Answer:
From the later months of age 2 and into the middle of their third year, the number of ways children combine words and phrases to form sentences grows each month.
Explanation:
As far as vocabulary is concerned, child develops an understanding to cover 100 words at just 18 months of age. Then comes the stage where the child begins to compose expressions and come to a basic understanding of syntax, the phase of telegraphic speech, and by the age of three, child has tripled vocabulary and doses of up to 1000 words (Sternberg 2005). Furthermore, from the second to the third year, the child understands the differences in the meaning of the word, names the word for all things and concepts, often looks for objects to name them, and speech is understandable to most listeners. In the 2nd year, the speech consists of nouns and verbs that child has created only (bi-bi, am-am, wow-wow) and those adopted from adults (dad, mom, car, juice). In the second half of the second year of life, the child begins to associate words and create the first sentences.
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.
Learn more about random parameter approach:
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Answer:
No entiendo lo que dice, pero si me puedes decir adiós, ¿puedo ayudar?Con eso quiero decir que sea más clara.
Explanation:
All of the following are classification of government based on how many people hold power except for the federal government. The correct answer is A. The federal government is a concept of power sharing.
This would be True because as a part of life they are exposed to new events such as pre school and more.
