Gain of Function Research
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A State-by-State Comparison of Occupational Electrical Fatalities
A State by State Comparison of Occupational Electrical Fatalities
John Mattews Associates
National Fire Protection Association
Abstract: The United States, ranking third among countries in both population and land area, is geographically and ethnically diverse. The 50 states, admitted one at a time to the Union over a period of about 175 years, reflect this diversity in historical development, population, population density, land area, and natural resources. State populations vary by as much as nearly 70 times and state land area by a factor greater than 400. Consequently, industry types, population demographics, and involvement of state governments in occupational health and safety vary among states. The 2011-2018 Bureau of Labor Statistics (BLS) occupational and electrical fatality data are used to identify states with higher numbers of fatal injuries and higher incidence rates. The 2011-2018 BLS data and occupational safety and health administration (OSHA) records are reviewed to characterize worker occupations and incidents. The five states with the highest numbers of electrical fatalities are discussed. The 12 states with the highest electrical fatality incidence rates are also reviewed. The potential factors contributing to higher numbers of fatal electrical injuries and incidence rates are explored. These include industry type, worker demographics, climate, and state legislation and culture. Failure to reach workers and more effective ways to reach workers at risk for electrical injury are addressed.
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https://ieeexplore.ieee.org/document/9195772
Cloud Service Selection
太原理工大学
Normal Cloud Model-Based Algorithm for Multi-Attribute Trusted Cloud Service Selection
Yuli Yang – Rui Liu – Yongle Chen
Taiyuan University of Technology
Tong Li – Yi Tang
Guangzhou University
Abstract:
With the wide deployment of cloud computing, many security challenges have arisen, such as data and storage integrity and virtualization security. The crisis of trust caused by these security issues has become one of the important factors restricting the wide applications of cloud service. Especially for security-sensitive users, it is challenging to quickly select a cloud service which has the high level of trust and can meet both the user preferences and specific functional demands. This paper explores the multi-granularity selection standard of trust level, the users’ preference calculation model, and the cloud service selection algorithm. First, the trust evaluation mechanisms among different entities in the human society are fitted, and the multi-granularity selection standard of trust levels based on Gaussian cloud transformation is constructed. Then, the calculation model of user preferences based on the cloud analytic hierarchy process is developed. Finally, the trusted cloud service selection algorithm based on two-step fuzzy comprehensive evaluation is proposed and experimentally validated.
广州大学
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S. 96 Reopen and Rebuild America’s Schools Act of 2021
117th Congress Swearing In Floor Proceedings – January 3, 2021, House Chamber
BIM-based automated code compliance checking
A Review on BIM-based automated code compliance checking system
Aimi Sara Ismail – Kherun Nita Ali – Noorminshah A. Iahad
Abstract: The checking process of the building design with building regulations or codes is a time-consuming and error prone process. The automation of code compliance checking process has been explored since 1960s and becoming more vigorous with the emergence of Building Information Modeling (BIM). A neutral format, Industry Foundation Classes (IFC) which is developed under BIM platform had led to better collaboration and information exchange throughout BIM software and development of the checking system. Generally, the structure of an automated system consists of rule interpretation stage, building model preparation stage, rule execution stage and rule reporting stage. Rule interpretation stage is the most vital and complex stage. In interpreting the rules, various techniques have been investigated and applied to employ comprehensive and accurate checking process on the building designs which are mainly in IFC format. The most common techniques used are by utilizing existing software such as Solibri Model Checker, establishing a plug-in application, adopting object-based approach, logical approach and ontological approach. This paper provides a highlight and review on previous studies which successfully employed the appropriate techniques in interpreting the rules for checking purposes. This will subsequently assist future research on this area and create more astounding code compliance checking system.
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https://ieeexplore.ieee.org/document/8002486/authors#authors
Artificial Intelligence Applications to Achieve Water-related Sustainable Development Goals
国際連合大学
Hamid Mehmood – Danielle Liao – Kimberly Mahadeo
Abstract: This paper reviews the Artificial Intelligence (AI) applications that help achieve water-related Sustainable Development Goals (SDGs). Current applications of AI in the water sector include i) predictive maintenance of water infrastructure, ii) forecasting water demand and consumption, iii) monitoring water reservoirs and dams, iv) tracking water quality, and v) monitoring and predicting water-related disasters. These applications contribute to achieving water-related SDG targets, specifically 3, 6, 11, and 15. The literature review shows that: i) the rate of adoption of AI-based solutions in predictive maintenance of water infrastructure has accelerated, as AI becomes increasingly accessible, and data analytics and smart sensors become more efficient and affordable; ii) deep learning technology has enabled a new generation of water management systems, which can generate short-term (daily) and long-term (annual) forecasts. iii) as Asia and South America experience an increase in water reservoir and dam construction, AI-based techniques are being successfully implemented in reservoir development and operation; iv) water quality monitoring has been the most significantly impacted by AI relative to other applications, as AI is used to examine small samples and large water bodies, and for real time water quality monitoring; v) AI can be used to forecast water-related disasters with higher accuracy, frequency and lead time, allowing for focused management of post-disaster activity. The paper ends by highlighting the challenges of adopting AI to achieve water-related SDGs.
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New update alert! The 2022 update to the Trademark Assignment Dataset is now available online. Find 1.29 million trademark assignments, involving 2.28 million unique trademark properties issued by the USPTO between March 1952 and January 2023: https://t.co/njrDAbSpwB pic.twitter.com/GkAXrHoQ9T
— USPTO (@uspto) July 13, 2023
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