MIL-STD
- Home Page 329
loading...
Comparison of STEM Programs in a Chinese School and an American School
Xiang Gong, Mathematics Teacher & Research Mentor
Erik R. Mohlhenrich, Biology Teacher & Research Mentor
Princeton International School of Mathematics and Science
Abstract: Countries around the world are committed to cultivating outstanding talent through STEM education. It is widely acknowledged that authentic STEM research programs are one of the most effective ways to achieve the goals of STEM education. In this paper, we present survey results in the 2018-2019 school year from school-based research programs at Princeton International School of Mathematics and Science (PRISMS) in the US and the High School Affiliated to Renmin University (commonly abbreviated as RDFZ) in China. A factorial MANOVA and a General Linear Model Univariate Analysis were used to test for similarities and differences between students’ gains in dimensions of gains in thinking and working like a scientist (WIS), personal gains related to research work (PG), gains in skills (SKILL), attitudes or behaviors as a researcher (ATT), and career and graduate education aspirations (INF). Across both programs, we find significant gains on all variables as students’ progress through their research experience. Scores from PRISMS students on WIS, PG, and ATT are significantly higher than those from RDFZ students. SKILL and INF showed significant correlations and thus were analyzed together; PRISMS students also scored higher on these variables. PRISMS 12th graders scored the highest of all school/grade level combinations. The results of this comparison speak to the efficacy of both programs in achieving the pedagogical goals of STEM research experiences. Variables that may have influenced the difference in outcomes between PRISMS and RDFZ are discussed, with particular attention given to the differences in the student population and school in general, number of students per project, and length of the research experience.
CLICK HERE to order complete paper
Nota Bene
This content is accessible to paid subscribers. To view it please enter your password below or send [email protected] a request for subscription details.
International Building Code Assembly Group A
Occupancy classifications inform every dimension and every discipline of the built environment. Classifications are grouped primarily based on their relative fire hazard and life safety properties such as how many people will be in the area, are there hazardous materials or manufacturing, and are people sleeping, cooking, living etc. Getting people and animals out of a built space with an unobstructed egress path to exit buildings, structures, and spaces inform occupancy classifications. A means of egress is comprised of exit access, exit, and exit discharge.
S. 919 Data Care Act of 2021
117th Congress Swearing In Floor Proceedings – January 3, 2021, House Chamber
H.R. 331 Nurses CARE Act of 2021
117th Congress Swearing In Floor Proceedings – January 3, 2021, House Chamber
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.
CLICK HERE to order complete paper.
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
CLICK HERE for complete article
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
Welcome
Standards Michigan Group, LLC
2723 South State Street | Suite 150
Ann Arbor, MI 48104 USA
888-746-3670
DIRECTIONS
 |
 |
|
 |
 |
|
 |
 |
Layout mode
Predefined Skins
Custom Colors
Choose your skin color
Patterns Background
Images Background