作者：
MALKOFF, DBMOY, MCWILLIAMS, HLDr. Donald B. Malkoff majored in physics as an undergraduate at Harvard University. He received an M.D. degree from the University of Pittsburgh School of Medicine in 1960. This was followed by an internship and residency in neurology at University Hospital in Ann Arbor
Michigan. He spent several years at the National Institutes of Health engaged in gerontology research has practiced and taught clinical neurology and in 1983 received an M.S. degree in computer science at the University of California San Diego. Currently Dr. Malkoff is employed by the Navy Personnel Research and Development Center in San Diego California where he is senior investigator in a human factor/computer display-and-control project involving the DDG-51 gas turbine propulsion unit. He is a member of the American Academy of Neurology the Society for Neuroscience the American Association for Artificial Intelligence and the Association for Computing Machinery. Dr. Malkoff is certified by the American Board of Psychiatry and Neurology has taught computer science at UCSD and published in several research areas including magnetoencephalography and electron microscopy. His basic interests are in the areas of artificial intelligence and learning expert systems particularly as they apply to the problems of fault-detection and control. Dr. Melvyn C. Moy received his undergraduate training in mathematics and chemistry at the University of Texas
Austin. He studied experimental psychology at the University of Wisconsin Madison receiving his M.S. in 1970 and Ph.D. in 1972. He served as an assistant professor at the University of South Dakota where he taught experimental design and methodology for a year before joining the Navy Personnel Research and Development Center in 1973. His work and research since then spans across many application areas such as the development of manpower planning models for the Navy the design of operational decision aids the human engineering of interactive large-scale war gaming systems and the evaluation o
The ship fire main has undergone considerable development throughout the past 2,000 years, resulting in a system that is critical both for normal ship function and for ship survivability in emergencies. Because of its...
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The ship fire main has undergone considerable development throughout the past 2,000 years, resulting in a system that is critical both for normal ship function and for ship survivability in emergencies. Because of its complexity, the modern firemain system is highly vulnerable to malfunction and to damage during combat. Firemain fault detection and fault recovery are currently conducted manually by damage control teams. The advantages and disadvantages of this method are discussed, and alternative methods of fault detection and recovery are explored. An interactive computer program is introduced which uses central control over remotely situated valves to facilitate fault detection and recovery, significantly reducing recovery-time and manpower requirements. These reductions may result in savings of lives, ship systems, and ships themselves. The computer program is based upon an algorithm which is, in effect, a prescription that can be followed manually by the operator or be completely automated. The color graphic display which is used for monitoring can also be utilized for the training of damage control operators or for the evaluation of other algorithms for firemain control. Alternative firemain hardware and configurations could lead to even more efficient methods of fault detection and recovery as well as improved firemain water supply management in general.
This book constitutes the thoroughly refereed post-workshop-proceedings of the 4th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2011, held in Beijing, China, in September 2011. The 1...
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ISBN:
(数字)9783642293641
ISBN:
(纸本)9783642293634
This book constitutes the thoroughly refereed post-workshop-proceedings of the 4th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2011, held in Beijing, China, in September 2011. The 13 revised full papers presented were carefully selected during a second round of reviewing and improvement from numerous original submissions. Intended to give a snapshot of the state-of-the-art research in the field of camera based document analysis and recognition, the papers are organized in topical sections on text detection and recognition in scene images, camera-based systems, and datasets and evaluation.
Like other global mass gatherings, religious pilgrimages, such as Hajj, Arba’een, and the Hindu festival Kumbh Mela, attract millions of pilgrims to gather at specific holy sites on specific dates. During disease pan...
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Like other global mass gatherings, religious pilgrimages, such as Hajj, Arba’een, and the Hindu festival Kumbh Mela, attract millions of pilgrims to gather at specific holy sites on specific dates. During disease pandemics, mass gatherings can become super spreader events, causing exponential growth of infections in multiple regions. Epidemic modeling approaches can be valuable tools for studying the impact of mass gatherings on global health during disease outbreaks. To assess the use of epidemic models at religious pilgrimages, we compile published studies that proposed epidemic models at mass religious gatherings. A review of existing epidemic models at various religious gatherings highlights the role of epidemic modeling approaches in assessing the implications of religious pilgrimages on disease pandemics. All the articles surveyed showed a link between hosting religious gatherings and an increase in the number of cases of the simulated epidemic. In addition, we found that the SEIR mathematical model was the most common type developed with variations in some of the retrieved papers. The results reported in these studies motivate further investigation of the role of epidemic modeling and simulation in estimating the size and geographic scale of infections while hosting religious gatherings. Finally, we believe that this survey paper draws attention to the application of epidemic models in the advanced planning of recurrent religious pilgrimages, as it is not feasible to cancel, suspend, or reallocate these pilgrimages. These epidemic models can provide a baseline for policymakers to determine which control measures should be implemented and when.
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