양자오류정정부호가 필수적이며, 클라우드 컴퓨팅의 경우 보안성 및 계산성을 확보하기 위해 동형암호가 사용될 수 있다. 각각 다른 목적을 위해 사용되는 이 두 기법은 서로 비슷한 가정을 바탕으로 하고 있어, 양자오류정정부호를 기반으로 동형암호를 구성하는 연구들이 진행되어왔다. 따라서 본 논문에서는 일반적인 양자오류정정부호를 변형하여 동형암호적 양자정보처리가 가능한 기법을 제시한다. 기존의 양자오류정정부호를 이용한 동형암호기법의 경우 부호를 사용하였지만 오류정정 능력이 전혀 없는데 반해, 제시한 양자오류정정부호 기법을 사용하면 동형암호적 양자정보처리가 가능하면서도, 동시에 양자오류정정부호 본연의 기능인 양자정보의 연산, 저장 중의 오류를 정정할 수 있는 장점이 존재한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.69-70
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• 2012

• 대한기계학회논문집B
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• 제22권1호
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• pp.104-112
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• 1998

The mold filling process has been a central issue in the development of numerical methods to solve the casting processes. A mold filling which is inherently transient free surface fluid flow, is important because the quality of casting highly depends on such phenomenon, Most of the existing numerical schemes to solve mold filling process have severe limitations in time step restrictions or Courant criteria since explicit time integration is used. Therefore, a large computation time is required to analyze casting processes. In this study, the well known SOLA-VOF method has been modified implicitly to simulate the mold filling process. Solutions to example filling problems show that the proposed method is more efficient in computation time than the original SOLA -VOF method.

• Journal of the Korean Statistical Society
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• 제36권2호
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• pp.321-333
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• 2007

In the proportional hazard model with the beta process prior, the posterior computation with the discrete approximation is considered. The time period of interest is partitioned by small intervals. On each partitioning interval, the likelihood is approximated by that of a binomial experiment and the beta process prior is by a beta distribution. Consequently, the posterior is approximated by that of many independent binomial model with beta priors. The analysis of the leukemia remission data is given as an example. It is illustrated that the length of the partitioning interval affects the posterior and one needs to be careful in choosing it.

• Communications for Statistical Applications and Methods
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• 제24권5호
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• pp.457-480
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• 2017

We develop a random partition procedure based on a Dirichlet process prior with Laplace distribution. Gibbs sampling of a Laplace mixture of linear mixed regressions with a Dirichlet process is implemented as a random partition model when the number of clusters is unknown. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities, unlike its counterparts. A full Gibbs-sampling algorithm is developed for an efficient Markov chain Monte Carlo posterior computation. The proposed method is illustrated with simulated data and one real data of the energy efficiency of Tsanas and Xifara (Energy and Buildings, 49, 560-567, 2012).

• 대한전기학회논문지:시스템및제어부문D
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• 제53권4호
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

• 대한기계학회논문집A
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• 제24권3호
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• pp.769-776
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• 2000

RP(Rapid Prototyping) technology is gaining its popularity in building a prototype in all industries. SLS(Slective Laser Sintering) is one of RP technologies, which is focused on tooling processes as well as three dimension solid model. There are several factors, the length and the cross-sectional area of a part, that have an effect on build setup in SLS process. In this paper, the computation on geometrical relationship is used to slice STL file and to estimate these factors. Based on these values, the build setup parameters such as the heating temperature, the laser power, and the powder cartridge feed rate are determined by neural network approaches. The test results show that the computation time is saved and the neural network approach is able to apply to get the optimal parameters of build process within an acceptable error rate.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권6호
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• pp.771-780
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• 2016

Detecting a set of longest paths is one of the crucial steps in static timing analysis and optimization. Recently, the process variation during manufacturing affects performance of the circuit design due to nanometer feature size. Measuring the performance of a circuit prior to its fabrication requires a considerable amount of computation time because it requires multi-corner and multi-mode analysis with process variations. An efficient algorithm of detecting the K-most critical paths in multi-corner multi-mode static timing analysis (MCMM STA) is proposed in this paper. The ISCAS'85 benchmark suite using a 32 nm technology is applied to verify the proposed method. The proposed K-most critical paths detection method reduces about 25% of computation time on average.

• 소성∙가공
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• 제8권3호
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• pp.284-293
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• 1999

The rigid-plastic finite element analysis requires a large amount of computation time due to its non-linearity. For economic computation, mismatching refinement, and efficient domain decomposition method with different mesh density for each sub domain, is developed. A modified velocity alternating scheme for the interface treatment is proposed in order to obtain good convergence and accuracy. As a numerical example, the axisymmetric extrusion process is analyzed. The results are discussed for the various velocity update schemes form the viewpoint of convergence and accuracy. The three-dimen-sional extrusion process with rectangular section is analyzed in order to verify the effectiveness of the proposed method. Comparing the results with those of the conventional method of full region analysis, the accuracy and the computational efficiency of the proposed method are then discussed.

• 한국군사과학기술학회지
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• 제2권2호
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• pp.131-139
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• 1999

An easy and efficient method is proposed for a computation of reliability of preprocessing filters in the fire control system when the sensor data are frequently unreliable depending on the operation environment. It computes state transition probability matrix after modeling filter states as a Markov process, and computing false alarm and detection probability of each filter state under the given sensor failure probability. It shows that two important indices such as distributed state probability and error variance can be derived easily for a reliability assessment of the given sensor fusion system.