Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Recommendations for the reporting of foot and ankle models

Multiple marker sets and models are currently available for assessing foot and ankle kinematics in gait. Despite the presence of such a wide variety of models, the reporting of methodological designs remains inconsistent and lacks clearly defined standards. This review highlights the variability found when reporting biomechanical model parameters, methodological design, and model reliability. Further, the review clearly demonstrates the need for a consensus of what methodological considerations to report in manuscripts, which focus on the topic of foot and ankle biomechanics. We propose five minimum reporting standards, that we believe will ensure the transparency of methods and begin to allow the community to move towards standard modelling practice. The strict adherence to these standards should ultimately improve the interpretation and clinical useability of foot and ankle marker sets and their corresponding models.

Bribie Island groundwater resources : challenges in development of conceptual and numerical models

Groundwater is a major resource on Bribie Island and its sustainable management is essential to maintain the natural and modified eco-systems, as well as the human population and the integrity of the island as a sand mass. An effective numerical model is essential to enable predictions, and to test various water use and rainfall/climate scenarios. Such a numerical model must, however, be based on a representative conceptual hydrogeological model to allow incorporation of realistic controls and processes. Here we discuss the various hydrogeological models and parameters, and hydrological properties of the materials forming the island. We discuss the hydrological processes and how they can be incorporated into these models, in an integrated manner. Processes include recharge, discharge to wetlands and along the coastline, abstraction, evapotranspiration and potential seawater intrusion. The types and distributions of groundwater bores and monitoring are considered, as are scenarios for groundwater supply abstraction. Different types of numerical models and their applicability are also considered

Development of zonal cartilage constructs : effects of chondrocyte subpopulation, compressive stimulation, and culture models

Articular cartilage is a highly resilient tissue located at the ends of long bones. It has a zonal structure, which has functional significance in load-bearing. Cartilage does not spontaneously heal itself when damaged, and untreated cartilage lesions or age-related wear often lead to osteoarthritis (OA). OA is a degenerative condition that is highly prevalent, age-associated, and significantly affects patient mobility and quality of life. There is no cure for OA, and patients usually resort to replacing the biological joint with an artificial prosthesis. An alternative approach is to dynamically regenerate damaged or diseased cartilage through cartilage tissue engineering, where cells, materials, and stimuli are combined to form new cartilage. However, despite extensive research, major limitations remain that have prevented the wide-spread application of tissue-engineered cartilage. Critically, there is a dearth of information on whether autologous chondrocytes obtained from OA patients can be used to successfully generate cartilage tissues with structural hierarchy typically found in normal articular cartilage. I aim to address these limitations in this thesis by showing that chondrocyte subpopulations isolated from macroscopically normal areas of the cartilage can be used to engineer stratified cartilage tissues and that compressive loading plays an important role in zone-dependent biosynthesis of these chondrocytes. I first demonstrate that chondrocyte subpopulations from the superficial (S) and middle/deep (MD) zones of OA cartilage are responsive to compressive stimulation in vitro, and that the effect of compression on construct quality is zone-dependent. I also show that compressive stimulation can influence pericelluar matrix production, matrix metalloproteinase secretion, and cytokine expression in zonal chondrocytes in an alginate hydrogel model. Subsequently, I focus on recreating the zonal structure by forming layered constructs using the alginate-released chondrocyte (ARC) method either with or without polymeric scaffolds. Resulting zonal ARC constructs had hyaline morphology, and expressed cartilage matrix molecules such as proteoglycans and collagen type II in both scaffold-free and scaffold-based approaches. Overall, my findings demonstrate that chondrocyte subpopulations obtained from OA joints respond sensitively to compressive stimulation, and are able to form cartilaginous constructs with stratified organization similar to native cartilage using the scaffold-free and scaffold-based ARC technique. The ultimate goal in tissue engineering is to help provide improved treatment options for patients suffering from debilitating conditions such as OA. Further investigations in developing functional cartilage replacement tissues using autologous chondrocytes will bring us a step closer to improving the quality of life for millions of OA patients worldwide.

Timed and Probabilistic Automata for Automatic Animal Call Recognition

Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

Comparative study of analytical rental model and statistical models for predicting house rental levels

The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.

Comment on "Local accumulation times for source, diffusion, and degradation models in two and three dimensions" [J. Chem. Phys. 138, 104121 (2013)]

In a recent paper, Gordon, Muratov, and Shvartsman studied a partial differential equation (PDE) model describing radially symmetric diffusion and degradation in two and three dimensions. They paid particular attention to the local accumulation time (LAT), also known in the literature as the mean action time, which is a spatially dependent timescale that can be used to provide an estimate of the time required for the transient solution to effectively reach steady state. They presented exact results for three-dimensional applications and gave approximate results for the two-dimensional analogue. Here we make two generalizations of Gordon, Muratov, and Shvartsman’s work: (i) we present an exact expression for the LAT in any dimension and (ii) we present an exact expression for the variance of the distribution. The variance provides useful information regarding the spread about the mean that is not captured by the LAT. We conclude by describing further extensions of the model that were not considered by Gordon,Muratov, and Shvartsman. We have found that exact expressions for the LAT can also be derived for these important extensions...

Exploring new and emerging models for nonlinear performative works

This dissertation seeks to define and classify potential forms of Nonlinear structure and explore the possibilities they afford for the creation of new musical works. It provides the first comprehensive framework for the discussion of Nonlinear structure in musical works and provides a detailed overview of the rise of nonlinearity in music during the 20th century. Nonlinear events are shown to emerge through significant parametrical discontinuity at the boundaries between regions of relatively strong internal cohesion. The dissertation situates Nonlinear structures in relation to linear structures and unstructured sonic phenomena and provides a means of evaluating Nonlinearity in a musical structure through the consideration of the degree to which the structure is integrated, contingent, compressible and determinate as a whole. It is proposed that Nonlinearity can be classified as a three dimensional space described by three continuums: the temporal continuum, encompassing sequential and multilinear forms of organization, the narrative continuum encompassing processual, game structure and developmental narrative forms and the referential continuum encompassing stylistic allusion, adaptation and quotation. The use of spectrograms of recorded musical works is proposed as a means of evaluating Nonlinearity in a musical work through the visual representation of parametrical divergence in pitch, duration, timbre and dynamic over time. Spectral and structural analysis of repertoire works is undertaken as part of an exploration of musical nonlinearity and the compositional and performative features that characterize it. The contribution of cultural, ideological, scientific and technological shifts to the emergence of Nonlinearity in music is discussed and a range of compositional factors that contributed to the emergence of musical Nonlinearity is examined. The evolution of notational innovations from the mobile score to the screen score is plotted and a novel framework for the discussion of these forms of musical transmission is proposed. A computer coordinated performative model is discussed, in which a computer synchronises screening of notational information, provides temporal coordination of the performers through click-tracks or similar methods and synchronises the audio processing and synthesized elements of the work. It is proposed that such a model constitutes a highly effective means of realizing complex Nonlinear structures. A creative folio comprising 29 original works that explore nonlinearity is presented, discussed and categorised utilising the proposed classifications. Spectrograms of these works are employed where appropriate to illustrate the instantiation of parametrically divergent substructures and examples of structural openness through multiple versioning.

Applications and equivalent models for coupled inductor parallel interleaved converters

Parallel interleaved converters are finding more applications everyday, for example they are frequently used for VRMs on PC main boards mainly to obtain better transient response. Parallel interleaved converters can have their inductances uncoupled, directly coupled or inversely coupled, all of which have different applications with associated advantages and disadvantages. Coupled systems offer more control over converter features, such as ripple currents, inductance volume and transient response. To be able to gain an intuitive understanding of which type of parallel interleaved converter, what amount of coupling, what number of levels and how much inductance should be used for different applications a simple equivalent model is needed. As all phases of an interleaved converter are supposed to be identical, the equivalent model is nothing more than a separate inductance which is common to all phases. Without utilising this simplification the design of a coupled system is quite daunting. Being able to design a coupled system involves solving and understanding the RMS currents of the input, individual phase (or cell) and output. A procedure using this equivalent model and a small amount of modulo arithmetic is detailed.

Pavlovian fear memory circuits and phenotype models of PTSD

Pavlovian fear conditioning, also known as classical fear conditioning is an important model in the study of the neurobiology of normal and pathological fear. Progress in the neurobiology of Pavlovian fear also enhances our understanding of disorders such as posttraumatic stress disorder (PTSD) and with developing effective treatment strategies. Here we describe how Pavlovian fear conditioning is a key tool for understanding both the neurobiology of fear and the mechanisms underlying variations in fear memory strength observed across different phenotypes. First we discuss how Pavlovian fear models aspects of PTSD. Second, we describe the neural circuits of Pavlovian fear and the molecular mechanisms within these circuits that regulate fear memory. Finally, we show how fear memory strength is heritable; and describe genes which are specifically linked to both changes in Pavlovian fear behavior and to its underlying neural circuitry. These emerging data begin to define the essential genes, cells and circuits that contribute to normal and pathological fear.

An evaluation of different features and learning models for anomalous event detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Quality Information System: Investigating the conception, role, models and suggesting conceptual and hierarchal models

In the current business world which companies’ competition is very compact in the business arena, quality in manufacturing and providing products and services can be considered as a means of seeking excellence and success of companies in this competition arena. Entering the era of e-commerce and emergence of new production systems and new organizational structures, traditional management and quality assurance systems have been challenged. Consequently, quality information system has been gained a special seat as one of the new tools of quality management. In this paper, quality information system has been studied with a review of the literature of the quality information system, and the role and position of quality Information System (QIS) among other information systems of a organization is investigated. The quality Information system models are analyzed and by analyzing and assessing presented models in quality information system a conceptual and hierarchical model of quality information system is suggested and studied. As a case study the hierarchical model of quality information system is developed by evaluating hierarchical models presented in the field of quality information system based on the Shetabkar Co.

Probability and story-telling : normative and descriptive models of juridical proof

The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

Comparing different approach and avoidance models of learning and personality in the prediction of work, university, and leadership outcomes

Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N equals 137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.