Positive photoresists can keep their size and design as the photoresist developer solvent doesn't saturate the spots that have not been exposed to UV light. With negative resists, both the UV uncovered and unexposed provinces are permeated by the solvent, which can lead to design distortions.
<h3>What is a positive photoresist?</h3>
A positive photoresist is a kind of photoresist in which the part of the photoresist that is exposed to light evolves soluble to the photoresist developer. The unexposed portion of the photoresist stays insoluble to the photoresist creator.
There are two basic kinds of photoresists: negative and positive. Their primary distinction is how they respond to the light origin.
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Answer:
The civil right movement was a struggle for social justice for African Americans to gain equal rights in the United States.
Explanation:
The civil rights movement helped African American to achieve their rights in America in the 1950s and 1960s. After the Civil War in America, slaves became free. The new changes not seen good because white Southerners believed that African Americans were to be controlled and regulated. The South issued sets of Black Codes called Jim Crow Laws to separate African Americans from the whites. During the Civil rights movement, people were marching and protesting against the Jim Crow Laws and the segregation. The protesters brought the nation’s attention to the injustice, brutality toward them based on their colour. The anger towards racism turned into riots all over the country because whites American were not ready to see African American having the same rights.
Vikings were kind of like pirates, but they raided other ships and destroyed ships. They we're from England. They died around 1400's-1500's.
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.The simple split partitions the data into two mutually exclusive subsets called a training set and a test set . It is common to designate two-thirds of the data as the training set and the remaining one-third as the test set.
How do you measure accuracy of classification models?
There are many ways for measuring classification performance. Accuracy, confusion matrix, log-loss, and AUC-ROC are some of the most popular metrics. Precision-recall is a widely used metrics for classification problems
Classification accuracy:
is a metric that summarizes the performance of a classification model as the number of correct predictions divided by the total number of predictions. It is easy to calculate and intuitive to understand, making it the most common metric used for evaluating classifier models.
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Has a definite volume but no definite shape.
