Most Popular Books by David Hutchinson

Consists entirely of art originally published in the graphic novels Victorian secret, Victorian secret summer catalog, Victorian secret winter wardrobe, Victorian secret masquerade, and Victorian secret agents.

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.

What Remains is a limited edition artist book with an edition of 100 signed and numbered books and 10 Artist Proof books. The book is comprised of a chromatically-coded (translated) ''text'' superimposed over forest photographs. The text is a colored translation of two essays by Jean Genet: ''What Remains of a Rembrandt Torn into Four Equal Pieces and Flushed Down the Toilet ...'' and ''Rembrandt''s Secret'', both published by Hanuman Press in 1988. The photographs were taken in a forest near the artist''s home. The juxtaposition of photographs and ''translated'' texts contemplate the import of ''natural laws'' as they are ascribed to our environment and to human actions. The book is formatted to 8 1/2" x 11". The first edition will be hardback and printed on archival paper.

Cluster is a coloring book that focuses on forest blowdown, an increasingly familiar phenomenon as storms become more violent. The book is comprised of 30 drawings of various blowdown events in a nearby forest. It is top-bound for use by left-handed and right-handed artists. The paper of the book will be heavy enough to support wet or dry media.

Context. Reports suggest that defects in code cost the US in excess of $50billion per year to put right. Defect Prediction is an important part of Software Engineering. It allows developers to prioritise the code that needs to be inspected when trying to reduce the number of defects in code. A small change in the number of defects found will have a significant impact on the cost of producing software. Aims. The aim of this dissertation is to investigate the factors which a ect the performance of defect prediction models. Identifying the causes of variation in the way that variables are computed should help to improve the precision of defect prediction models and hence improve the cost e ectiveness of defect prediction. Methods. This dissertation is by published work. The first three papers examine variation in the independent variables (code metrics) and the dependent variable (number/location of defects). The fourth and fifth papers investigate the e ect that di erent learners and datasets have on the predictive performance of defect prediction models. The final paper investigates the reported use of di erent machine learning approaches in studies published between 2000 and 2010. Results. The first and second papers show that independent variables are sensitive to the measurement protocol used, this suggests that the way data is collected a ects the performance of defect prediction. The third paper shows that dependent variable data may be untrustworthy as there is no reliable method for labelling a unit of code as defective or not. The fourth and fifth papers show that the dataset and learner used when producing defect prediction models have an e ect on the performance of the models. The final paper shows that the approaches used by researchers to build defect prediction models is variable, with good practices being ignored in many papers. Conclusions. The measurement protocols for independent and dependent variables used for defect prediction need to be clearly described so that results can be compared like with like. It is possible that the predictive results of one research group have a higher performance value than another research group because of the way that they calculated the metrics rather than the method of building the model used to predict the defect prone modules. The machine learning approaches used by researchers need to be clearly reported in order to be able to improve the quality of defect prediction studies and allow a larger corpus of reliable results to be gathered.