• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• Smart Structures and Systems
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• v.20 no.4
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• pp.397-413
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• 2017

Precast concrete (PC) members are currently being employed for general construction or partial replacement to reduce construction period. As assembly work in PC construction requires connecting PC members accurately, measuring the 6-DOF (degree of freedom) relative displacement is essential. Multiple planar markers and camera-based displacement measurement systems can monitor the 6-DOF relative displacement of PC members. Conventional methods, such as direct linear transformation (DLT) for homography estimation, which are applied to calculate the 6-DOF relative displacement between the camera and marker, have several major problems. One of the problems is that when the marker is partially hidden, the DLT method cannot be applied to calculate the 6-DOF relative displacement. In addition, when the images of markers are blurred, error increases with the DLT method which is employed for its estimation. To solve these problems, a hybrid method, which combines the advantages of the DLT and MCL (Monte Carlo localization) methods, is proposed. The method evaluates the 6-DOF relative displacement more accurately compared to when either the DLT or MCL is used alone. Each subsystem captures an image of a marker and extracts its subpixel coordinates, and then the data are transferred to a main system via a wireless communication network. In the main system, the data from each subsystem are used for 3D visualization. Thereafter, the real-time movements of the PC members are displayed on a tablet PC. To prove the feasibility, the hybrid method is compared with the DLT method and MCL in real experiments.

• ETRI Journal
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• v.40 no.3
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• pp.291-302
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• 2018

The deployment of an incremental hybrid decode-amplify and forward relaying scheme is a promising and superior solution for cellular networks to meet ever-growing network traffic demands. However, the selection of a suitable relaying protocol based on the signal-to-noise ratio threshold is important in realizing an improved quality of service. In this paper, an incremental hybrid relaying protocol is proposed using polar codes. The proposed protocol achieves a better performance than existing turbo codes in terms of capacity. Simulation results show that the polar codes through an incremental hybrid decode-amplify-and-forward relay can provide a 38% gain when ${\gamma}_{th(1)}$ and ${\gamma}_{th(2)}$ are optimal. Further, the channel capacity is improved to 17.5 b/s/Hz and 23 b/s/Hz for $2{\times}2$ MIMO and $4{\times}4$ MIMO systems, respectively. Monte Carlo simulations are carried out to achieve the optimal solution.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.703-709
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• 2012

In this paper, we propose a hybrid decode-amplify-forward incremental cooperative diversity protocol using SNR-based relay selection. In the proposed protocol, whenever destination unsuccessfully receives the source's signal, one of relays that exploit hybrid decode-amplify-forward technique is chosen to retransmit the signal. We derive approximate closed-form expressions of outage probability and average channel capacity. Monte-Carlo simulations are presented to verify the theoretical results and compare the performance of the proposed protocol with the direct transmission protocol and conventional incremental relaying protocols.

• ETRI Journal
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• v.37 no.3
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• pp.533-540
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• 2015

In wireless localization, several linear closed-form solution (LCS) methods have been investigated as a direct result of the drawbacks that plague the existing iterative methods, such as the local minimum problem and heavy computational burden. Among the known LCS methods, both the direct solution method and the difference of squared range measurements method are considered in this paper. These LCS methods do not have any of the aforementioned problems that occur in the existing iterative methods. However, each LCS method does have its own individual error property. In this paper, a hybrid LCS method is presented to reduce these errors. The hybrid LCS method integrates the two aforementioned LCS methods by using two check points that give important information on the probability of occurrence of each LCS's individual error. The results of several Monte Carlo simulations show that the proposed method has a good performance. The solutions provided by the proposed method are accurate and reliable. The solutions do not have serious errors such as those that occur in the conventional standalone LCS and iterative methods.

• Current Optics and Photonics
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• v.3 no.5
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• pp.365-373
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• 2019

This paper investigates the performance of a hybrid single input multiple output radio frequency/free-space optics (SIMO-RF/FSO) communication system. Each SIMO-RF link is modeled as an independent and identically distributed (i.i.d.) Rayleigh distribution, while the FSO link follows a generalized $M{\acute{a}}laga$ (M) distribution. Considering the fixed gain amplify-and-forward (AF) relay and misalignment errors, novel expressions for the outage probability (OP), average bit error rate (ABER) and average capacity are derived. Numerical results show that atmospheric turbulence and misalignment errors can seriously impair the system performance, and the hybrid RF/FSO communication system using SIMO-RF links can greatly improve system performance. We also analyze system performance under different types of modulation schemes. Numerical results are verified by Monte Carlo simulations.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.209-209
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• 1999

현재 magnetron sputter는 반도체, LCD 등을 포함하는 microelectronics 산업에서 박막형성을 위한 주요 장비로 널리 쓰이고 있으며, 소자의 고집적화 및 대형화 추세에 따라 그 이용가치는 더욱 증대되고 있다. 본 연구엣는 TFT-LCD용 Color Filter 제조시 ITO박막형성을 위해 사용하는 magnetron sputter 내부의 플라즈마 분포 및 ion kinetic energy에 대한 해석을 실시하였으며, ITO target의 erosion 형상의 원인을 실험결과와 비교하였다. Magnetron sputtering은 target에 가해지는 bias 전압(DC 혹은 RF)에 의해 target과 shield 혹은 target과 substrate 사이에서 생성될 수 잇는 플라즈마를 target 및 부분에 붙어있는 영구자석을 이용하여 target 근처에 집중시키고, target 표면과 플라즈마 사이의 전위차에 의해 가속된 이온들이 target 표면과 충돌하여 이차 전자방출을 일으킴과 동시에 target 표면에서 sputtering을 일으키고, 이들 sputtered 된 중성의 atom 들이 substrate로 날아가 박막을 형성하는 원리로 작동된다. 이때 target에서 방출되는 이차전자들은 영구자석에 의한 자기장 효과에 의해 target 근처에 갇히게 되어 중성 기체분자들과 이온화반응을 통해 플라즈마를 유지하고 그 밀도를 높혀주는 역할을 담당하게 된다. 즉 낮은 압력 및 bias 전압에서도 플라즈마 밀도를 높일수 있고 sputtering 공정이 가능한 장점을 가지고 있다. Magnetron sputtering 현상에 대한 시뮬레이션은 크게 magnetron discharge와 sputtering에 대한 해석 두가지로 나누어 볼 수 있는데, sputtering 현상 자체를 수치묘사할 수 있는 정량적인 모델은 아직까지 명확하게 정립되어 있지 않다. 따라서 본 연구에서는 magnetron plasma 자체에 대한 수치해석에 주안점을 두고 아울러 bulk plasma 영역에서 target으로 입사하는 이온들의 입사에너지 및 입사각도 등을 Monte Carlo 방법으로 추적하여 sputtering 현상을 유추해보았다. Sputtering 현상을 살펴보기 위해 magnetron sputter 내 플라즈마 밀도, 전자온도, 특히 target 및 substrate를 충돌하는 이온의 입사에너지 및 입사각 분포등을 계산하는데 hybrid 방법으로 시뮬레이션을 하였다. 즉 ion과 bulk electron에 대해서는 fluid 방식으로 접근하고, 이차전자 운동과 그로 인한 반응관계 및 target으로 입사하는 이온의 에너지와 입사각 분포는 Monte-Carlo 방법으로 처리하였다. 정지기장해석의 경우 상용 S/W인 Vector Fields를 사용하였다. 이를 통해 sputter 내 플라즈마 특성, target으로 입사하는 이온에너지 및 각 분포, 이들이 target erosion 형상에 미치는 영향을 살펴보았다. 또한 이들 결과로부터 간단한 sputtering 모델을 사용하여 target으로부터 sputter된 입자들이 substrate에 부착되는 현상을 Monte-Carlo 방법으로 추적하여 성막특성도 살펴보았다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.73-79
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• 2002

In this paper, two interference suppression schemes (LCCMA, HIC) applied to the MC-CDMA system were proposed. The proposed schemes have advantages that it don't requires the other's spreading code and can be used even in mobile. The proposed HIC combines the proposed interference suppressor with PIC. Simulation is performed in various environments using the Monte Carlo method. Simulation results show that there is 1.4~3 times capacity increase in corresponding simulation environments. Also this scheme can take advantage of path diversity whereas the system using EGC, MRC, and PIC cannot. Therefore, as the number of path increase, a considerable performance improvement can be attained.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2516-2533
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• 2023

Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.