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22q11.2 결손 증후군 (DiGeorge 증후군)의 산전 진단 2예
박성균 ( Sung Kyun Park ),전균호 ( Gyun Ho Jeon ),노현진 ( Hyun Jin Roh ),안송미 ( Song Mi Ahn ),김선권 ( Sun Kwon Kim ),심재윤 ( Jae Yoon Shim ),김성훈 ( Sung Hoon Kim ),원혜성 ( Hye Sung Won ),이필량 ( Pil Ryang Lee ),김암 ( Ah 대한산부인과학회 2004 Obstetrics & Gynecology Science Vol.47 No.9
Before the exact location of its chromosomal abnormality was identified, 22q11.2 deletion syndrome was described as many different names depending on its presenting clinical features. Patients with this syndrome have a wide range of findings such as cardi
관리도의 군간 , 군내 분산과 실험계획의 일원배치 분산의 관련성 해석
박성균(Sung Gyun Park),김영균(Young Gyun Kim) 한국품질경영학회 2001 품질혁신 Vol.2 No.1
It has often been said that adequate quality control begins with control of fundamental data. Control chart, one of many quality control tools, has been developed since it was developed firstly by W. A. Shewhart in 1924. Control chart`s analysis of between-sample and within-sample variability plays an important role in manufacturing and process control, and these well-defined standard deviations can be based on calculation of process capability and sigma level, and so on. In this study, it was noticed to fact that data between the variability of x bar-s control charts and one-way analysis of variance have the same data structure, and between-sample and within-sample standard deviation were investigated. As the result, the related equation was derived as follows: s_0^2×(N-1)=S_w^2×(m^(-)-1)×l+s_b^2×(l-1)×m^(-) where, s_(0)^(2)=overall variance S_(w)^(2)=within-sample variance s_(b)^(2)=between-sample variance l=number of between-sample group m^(-)=average number of within-sample Also, x bar-s control charts, one-way analysis of variance, and process capability analysis were carried out by a series of sample data such as within sample`s number = constant and within sample`s number ≠ constant using statistical software(Minitab), and the above-mentioned equation was verified by comparing standard deviations shown in quality control tools. Moreover, overall standard deviation can be simply calculated by utilizing between-sample standard deviation from x bar chart and within-sample standard deviation from s chart with the help of the above equation.
계량형 관리도의 관리규격 계산에 사용되는 여러 계수값 사이의 관계
박성균 ( Sung Gyun Park ),김영균 ( Young Gyun Kim ) 한국품질경영학회 2002 품질경영학회지 Vol.30 No.4
There are many different factors used in calculating control limits of control chart for variable data. Specially these factors are divided into two groups such as no given standard and given standard(namely, for analysis and management), but many kind of factors give rise to confusion. Therefore, It is necessary to manifest relationships among factors for easy application regardless of subgroup size. Many SQC textbooks show us plainly these factors, but do not have enough for adequate explanation of relationships among factors. Besides, notation of these factors of SQC textbook isn`t coincide with another one, so necessity to the coincidence for the notation of the factors is highlighted during my work recently. In this study, the close examination about relationships among various factors (A-A3, B3-B6, D1-D4, C4, d2, d3 etc) was carried out. Spread sheet results are presented for getting factors according to subgroup size, by grouping as the case of no given standard and given standard. How are these factors to be applied in statistical package (ex, Minitab) have been analyzed using a series of sample data.
마이크로셀룰라 이동 무선 시스템에서 Outage 확률을 이용한 라이시안 페이딩과 로그노말 섀도우잉 영향에 관한 분석
안치훈,김남,박성균,Ahn, Chy-Hun,Kim, Nam,Park, Sung-Gyun 한국전자파학회 1998 한국전자파학회논문지 Vol.9 No.1
마이크로셀룰라 이동 무선 시스템의 전파환경은 레일라이, 라이시안 페이딩과 경로손실, 로그노말 새도우잉 동의 영향을 받는다. 이러한 복합적 환경에서 L개의 라이시안 간섭 사이에서 수신된 라이시안 신호와 로그노말 새도우영의 영향을 고려하여 재사용거리와 cluster 사이즈, 신호대 간섭의 전력비, 임계비(protection ratio) RI 둥 여러 파라미터에 대한 특성을 outage 확률을 이용하여 분석하였다. 또한 본 논문에서 이용한 outage 확률로 레일라이 신호와 단일 라이시안 간섭, 라이시안 신호와 레일라이 간섭, 라이시안 신호와 라이시안 간섭 둥에 대해 연구하였다. 이론 전개와 시뮬레이션 결과를 통해 로그노말 새도우드 라이시안 채널의 특성을 효과적으로 분석하였다. The propagation environment is effected by Rayleigh fading, Rician fading, path loss and lognormal shadowing in microcellular mobile radio system. In these surroundings we analysed the performance on received Rician signals among L Rician interferers and the characteristics of lognormal shadowing for various parameters such as reuse distance, cluster size, signal to interference power ratio and protection ratio using outage probability. We also studied various channels Rayleigh signal and Rician interferer, Rician signal and Rayleigh interferer, Rician signal and Rician interferer and so on using outage probability. The theoretical extention and computer simulation effectively analysed the characteristic of lognormal shadowed Rician channel.