Marine mammal species detection and classification

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

Developing a categorisation system for rapists' speech

Case linkage, the linking of crimes into series, is used in policing in the UK and other countries. Previous researchers have proposed using rapists' speech in this practice; however, researching this application requires the development of a reliable coding system for rapists' speech. A system was developed based on linguistic theories of pragmatics which allowed for the categorization of an utterance into a speech act type (e.g. directive). Following this classification, the qualitative properties of the utterances (e.g. the degree of threat it carried) could be captured through the use of rating scales. This system was tested against a previously developed system using 188 rapists' utterances taken from victims' descriptions of rape. The pragmatics-based system demonstrated higher inter-rater reliability whilst enabling the classification of a greater number of rapists' utterances. Inter-rater reliability for the subscales was also tested using a sub-sample of 50 rapists' utterances and inter-item correlations were calculated. Seventy-six per cent of the subscales had satisfactory to high inter-rater reliability. Based on these findings and the inter-item correlations, the classification system was revised. The potential use of this system for the practices of case linkage and offender profiling is discussed.

Task classification and decision processes in monitoring behaviour

Task classification is introduced as a method for the evaluation of monitoring behaviour in different task situations. On the basis of an analysis of different monitoring tasks, a task classification system comprising four task 'dimensions' is proposed. The perceptual speed and flexibility of closure categories, which are identified with signal discrimination type, comprise the principal dimension in this taxonomy, the others being sense modality, the time course of events, and source complexity. It is also proposed that decision theory provides the most complete method for the analysis of performance in monitoring tasks. Several different aspects of decision theory in relation to monitoring behaviour are described. A method is also outlined whereby both accuracy and latency measures of performance may be analysed within the same decision theory framework. Eight experiments and an organizational study are reported. The results show that a distinction can be made between the perceptual efficiency (sensitivity) of a monitor and his criterial level of response, and that in most monitoring situations, there is no decrement in efficiency over the work period, but an increase in the strictness of the response criterion. The range of tasks exhibiting either or both of these performance trends can be specified within the task classification system. In particular, it is shown that a sensitivity decrement is only obtained for 'speed' tasks with a high stimulation rate. A distinctive feature of 'speed' tasks is that target detection requires the discrimination of a change in a stimulus relative to preceding stimuli, whereas in 'closure' tasks, the information required for the discrimination of targets is presented at the same point In time. In the final study, the specification of tasks yielding sensitivity decrements is shown to be consistent with a task classification analysis of the monitoring literature. It is also demonstrated that the signal type dimension has a major influence on the consistency of individual differences in performance in different tasks. The results provide an empirical validation for the 'speed' and 'closure' categories, and suggest that individual differences are not completely task specific but are dependent on the demands common to different tasks. Task classification is therefore shovn to enable improved generalizations to be made of the factors affecting 1) performance trends over time, and 2) the consistencv of performance in different tasks. A decision theory analysis of response latencies is shown to support the view that criterion shifts are obtained in some tasks, while sensitivity shifts are obtained in others. The results of a psychophysiological study also suggest that evoked potential latency measures may provide temporal correlates of criterion shifts in monitoring tasks. Among other results, the finding that the latencies of negative responses do not increase over time is taken to invalidate arousal-based theories of performance trends over a work period. An interpretation in terms of expectancy, however, provides a more reliable explanation of criterion shifts. Although the mechanisms underlying the sensitivity decrement are not completely clear, the results rule out 'unitary' theories such as observing response and coupling theory. It is suggested that an interpretation in terms of the memory data limitations on information processing provides the most parsimonious explanation of all the results in the literature relating to sensitivity decrement. Task classification therefore enables the refinement and selection of theories of monitoring behaviour in terms of their reliability in generalizing predictions to a wide range of tasks. It is thus concluded that task classification and decision theory provide a reliable basis for the assessment and analysis of monitoring behaviour in different task situations.

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.

Hierarchical classification of G-protein-coupled receptors with data-driven selection of attributes and classifiers

We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.

AstroWeb – A Graphical Representation of an Astronomical WFPDB Database Using a Web-Based Open Source Geographical Information System

ACM Computing Classification System (1998): H.5.2, H.2.8, J.2, H.5.3.

Classifier PGN: Classification with High Confidence Rules

ACM Computing Classification System (1998): H.2.8, H.3.3.

A Refinement of some Overrelaxation Algorithms for Solving a System of Linear Equations

In this paper we propose a refinement of some successive overrelaxation methods based on the reverse Gauss–Seidel method for solving a system of linear equations Ax = b by the decomposition A = Tm − Em − Fm, where Tm is a banded matrix of bandwidth 2m + 1. We study the convergence of the methods and give software implementation of algorithms in Mathematica package with numerical examples. ACM Computing Classification System (1998): G.1.3.

Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features

ACM Computing Classification System (1998): I.4.9, I.4.10.

Developing a Data-Driven Classification of South Florida Plant Communities

A comprehensive, broadly accepted vegetation classification is important for ecosystem management, particularly for planning and monitoring. South Florida vegetation classification systems that are currently in use were largely arrived at subjectively and intuitively with the involvement of experienced botanical observers and ecologists, but with little support in terms of quantitative field data. The need to develop a field data-driven classification of South Florida vegetation that builds on the ecological organization has been recognized by the National Park Service and vegetation practitioners in the region. The present work, funded by the National Park Service Inventory and Monitoring Program - South Florida/Caribbean Network (SFCN), covers the first stage of a larger project whose goal is to apply extant vegetation data to test, and revise as necessary, an existing, widely used classification (Rutchey et al. 2006). The objectives of the first phase of the project were (1) to identify useful existing datasets, (2) to collect these data and compile them into a geodatabase, (3) to conduct an initial classification analysis of marsh sites, and (4) to design a strategy for augmenting existing information from poorly represented landscapes in order to develop a more comprehensive south Florida classification.

Vegetation community and geochemistry in the Uummannaq District, West Greenland

Beach and salt marsh vegetation of the Uummannaq District, northern West Greenland (c. 70°15' N - 72° N, 49° W - 54° W) was studied 1998 according to the Braun-Blanquet phytosociological approach. Habitat analyses included soil chemistry. Such vegetation locally occurs and is not developed over extensive areas. On gravely stony beaches a Mertensia maritima ssp. maritima community occurs, while a Honckenya peploides var. diffusa community is confined to sandy beaches. The association Honckenyo diffusae-Elymetum mollis Thannh. 1975 is confined to sandy shore walls and low dunes. All vegetation types are assigned to the alliance Honckenyo- Elymion arenariae Tx. 1966, which again is a unit of the order Honckenyo- Elymetalia arenariae Tx. 1966, which is sub ordered to the class Honckenyo-Elymetea arenariae Tx. 1966. On fine sediments along sheltered coasts salt marsh vegetation is locally developed mainly on fiord deltas and outwash plains of small rivers and streams. A distinct zonation pattern in vegetation can be observed from the lower to upper salt marsh: Puccinellietum phryganodis Hadac 1946 association, Caricetum subspathaceae Hadac 1946 association, Caricetum ursinae Hadac 1946 association (all assigned to the alliance Puccinellion phryganodis Hadac 1946) and Festuco-Caricetum glareosae Nordh. 1954 association (assigned to the alliance Armerion maritimae Br.-Bl. et de Leeuw 1936). Both alliances are units of the order Glauco- Puccinellietalia Beeftink et Westhoff in Beeftink 1965, which is assigned to the class Asteretea tripolii Westhoff et Beeftink in Beeftink 1962. TWINSPAN and CCA support the vegetation classification and the CCA with soil chemistry parameters shows that salinity (related to position above MHW) and Ncontent are strongly correlated with the floristical differentiation of the vegetation of the Honckenyo-Elymetea class. In the Asteretea tripolii class, position above MHW (negatively correlated with pH, conductivity and Clcontent) and fresh water supply are likely the main factors, which affect vegetation differentiation. A synoptic survey of vegetation types from Greenland based on published phytosociological tables is presented and distribution of the vegetation types is addressed, just as their position in a circumpolar context. Moreover a Cochlearia groenlandica-Melandrium triflorum community is described as a new vegetation type, occurring on shallow soil on cliffs influenced by salt spray.

Adapting the social-ecological system framework for urban stormwater management: the case of green infrastructure adoption

Stormwater management has long been a critical societal and environmental challenge for communities. An increasing number of municipalities are turning to novel approaches such as green infrastructure to develop more sustainable stormwater management systems. However, there is a need to better understand the technological decision-making processes that lead to specific outcomes within urban stormwater governance systems. We used the social-ecological system (SES) framework to build a classification system for identifying significant variables that influence urban stormwater governance decisions related to green infrastructure adoption. To adapt the framework, we relied on findings from observations at national stormwater meetings in combination with a systematic literature review on influential factors related to green infrastructure adoption. We discuss our revisions to the framework that helped us understand the decision by municipal governments to adopt green infrastructure. Remaining research needs and challenges are discussed regarding the development of an urban stormwater SES framework as a classification tool for knowledge accumulation and synthesis.

A Phylogenetic Classification of the Video-Game Industry’s Business Model Ecosystem

Part 8: Business Strategies Alignment

Atlantic Area Eunis Habitats. Adding new habitat types from European Atlantic coast to the EUNIS Habitat Classification

Marine protection has been emphasized through global and European conventions which highlighted the need for the establishment of special areas of conservation. Classification and habitat mapping have been developed to enhance the assessment of marine environment and improve spatial and strategic planning of human activities and to help on the implementation of ecosystem based management. European Nature information System (EUNIS) is a comprehensive habitat classification system to facilitate the harmonised description and collection of habitat and biotopes that has been developed by the European Environment Agency (EEA) in collaboration with experts from institutions throughout Europe.

Epilepsies Associated With Hippocampal Sclerosis.

Hippocampal sclerosis (HS) is considered the most frequent neuropathological finding in patients with mesial temporal lobe epilepsy (MTLE). Hippocampal specimens of pharmacoresistant MTLE patients that underwent epilepsy surgery for seizure control reveal the characteristic pattern of segmental neuronal cell loss and concomitant astrogliosis. However, classification issues of hippocampal lesion patterns have been a matter of intense debate. International consensus classification has only recently provided significant progress for comparisons of neurosurgical and clinic-pathological series between different centers. The respective four-tiered classification system of the International League Against Epilepsy subdivides HS into three types and includes a term of gliosis only, no-HS. Future studies will be necessary to investigate whether each of these subtypes of HS may be related to different etiological factors or with postoperative memory and seizure outcome. Molecular studies have provided potential deeper insights into the pathogenesis of HS and MTLE on the basis of epilepsy-surgical hippocampal specimens and corresponding animal models. These include channelopathies, activation of NMDA receptors, and other conditions related to Ca(2+) influx into neurons, the imbalance of Ca(2+)-binding proteins, acquired channelopathies that increase neuronal excitability, paraneoplastic and non-paraneoplastic inflammatory events, and epigenetic regulation promoting or facilitating hippocampal epileptogenesis. Genetic predisposition for HS is clearly suggested by the high incidence of family history in patients with HS, and by familial MTLE with HS. So far, it is clear that HS is multifactorial and there is no individual pathogenic factor either necessary or sufficient to generate this intriguing histopathological condition. The obvious variety of pathogenetic combinations underlying HS may explain the multitude of clinical presentations, different responses to clinical and surgical treatment. We believe that the stratification of neuropathological patterns can help to characterize specific clinic-pathological entities and predict the postsurgical seizure control in an improved fashion.