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병원 전 심정지 환자의 동반자에 대한 면담 설문을 통한 심폐소생술에 대한 태도 연구
오석남,신태건,홍종근,송근정,심민섭 대한응급의학회 2010 대한응급의학회지 Vol.21 No.5
Purpose: The purpose of this study was to provide an appropriate direction for cardiopulmonary resuscitation (CPR) education for laypersons by analyzing the status of CPR training, bystander CPR, and the prognosis of patients with out-of-hospital cardiac arrest (OHCA). Methods: Data were obtained prospectively by interviews of bystanders who arrived with an OHCA patient between Jan 1, 2009 and Mar 31, 2010. Variables analyzed included CPR education, bystander CPR, and prognosis of OHCA patients. Multivariate logistic regression analysis was performed to identify independent factors for bystander CPR. Results: Nineteen (33.9%) of 56 bystanders (male: 48.2%,age: 48.98±16.87) conducted CPR on an individual having an OHCA. Fourteen (25.0%) of the 56 had CPR education. Of the 14, 8 (57.1%) performed CPR. Among those who did not have any CPR training (p<0.05) 11 (26.2%) conducted it. In a multivariate regression analysis, younger age was a significant predictor for bystander CPR. Previous CPR training and male also appeared to be potential factors although their predictive value was not statistically significant. Conclusion: The rates of CPR training experience and bystander CPR were relatively low in this study. Younger age, male and previous CPR training were associated with the rate of bystander CPR, which is known as a critical factor influencing survival of OHCA patients. In order to increase survival of OHCA patients by raising the bystander CPR rate, systemic CPR education for laypersons should be established.
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분산메모리 병렬 컴퓨터에서 데이타 배분에 무관한 행렬 곱셈 알고리즘
최재영(Jaeyoung Choi),김명호(Myungho Kim),오석남(Seoknam Oh),황석찬(Seogchan Hwang) 한국정보과학회 1998 정보과학회논문지 : 시스템 및 이론 Vol.25 No.1
분산메모리를 가진 병렬 컴퓨터에서 아주 빠르고 확장성이 우수한 행렬 곱셈 알고리즘을 제안한다. 그 성능이 데이타 배분에 무관하므로 그 알고리즘을 DlMMA (Distribution-Independent Matrix Multiplication Algorithm)라고 명하였다. 이 새로운 알고리즘은 두가지의 새로운 개념에 근거하였다. 각 프로세서에서 계산과 통신을 효과적으로 중칩시키기 위하여 개선된 파이프라인 통신법을 사용하였고, 행렬 블록의 크기가 아주 작거나 혹은 아주 클 때에도 항상 BLAS의 최대 성능을 얻을 수 있도록 하기 위해 LCM 개념을 사용하였다. DIMMA는 Intel Paragon 컴퓨터에서 구현되었으며 SUMMA 와 비교 · 분석되었다. We present a fast and scalable matrix multiplication algorithm on distributed memory concurrent computers, whose performance is independent of data distribution on processors, and call it DIMMA (Distribution-Independent Matrix Multiplication Algorithm) The algorithm is based on two new ideas; it uses a modified pipelined communication scheme to overlap computation and communication effectively, and exploits the LCM block concept to obtain the maximum performance of the sequential BLAS routine in each processor when the block size is very small as well as very large. The algorithm is implemented and compared with SUMMA on the Intel Paragon computer.
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