4*30
120 pints per day
Tom drinks 120 pints in 30 days
A Temporal Investigation of Crash Severity Factors in Worker-Involved Work Zone Crashes: Random Parameters and Machine Learning Approaches:
Reason:
In the context of work zone safety, worker presence and its impact on crash severity has been less explored. Moreover, there is a lack of research on contributing factors by time-of-day. To accomplish this, first a mixed logit model was used to determine statistically significant crash severity contributing factors and their effects. Significant factors in both models included work-zone-specific characteristics and crash-specific characteristics, where environmental characteristics were only significant in the daytime model. In addition, results from parameter transferability test provided evidence that daytime and nighttime crashes need to be modeled separately. Further, to explore the nonlinear relationship between crash severity levels and time-of-day, as well as compare the effects of variables to that of the logit model and assess prediction performance, a Support Vector Machines (SVM)
What is meant by machine learning approach?
Machine Learning is an AI technique that teaches computers to learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model.
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Protozoan infections are most prevalent in <u>Asia, Africa</u><u> </u>and <u>South America</u>.
Explanation:
Infections caused by protozoans in humans include severe diseases like African sleeping sickness, malaria, amoebic dysentery, giardiasis etc.
These infections are transmitted through arthropod vectors mostly through their bite. Protozoan parasitic infections are common in tropical developing countries than in the developed nations.
When travelers from non-prevalent countries like the United States travel to countries which are prone to protozoan infections, they also become susceptible and get infected when their own immune system is weakened. They become potential carriers when they travel back to their country.
It is helpful because the grid can help pinpoint the exact location on the map.
Males are most likely to be ronbef