• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.114-121
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• 2007

Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkage-disequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.95-102
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• 2020

For the purpose of developing a PE fiber-reinforced highly ductile cementitious composite having high tensile strain capacity more than 2% under the condition of containing aggregates with large particle size, this study investigated the tensile behavior of composites according to the particle size and distribution of aggregates in the composite. Compared with the mixture containing silica sand of which particle size is less than 0.6 mm, mixtures containing river sand and/or gravel with the maximum particle size of 2.36 mm, 4.75 mm, 5.6 mm, 6.7 mm were considered in the experimental design. The particle size distributions of aggregates were adjusted for the optimized distribution curves obtained from modified A&A model by blending different sizes of aggregates. All the mixtures presented clear strain-hardening behavior in the direct tensile tests. The mixtures with the blended aggregates to meet the optimum curves of aggregate size distributions showed higher tensile strain capacity than the mixture with silica sand. It was also found that the tensile strain capacity was improved as the maximum size of aggregate increased which resulted in wider particle size distribution. The mixtures with the maximum size of 5.6 mm and 6.7 mm presented very high tensile strain capacities of 4.83% and 5.89%, respectively. This study demonstrated that it was possible to use coarse aggregates in manufacturing highly ductile fiber-reinforced cementitous composite by adjusting the particle size distribution.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.04a
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• pp.77-78
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• 2008

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.669-672
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• 2009

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.181-182
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• 2008

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1999.04a
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• pp.97-98
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• 1999

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.224.2-224.2
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• 2003

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.377-378
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• 2000

에어로졸 입자들의 물리적, 화학적 성질 및 인체에 미치는 영향 등은 입자의 크기분포에 밀접하게 관련되어 있다. 에어로졸 입자의 응집현상은 입자의 크기분포 변화를 일으키는 주된 메커니즘의 하나로서 여러 응용 및 기초 연구에 필수적으로 사용된다. 응집에 의한 입자크기분포의 변화는 다음 식으로 나타낼 수 있다. (중략)

• Journal of the Korean Magnetics Society
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• v.16 no.3
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• pp.163-167
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• 2006

Ultrasonic irradiation in a solution during the chemical reaction may accelerate the rate of the reaction and the crystallization at low temperature. We have synthesized nanometer sized magnetite particles using coprecipitation method, sonochemical method without surfactant, and sonochemical method with surfactant, in order to investigate the effect of ultrasonic irradiation and surfactant on the coprecipitates of metal ions. The size of the magnetite nanoparticles prepared by coprecipitation method, and sonochemical method without surfactant showed broad distributions. But we got uniform nanoparticles using a sonochemical method with oleic acid. The average size of the particles can be controlled by the ratio $R=[H_2O]/[surfactant]$. The size of the magnetite nanoparticles prepared by this method showed narrow distributions. We have characterized the nanoparticles using an X-ray diffraction (XRD), a superconducting quantum interference device (SQUID), and atomic force microscope (AFM). The size and distribution of the magnetite nanoparticles were measured by dynamic light scattering (DLS) method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.