Ecological and Behavioral Methods for the Study of Bats [2nd. Ed.]

"First published in 1988, Ecological and Behavioral Methods for the Study of Bats is widely acknowledged as the primary reference for both amateur and professional bat researchers. Bats are the second most diverse group of mammals on the earth. They live on every continent except Antarctica, ranging from deserts to tropical forests to mountains, and their activities have a profound effect on the ecosystems in which they live. Despite their ubiquity and importance, bats are challenging to study. This volume provides researchers, conservationists, and consultants with the ecological background and specific information essential for studying bats in the wild and in captivity. Chapters detail many of the newest and most commonly used field and laboratory techniques needed to advance the study of bats, describe how these methods are applied to the study of the ecology and behavior of bats, and offer advice on how to interpret the results of research. The book includes forty-three chapters, fourteen of which are new to the second edition, with information on molecular ecology and evolution, bioacoustics, chemical communication, flight dynamics, population models, and methods for assessing postnatal growth and development. Fully illustrated and featuring contributions from the world’s leading experts in bat biology, this reference contains everything bat researchers and natural resource managers need to know for the study and conservation of this wide-ranging, ecologically vital, and diverse taxon."--Publisher website

Materials, methods and systems for purification and/or seperation

Materials, methods and systems are provided for the purifn., filtration and​/or sepn. of certain mols. such as certain size biomols. Certain embodiments relate to supports contg. at least one polymethacrylate polymer engineered to have certain pore diams. and other properties, and which can be functionally adapted to for certain purifications, filtrations and​/or sepns. Biomols. are selected from a group consisting of: polynucleotide mols., oligonucleotide mols. including antisense oligonucleotide mols. such as antisense RNA and other oligonucleotide mols. that are inhibitory of gene function such as small interfering RNA (siRNA)​, polypeptides including proteinaceous infective agents such as prions, for example, the infectious agent for CJD, and infectious agents such as viruses and phage.

Using personal construct theory and narrative methods to facilitate reflexive constructions of teaching physical education

This paper reports on two lengthy studies in Physical education teacher education (PETE) conducted independently but which are epistemologically and methodologically linked. The paper describes how personal construct theory (PCT) and its associated methods provided a means for PETE students to reflexively construct their ideas about teaching physical education over an extended period. Data are drawn from each study in the form of a story of a single participant to indicate how this came about. Furthermore we suggest that PCT might be both a useful research strategy and an effective approach to facilitate professional development in a teacher education setting.

Finite volume methods for simulating anomalous transport

In this thesis a new approach for solving a certain class of anomalous diffusion equations was developed. The theory and algorithms arising from this work will pave the way for more efficient and more accurate solutions of these equations, with applications to science, health and industry. The method of finite volumes was applied to discretise the spatial derivatives, and this was shown to outperform existing methods in several key respects. The stability and convergence of the new method were rigorously established.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

Fine-grained plant classification using convolutional neural networks for feature extraction

We present an overview of the QUT plant classification system submitted to LifeCLEF 2014. This system uses generic features extracted from a convolutional neural network previously used to perform general object classification. We examine the effectiveness of these features to perform plant classification when used in combination with an extremely randomised forest. Using this system, with minimal tuning, we obtained relatively good results with a score of 0:249 on the test set of LifeCLEF 2014.

A survey: Error control methods used in bio-cryptography

Integration of biometrics is considered as an attractive solution for the issues associated with password based human authentication as well as for secure storage and release of cryptographic keys which is one of the critical issues associated with modern cryptography. However, the widespread popularity of bio-cryptographic solutions are somewhat restricted by the fuzziness associated with biometric measurements. Therefore, error control mechanisms must be adopted to make sure that fuzziness of biometric inputs can be sufficiently countered. In this paper, we have outlined such existing techniques used in bio-cryptography while explaining how they are deployed in different types of solutions. Finally, we have elaborated on the important facts to be considered when choosing appropriate error correction mechanisms for a particular biometric based solution.

Second-order quantile methods for experts and combinatorial games

We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.

An introduction to education research methods: Exploring the learning journey of pre-service teachers in a transnational programme

Internationally there is interest in developing the research skills of pre-service teachers as a means of ongoing professional renewal with a distinct need for systematic and longitudinal investigation of student learning. The current study takes a unique perspective by exploring the research learning journey of pre-service teachers participating in a transnational degree programme. Using a case-study design that includes both a self-reported and direct measure of research knowledge, the results indicate a progression in learning, as well as evidence that this research knowledge is continued or maintained when the pre-service teachers return to their home university. The findings of this study have implications for both pre-service teacher research training and transnational programmes.

Informing methods for preparing public health overviews of reviews: a comparison of public health overviews with Cochrane Overviews published between 1999 and 2014

Background: Overviews of systematic reviews (SRs) are useful for public health policy; however there is an absence of Cochrane Overviews covering public health (PH) topics. Objectives: We sought to analyze the methodological approaches used in existing Cochrane Overviews and Protocols for overviews (primarily clinical in nature), and compare these to the methods and approaches used in PH overviews (non-Cochrane). The intent was to identify issues that would be relevant for undertaking Cochrane overviews. Methods: We conducted a descriptive analysis of overviews published between 1999 and 2014. We searched the Cochrane Database of Systematic Reviews for Cochrane Protocols for overviews and Cochrane Overviews, and the HealthEvidence.org for PH overviews. The primary characteristics of the overviews and elements of the methodology were extracted and compared. Results: A total of 61 overviews of SRs were included in our analysis; specifically, this included 21 Cochrane Protocols for overviews, 15 Cochrane Overviews, and 27 non-Cochrane PH overviews. Amongst the overviews, the most significant differences are that PH overviews (non-Cochrane) tend to: include earlier and more reviews, greater number of participants, allow lower levels of evidence, use assessment tools other than AMSTAR (A Measurement Tool to Assess Systematic Reviews, i.e. a tool for assessing quality of SRs), not assess quality of evidence in reviews, search more databases overall, specify search limits including English-only reviews, and not consider recent primary studies for inclusion. Some of these differences clearly related to quality, however many relate to the nuances of PH interventions. Conclusions: The methodology in Cochrane overviews and PH overviews varies widely. Future PH overviews may benefit from the Cochrane methodology but the Cochrane approach requires modification to accommodate PH research methodology. Additionally, the use of databases that pre-screen and quality assess relevant PH systematic reviews may help expedite the search process.