Magnetic fields

Effects of high and low gradient magnetic fields on human performance for space flight application

Economics of Increased Beef Grader Accuracy

Carcass data from more than 38,000 cattle was used to compare the called and measured yield grade in two different periods: before and after the slaughter plant incorporated another grader in the line to improve grading accuracy. The study shows that the graders accuracy significantly increased. The higher accuracy affected all yield grades, but most notably resulted in more called yield grade 4 and 5 carcasses. This analysis will develop insight of what will be the effect of instrument grading that will be more accurate than previously called grades.The results are expressed as the conditional distribution of the called yield grade for a given value of the measured yield grade. The pricing grid currently used by the industry was used to analyze the effect of the graders errors on the expected values of the premiums on both periods and by yield grade. The results show that the company has an incentive to improve accuracy of grading. Simulating the results of measured vs. called yield grade over prices at the time and a standard industry grid showed that the plant can benefit by $1.32 per head by increasing grading accuracy.cattle, carcass grading, accuracy, economics of grading,

Upskilling, Reskilling and Learning Agility

What We Know... Technological developments will result in both need for new skills and job loss or replacement Some business units will be disproportionately impacted in the next 5-10 years Impact depends on rate of technology adoptio

Tesler\u27s Law and Learning Complexity

Tesler’s Law is an idea that complexity is conserved in a given situation. For example, an easy to use application (simple user experience) means that the complexity is transferred to the underlying code and network infrastructure. References: https://en.wikipedia.org/wiki/Law_of_conservation_of_complexity Complexity Law Tesler’s Law has implications to learning design. This article identifies five

I LEARNED FROM A STRUGGLING STUDENT, AND YOU CAN TOO.

Themes: A learner’s ability to articulate their own learning struggle is a skill worth developing A learning leader’s ability to facilitate the discussion to articulate specific learning obstacles is essential Specificity about “the problem” mitigates the risk of a “poor solution” being implemented The article presents a case example of insights from a student, then describes three observations about education/learning systems: Consider Content Complexity vs Pace of Change Be precise about assessing the defining the specific gap between expected performance and current performance Differentiate problems learning from problems with the learning solution Analyze the learning system (diagram included) The article closes with two questions to assess established, mature, paradigms in learning systems

Broadskilling to Prepare Students for Future Work

Education professionals are concerned about quality of the education our youth receive. Corporations are concerned about having a prepared, skilled workforce as we face a sweeping digital transformation. Impact metrics vary, but there are clear themes about concerns of the emerging generation of workers (“will a robot take my job?”) and skills gaps. While corporate HR leans in on innovative recruiting, “upskilling” and “reskilling” initiatives, the opportunity for students is “Broadskilling” (i.e. career awareness, entrepreneurship, soft skills, adaptability, learning to learn, and befriending technology). Let’s engage in a practical discussion based on current data and share our experiences and stories

Learning Systems in Schools and at Work

Key Points in this Post: Learning systems in schools differ from learning systems at work The content is different The context is different The complexity is different, specifically about promotion criteria Question explored: Is it time to assess the current K-12 education system paradigm in order to adapt to the future of work