A Study of the Effects of Teachers' Knowledge on the NCTM and New York State Mathematics Standards with Students in Grades 7- 12.
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Are you smarter than a high-schooler?This research examines the ability of students in introductory level college mathematics courses to recall fundamental information they learned in high school mathematics courses. During the first week of the Spring 2012 semester, students from three college mathematics classes were given a nineteen-problem quiz that consisted of problems on high school mathematics topics. Immediately following the quiz, the students were asked to complete a six question survey which was used to measure students’ prior mathematical knowledge, their outlook on mathematics, and how easily the students felt they could complete the quiz based on their ability to recall previously learned material. Results from the quiz and survey were compared and analyzed to draw conclusions. At the conclusion of this research study, it was determined that a significant difference existed in the students’ scores on individual questions based on the type of mathematics problem and a significant difference existed in the students’ total quiz scores based on their previous mathematics experience.
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Edge detection using parallel ant colony optimization with Hadoop MapReduce: implementation and scalabilityThe Ant Colony Optimization (ACO) is a popular optimization algorithm that finds use in multiple application areas. Though not among the common uses of this algorithm, edge detection in image analysis is a very functional application of this meta-heuristic. To improve the edge detection capabilities, the inherent parallel nature of the ACO method can be combined with the distributed computing framework provided by the Hadoop/Map-Reduce infrastructure. The latter provides a simple, scalable and fault-tolerant distributed processing paradigm that has been popular in industry and the academic community. In this thesis, we explore the Elastic MapReduce service provided by Amazon Web Services to implement ACO algorithm for edge detection in images, and study its scalability and effectiveness by standard metrics. In addition, we demonstrate a filtering technique to reduce the noisy background of images to achieve significant improvement in the accuracy of edge detection.
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Exploring everyday Math without using technology.No author abstract.
