778 resultados para Class Numbers


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This talk will describe a study designed to assess if clicker technology during a lesson can improve learning relative to traditional lecture alone. A control group was exposed to the stages of prenatal development via traditional lecture, and an experimental group was exposed to the material via an exercise that used clickers. A pretest showed no difference before the intervention. A posttest showed that the clicker group had significant gains indicating clickers may facilitate learning of science-based material.

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A group of four students are working in a classroom at the New York Trade School while a professor looks on.

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A class of electrical students at the New York Trade School are pictured at workbenches. Black and white photograph.

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Students are pictured with a professor around a workbench during a lead wiping class at the New York Trade School. Photograph is black and white.

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A camera class in the Lithography Department of the New York Trade School poses for a group photo. Black and white photograph mounted on paper.

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In this photo, members of the Stripping Class in the Lithography Department of the New York Trade School are shown at work. Original caption reads, "Members of the Stripping Class. Equipment loaned by the United States Printing & Litho. Company and Local #1." Black and white photograph.

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Ngugi wa Thiong’o’s Devil on the Cross represents both an insightful interpretation and a scathing critique of Kenyan politics and society during the period of neo-colonialism. The present thesis aims to explore, with the help of Marxist ideology and criticism, the relevance of the issues of class struggle, elitism and social collectivism in the novel. At the same time, this study will attempt to define Devil on the Cross as a "national allegory" depicting situations that are common to almost all post-colonial societies, and in particular, how the novel's ideological and political commitment is an important feature as it reflects Ngugi’s effort to draw attention to how Kenya and Africa as a whole suffered from imperialism, neo-colonialism, and a corrupt and greedy capitalist society.

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The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.