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Pre-earthquake fuzzy logic and neural network based rapid visual screening of buildings
Moseley, V.J.,Dritsos, S.E.,Kolaksis, D.L. Techno-Press 2007 Structural Engineering and Mechanics, An Int'l Jou Vol.27 No.1
When assessing buildings that may collapse during a large earthquake, conventional rapid visual screening procedures generally provide good results when identifying buildings for further investigation. Unfortunately, their accuracy at identify buildings at risk is not so good. In addition, there appears to be little room for improvement. This paper investigates an alternative screening procedure based on fuzzy logic and artificial neural networks. Two databases of buildings damaged during the Athens earthquake of 1999 are used for training purposes. Extremely good results are obtained from one database and not so good results are obtained from the second database. This finding illustrates the importance of specifically collecting data tailored to the requirements of the fuzzy logic based rapid visual screening procedure. In general, results demonstrate that the trained fuzzy logic based rapid visual screening procedure represents a marked improvement when identifying buildings at risk. In particular, when smaller percentages of the buildings with high damage scores are extracted for further investigation, the proposed fuzzy screening procedure becomes more efficient. This paper shows that the proposed procedure has a significant optimisation potential, is worth pursuing and, to this end, a strategy that outlines the future development of the fuzzy logic based rapid visual screening procedure is proposed.
Pre-earthquake fuzzy logic and neural network based rapid visual screening of buildings
V. J. Moseley,S. E. Dritsos 국제구조공학회 2007 Structural Engineering and Mechanics, An Int'l Jou Vol.27 No.1
When assessing buildings that may collapse during a large earthquake, conventional rapid visual screening procedures generally provide good results when identifying buildings for further investigation. Unfortunately, their accuracy at identify buildings at risk is not so good. In addition, there appears to be little room for improvement. This paper investigates an alternative screening procedure based on fuzzy logic and artificial neural networks. Two databases of buildings damaged during the Athens earthquake of 1999 are used for training purposes. Extremely good results are obtained from one database and not so good results are obtained from the second database. This finding illustrates the importance of specifically collecting data tailored to the requirements of the fuzzy logic based rapid visual screening procedure. In general, results demonstrate that the trained fuzzy logic based rapid visual screening procedure represents a marked improvement when identifying buildings at risk. In particular, when smaller percentages of the buildings with high damage scores are extracted for further investigation, the proposed fuzzy screening procedure becomes more efficient. This paper shows that the proposed procedure has a significant optimisation potential, is worth pursuing and, to this end, a strategy that outlines the future development of the fuzzy logic based rapid visual screening procedure is proposed.
송준영,Moon H. Nahm,M. Allen Moseley 대한의학회 2013 Journal of Korean medical science Vol.28 No.1
Streptococcus pneumoniae can asymptomatically colonize the nasopharynx and cause a diverse range of illnesses. This clinical spectrum from colonization to invasive pneumococcal disease (IPD) appears to depend on the pneumococcal capsular serotype rather than the genetic background. According to a literature review, serotypes 1, 4, 5, 7F,8, 12F, 14, 18C, and 19A are more likely to cause IPD. Although serotypes 1 and 19A are the predominant causes of invasive pneumococcal pneumonia, serotype 14 remains one of the most common etiologic agents of non-bacteremic pneumonia in adults, even after 7-valent pneumococcal conjugate vaccine (PCV7) introduction. Serotypes 1, 3, and 19A pneumococci are likely to cause empyema and hemolytic uremic syndrome. Serotype 1pneumococcal meningitis is prevalent in the African meningitis belt, with a high fatality rate. In contrast to the capsule type, genotype is more closely associated with antibiotic resistance. CC320/271 strains expressing serotype 19A are multidrug-resistant (MDR) and prevalent worldwide in the era of PCV7. Several clones of MDR serotype 6C pneumococci emerged, and a MDR 6D clone (ST282) has been identified in Korea. Since the pneumococcal epidemiology of capsule types varies geographically and temporally, a nationwide serosurveillance system is vital to establishing appropriate vaccination strategies for each country.