• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.8-15
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• 2018

New methodology for probabilistic reliability based grid expansion planning of HVDC in power system including Wind Turbine Generators(WTG) is developed in this paper. This problem is focused on scenario based optimal selection technique to decide best connection bus of new transmission lines of HVDC in view point of adequacy reliability in power system including WTG. This requires two kinds of modeling and simulation for reliability evaluation. One is how is reliability evaluation model and simulation of WTG. Another is to develop a failure model of HVDC. First, reliability evaluation of power system including WTG needs multi-state simulation methodology because of intermittent characteristics of wind speed and nonlinear generation curve of WTG. Reliability methodology of power system including WTG has already been developed with considering multi-state simulation over the years in the world. The multi-state model already developed by authors is used for WTG reliability simulation in this study. Second, the power system including HVDC includes AC/DC converter and DC/AC inverter substation. The substation is composed of a lot of thyristor devices, in which devices have possibility of failure occurrence in potential. Failure model of AC/DC converter and DC/AC inverter substation in order to simulate HVDC reliability is newly proposed in this paper. Furthermore, this problem should be formulated in hierarchical level II(HLII) reliability evaluation because of best bus choice problem for connecting new HVDC and transmission lines consideration. HLII reliability simulation technique is not simple but difficult and complex. CmRel program, which is adequacy reliability evaluation program developed by authors, is extended and developed for this study. Using proposed method, new HVDC connected bus point is able to be decided at best reliability level successfully. Methodology proposed in this paper is applied to small sized model power system.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.316-324
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• 2020

This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

• Journal of Korean Library and Information Science Society
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• v.36 no.2
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• pp.49-68
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• 2005

The purpose of this study is to examine the research trends and their experiment results on the applications of the language models for information retrieval. We reviewed the previous studies with the following categories: (1) the first generation of language modeling information retrieval (LMIR) experiments which are mainly focused on comparing the language modeling information retrieval with the traditional retrieval models in their retrieval performance, and (2) the second generation of LMIR experiments which are focused on comparing the expanded language modeling information retrieval with the basic language models in their retrieval performance. Through the analysis of the previous experiments results, we found that (1) language models are outperformed the probabilistic model or vector space model approaches, and (2) the expended language models demonstrated better results than the basic language models in their retrieval performance.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.127_128
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• 2009

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.341-348
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• 1990

This paper describes an algorithm for evaluating the Loss of Load Probability (LOLP) and calculating the production cost for all the generators in the system using Fast Hartley Transform (FHT). It also suggests the deconvolution procedure which is necessary for the generation expansion planning. The FHT is as fast as or faster than the Fast Fourier Transform (FFT) and serves for all the uses such as spectral, digital processing, and convolution to which the FFT is normally applied. The transformed function using FFT has complex numbers. However, the transformed function using FHT has real numbers and the convolution become quite simple. This method has been applied for the IEEE reliability test system and practical size model system. The test results show the effectiveness of the proposed method.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.37-44
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• 2020

In improving laser cutting of optical plastic films for mass production of optoelectronics display units, it is important to understand particle contamination over optical film surface due to fume particle generation and dispersion. This numerical study investigates the effects of downward and upward air flow motions on fume particle dispersion around laser cut line. The simulations employ random particle sampling of up to one million fume particles by probabilistic distributions of particle size, ejection velocity and angle, and fume particle dispersion and surface landing are predicted using Basset-Boussinesq-Oseen model of low Reynolds number flows. The numerical results show that downward air flow scatters fume particles of a certain size range farther away from laser cut line and aggravate surface contamination. However, upward air flow pushes fume particles of this size range back toward laser cut line or sucks them up with rising air motion, thus significantly alleviating surface contamination.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.51-58
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• 2020

Many types of optical plastic films are essential in optoelectronics display unit fabrication and it is important to develop high precision laser cutting methods of optical films with extremely low level of film surface contamination by fume particles. This study investigates the effects of suction and blowing air motions with air flow misalignment in removing fume particles from laser cut line by employing random particle trajectory simulation and probabilistic particle generation model. The computational results show fume particle dispersion behaviors on optical film under suction and blowing air flow conditions. It is found that suction air flow motion is more advantageous to blowing air motion in reducing film surface contamination outside designated target margin from laser cut line. While air flow misalignment adversely affects particle dispersion in blowing air flows, its effects become much more complicated in suction air flows by showing different particle dispersion patterns around laser cut line. It is required to have more careful air flow alignment in fume particle removal under suction air flow conditions.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.1-6
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• 2022

This computational investigation of micro-sized particle dispersion concerns the fume particle contamination over target surface in high-precision laser line machining process of semiconductor and display device materials. Employing the random sampling based on probabilistic fume particle generation distributions, the effects of sphericity for nonspherical fume particles are analyzed for the fume particle dispersion and contamination near the laser machining line. The drag coefficient correlation for nonspherical particles in a low Reynolds number regime is selected and utilized for particle trajectory simulations after drag model validation. When compared to the corresponding results by the assumption of spherical fume particles, the sphericity of nonspherical fume particles show much less dispersion and contamination characteristics and it also significantly affects the particle removal rate in a suction air flow patterns.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.45-52
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• 2024

This paper introduces an approach to enhance the performance of magnetic manipulation systems for microrobot actuation. A variety of eight-electromagnet configurations have been proposed to date. The previous study revealed that achieving 5 degrees of freedom (5-DOF) control necessitates at least eight electromagnets without encountering workspace singularities. But so far, the research considering the influence of iron cores embedded in electromagnets has not been conducted. This paper offers a novel approach to optimizing electromagnet configurations that effectively consider the influence of iron cores. The proposed methodology integrates probabilistic optimization with finite element methods (FEM), using Bayesian Optimization (BO). The Bayesian optimization aims to optimize the worst-case magnetic force generation for enhancing the performance of magnetic manipulation system. The proposed simulation-based model achieves approximately 20% improvement compared to previous systems in terms of actuation performance. This study has the potential for enhancing magnetic manipulation systems for microrobot control, particularly in medical and microscale technology applications.

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.683-688
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• 2006

We have developed a program for generating shotgun data sets from known genome sequences. Generation of synthetic data sets by computer program is a useful alternative to real data to which students and researchers have limited access. Uniformly-distributed-sampling clones that were adopted by previous programs cannot account for the real situation where sampled reads tend to come from particular regions of the target genome. To reflect such situation, a probabilistic model for biased sampling distribution was developed by using an experimental data set derived from a microbial genome project. Among the experimental parameters tested (varied fragment or read lengths, chimerism, and sequencing error), the extent of sequencing error was the most critical factor that hampered sequence assembly. We propose that an optimum sequencing strategy employing different insert lengths and redundancy can be established by performing a variety of simulations.