Marine mammal species detection and classification

Thesis (Ph.D.)--University of Washington, 2016-04

Vehicle routing and crew scheduling for metropolitan mail distribution at Australia Post

This paper presents a new multi-depot combined vehicle and crew scheduling algorithm, and uses it, in conjunction with a heuristic vehicle routing algorithm, to solve the intra-city mail distribution problem faced by Australia Post. First we describe the Australia Post mail distribution problem and outline the heuristic vehicle routing algorithm used to find vehicle routes. We present a new multi-depot combined vehicle and crew scheduling algorithm based on set covering with column generation. The paper concludes with a computational investigation examining the affect of different types of vehicle routing solutions on the vehicle and crew scheduling solution, comparing the different levels of integration possible with the new vehicle and crew scheduling algorithm and comparing the results of sequential versus simultaneous vehicle and crew scheduling, using real life data for Australia Post distribution networks.

Retrieving designs from a sketch using an automated GT coding and classification system

While the retrieval of existing designs to prevent unnecessary duplication of parts is a recognised strategy in the control of design costs the available techniques to achieve this, even in product data management systems, are limited in performance or require large resources. A novel system has been developed based on a new version of an existing coding system (CAMAC) that allows automatic coding of engineering drawings and their subsequent retrieval using a drawing of the desired component as the input. The ability to find designs using a detail drawing rather than textual descriptions is a significant achievement in itself. Previous testing of the system has demonstrated this capability but if a means could be found to find parts from a simple sketch then its practical application would be much more effective. This paper describes the development and testing of such a search capability using a database of over 3000 engineering components.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

Interactions between landcover pattern and geospatial processing methods:effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

The development and application of a coding and classification system for manufacturing industry

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Race car vehicle dynamics and design applied to formula student

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Recognition on Finite Set of Events: Bayesian Analysis of Generalization Ability and Classification Tree Pruning

The problem of recognition on finite set of events is considered. The generalization ability of classifiers for this problem is studied within the Bayesian approach. The method for non-uniform prior distribution specification on recognition tasks is suggested. It takes into account the assumed degree of intersection between classes. The results of the analysis are applied for pruning of classification trees.

A cash flow-kimutatás szabályozásainak nemzetközi összehasonlítása és csoportosítása (International comparison and classification of Cash Flow Statement regulations)

Az egyes nemzetek számviteli szabályozásának vizsgálatánál az adott ország sajátosságaiból eredően részben eltérő szabályozások alakultak ki. Az induktív megközelítésű vizsgálatok jellemzően a szabályozási kérdések széles körét fogják át, de csak néhány tényező mentén közelítve. A cash flow-kimutatások témakörénél a legtöbbször csak azt nézték, hogy van-e előírás a kimutatás elkészítésére, de a részletekkel már kevésbé foglalkoztak. Ebből adódóan e területen viszonylag kis különbséget mutattak ki ezek a felmérések. A szerző kutatása szerint a nemzeti cash flow-kimutatások szabályozásának részleteiben eltérések tapasztalhatók, és ezek alapján a nemzetek klaszterelemzéssel hierarchikusan csoportokba rendezhetők. _____ Research has found that as a result of their particularities, different countries have established partly different accounting frameworks. Studies with inductive approaches typically encompass a wide range of regulatory issues, but based on a limited number of factors only. In the case of Statements of Cash Flows, most studies have so far only examined the existence of rules governing the presentation of the statement, without an in-depth analysis of the details. Therefore, these studies only found relatively minor differences in this field. The author’s research shows that many differences exist in the details of national Cash Flow Statement regulations, which makes it possible to classify the countries in groups using the method of hierarchical clustering.