Kevin b reyes (15 risultati)

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condizione: As New. Condizione sovraccoperta: Fine. 1st Edition. As new condition maroon boards/brown spine/gold spine lettering contained in a fine condition non price-clipped color illustrated dust jacket. Includes List of Illustrations; Introduction by Byron Hollinshead; Acknowledgments; Illustration Credits; and A Note About the Editor. Illustrated with black-and-white photographs. "Twenty distinguished American historians vividly re-imagine twenty events of great drama and significance in our country's past. "What is the scene or incident in American history that you would like to have witnessed - and why?" This is the thought-provoking question that editor Byron Holingshead posed to twenty of our finest interpreters of American history with the invitation to write a personal essay answering it. The result is I Wish I'd Been There, a book that trains a lens on crucial moments of our past and brings them to vivid life. With these peerless scholars as their guides, readers will be transported to the Salem witch trials, the Lewis and Clark expedition, the raid on Harpers Ferry, the assissination of Abraham Lincoln, the Scopes "monkey trial," the beginnings of the Vietnam War, the voting rights march to Selma, and other turning points of our national drama. Contributors include Mary Beth Norton, Joseph Ellis, Jay Winik, Carol Berkin, Kevin Baker, Robert Cowley, Carolyn Gilman, Geoffrey Ward, Robert Dallek, and William Leuchtenburg, among other luminaries of the historical profession. I Wish I'd Been There is a marvelous concept, wonderfully and imaginatively executed. The result is an American pageant of character and event that will attract and delight readers of history." - from the inner front and rear jacket flaps. Reyes, Jesse Marinoff (jacket design); Hobbing, Diane (book design) (illustratore). …

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condizione: Neu. Neuware - The purpose of this research was to improve on the outlier detection methods used in hyperspectral imagery analysis. An algorithm was developed based on Principal Component Analysis (PCA), a classical multivariate technique usually used for data reduction. Using PCA, a score is computed and a test statistic is then used to make outlier declarations. First, four separate PCA test statistics were compared in the algorithm. It was found that Mahalanobis distance performed the best. This test statistic was then compared using the entire data set and a clustered data set. Since it has been shown in the literature that even one outlier can distort the covariance matrix, an iterative approach to the clustered based algorithm was developed. After each iteration, if an outlier(s) is identified, the observation(s) is removed and the algorithm is reapplied. Once no new outliers are identified or one of the stopping conditions is met, the algorithm is reapplied a final time with the new covariance matrix applied to the original data set. Experiments were designed and analyzed using analysis of variance to identify the significant factors and optimal settings to maximize each algorithm's performance.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. …

Buch. Condizione: Neu. Neuware - The purpose of this research was to improve on the outlier detection methods used in hyperspectral imagery analysis. An algorithm was developed based on Principal Component Analysis (PCA), a classical multivariate technique usually used for data reduction. Using PCA, a score is computed and a test statistic is then used to make outlier declarations. First, four separate PCA test statistics were compared in the algorithm. It was found that Mahalanobis distance performed the best. This test statistic was then compared using the entire data set and a clustered data set. Since it has been shown in the literature that even one outlier can distort the covariance matrix, an iterative approach to the clustered based algorithm was developed. After each iteration, if an outlier(s) is identified, the observation(s) is removed and the algorithm is reapplied. Once no new outliers are identified or one of the stopping conditions is met, the algorithm is reapplied a final time with the new covariance matrix applied to the original data set. Experiments were designed and analyzed using analysis of variance to identify the significant factors and optimal settings to maximize each algorithm's performance.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. …

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Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.