Convolutional neural networks show outstanding results in a variety of computer vision ***, a neural network architecture design usually faces a trade-off between model performance and computational/memory complexity....
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Objective: To identify the leading predictors of co-occurring cardiovascular or gastrointestinal disorders (CV-GID) in a real-world cohort of elderly with osteoarthritis (OA). Method: An observational retrospective co...
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Background: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reac...
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Background: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences. Objective: This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese. Methods: We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19–related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures. Results: We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak’s seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior. Conclusions: Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxie
作者：
Wu, BCYoung, GSSchmidt, WChoppella, KDr. Bi-Chu Wu:received a PhD in Mechanical Engineering from the University of Maryland
College Park in 1991. She has worked on projects involving naval architecture design optimization solid mechanics and database development. Presently a senwr engineer with Angle Incorporated Dr Wu's research interests are in design optimization and fuzzy logic applications. Dr. Gin-Shu Young:
a senior engineer with Angle Incorporated holds a PhD in Mechanical Engineering from the University of Maryland College Park. As a guest researcher with National Institute of Standards and Technologies from 1990 to 1993 he worked on vision-based navigation for autonomous vehicles. His experience also includes applications of optimization fuzzy logic neural network and genetic algorithm methods to engineering system design Mr. William Schmidt:co-founded Angle Incorporated in 1990 and has served as Vice PresidentlChiefScientist during this tame. He holds a B.Sc. in Applied Science from the Naval Acadt?my and an M.Sc. in Physics from the Naval Post Graduate School. He has cner 20 years experience in technical leadership
material and personnel management. He has led the application of computer aided design (CAD) and Product Model Information Exchange to the shipbuilding industry. His experience also includes leading the amlication of model based operational analysis to support the Live Fire Test Program for DDG 51 Class Destroyers. Mr. Krishna M. Choppella:is a Sofware Engineer at Eidea Laboratories
Incotporated where he works on componentbased distributed enterpvise frameworks. He has been involved in creating data analysis tools for the US Nay by integrating CAD modeis databases and graphical front ends. His work in the Masters degree program in Mechanical Engineering at the University of Texas at Austin was in di0ddase.r spectroscopy of combustion products in porous-matri burners. He received his Bachelors degree in Electrical Engineering in India. He was a Research Associate at the Centre for Laser Technology and Project Engi
Ship design is often multidisciplinary involving several design elements with various types of objectives and constraints (O/C) some easily described as mathematical formulas, others better modeled as descriptive asse...
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Ship design is often multidisciplinary involving several design elements with various types of objectives and constraints (O/C) some easily described as mathematical formulas, others better modeled as descriptive assertions. This paper describes a method based on fuzzy functions and an integrated performance index to model O/C using descriptive assertions to be used with mathematical formulas in optimization. Another issue addressed in this paper concerns the coordination of design elements when sequentially coupled, that is, when one leads the other and the performance of the follower depends greatly on the design of the leader. Based on neuro-fuzzy techniques, the method described here coordinates and optimizes sequentially coupled elements. The two methods are applied to machinery arrangement (MA) and pipe routing (PR). Preliminary models for optimization of MA and PR are described considering convenience, producibility: engine room size, interference and location as factors in the O/C set. Some test results from MA/PR applications are presented and discussed. The methods are generic and can be extended to other elements in ship design. They are mutually independent and may be used separately Two advantages of their use are an improvement in overall performance and a reduction in the need for redesign of elements.
The Shipboard data Multiplex System (SDMS) is a general purpose information transfer system directed toward fulfilling the internal data Intercommunication requirements of a variety of naval combatant ships and submar...
The Shipboard data Multiplex System (SDMS) is a general purpose information transfer system directed toward fulfilling the internal data Intercommunication requirements of a variety of naval combatant ships and submarines in the 1980–1990 time frame. The need for a modern data transfer system of the size and capability of SDMS has been increase in unison with the sophistication of shipboard electronic equipment and the associated magnitude of equipment-to-equipment signal traffic. Instead of the miles of unique cabling that must be specifically designed for each ship, SDMS will meet information transfer needs with general-purpose multiplex cable that will be Installed according to a standard plan that does not vary with changes to the ship's electronics suite. Perhaps the greatest impact of SDMS will be the decoupling of ship subsystems from each other and from the ship. Standard multiplex interfaces will avoid the cost and delay of modifying subsystems to make them compatible. The ability to wire a new ship according to a standard multiplex cable plan, long before the ship subsystems are fully defined, frees both the ship and the subsystems to develop at their own pace, will allow compression of the development schedules and will provide ships with more advanced subsystems. This paper describes the SDMS system currently being developed by the U.S. Navy.
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