Scaling acoustic data analysis through collaboration and automation

Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

Moving tele-monitoring and tele-treatment from promise to practice : a business model approach for a chronic lower back pain application

The availability of new information and communication technologies creates opportunities for new, mobile tele-health services. While many promising tele-health projects deliver working R&D prototypes, they often do not result in actual deployment. We aim to identify critical issues than can increase our understanding and enhance the viability of the mobile tele-health services beyond the R&D phase by developing a business model. The present study describes the systematic development and evaluation of a service-oriented business model for tele-monitoring and -treatment of chronic lower back pain patients based on a mobile technology prototype. We address challenges of multi-sector collaboration and disruptive innovation.

Changing personal epistemologies in early childhood pre-service teachers using an integrated teaching program

This study investigated changes in pre-service teachers’ personal epistemologies as they engaged in an integrated teaching program. Personal epistemology refers to individual beliefs about the nature of knowing and knowledge and has been shown to influence teaching practice. An integrated approach to teaching, based on both an implicit and explicit focus on personal epistemology, was developed by an academic team within a Bachelor of Education (Early Childhood). The teaching program integrated content across four units of study, modelling personal epistemologies implicitly through collaborative reflexive practice. The students were also required to engage in explicit reflections on their personal epistemologies. Quantitative measures of personal epistemology were collected at the beginning and end of the semester using the Epistemological Beliefs Survey (EBS) to assess changes across the teaching period. Results indicated that pre-service teachers’ epistemological beliefs about the integration of knowledge became more sophisticated over the course of the teaching period. Qualitative data included pre-service teachers’ responses to open ended questions and field experience journal reflections about their perceptions of the teaching program and were collected at the end of the semester. These data showed that pre-service teachers held different conceptions about learning as integration, which provided a more nuanced understanding of the EBS data. Understanding pre-service teachers’ epistemological beliefs provides promising directions for teacher preparation and professional enrichment.

Remote monitoring of outdoor performance of low scale dye sensitized solar cells for nanosensors nodes

This is the first outdoor test of small-scale dye sensitized solar cells (DSC) powering a stand-alone nanosensor node. A solar cell test station (SCTS) has been developed using standard DSC to power a gas nanosensor, a radio transmitter, and the control electronics (CE) for battery charging. The station is remotely monitored through wired (Ethernet cable) or wireless connection (radio transmitter) in order to evaluate in real time the performance of the solar cells and devices under different weather conditions. The 408 cm2 active surface module produces enough energy to power a gas nanosensor and a radio transmitter during the day and part of the night. Also, by using a programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. These experiments provide useful data for future outdoor applications such as nanosensor networks.

Personal epistemology and teacher education

A growing body of personal epistemology research shows that personal epistemologies influence student learning, particularly in academic contexts. However, we know little about how personal epistemologies relate to teaching, and even less about teacher education. This introductory chapter sets the stage for this book which brings together a range of international researchers in the field of personal epistemology, teaching, and teacher education. This introductory chapter explores personal epistemology as a construct in the field of teaching and teacher education. In particular, it focuses on teacher education a one contextual influence on personal epistemologies by exploring the nature of teachers' personal epistemologies, teachers' personal epistemologies and learning, teachers' personal epistemologies and teaching, and changing personal epistemology in teacher education programs.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

Teachers' personal epistemologies and teacher education : emergent themes and future research

This chapter summarizes the responses to four questions in each of the chapters in this volume. The questions addressed the use of a conceptual framework that guides the chapter, issues of domain-generality, how personal epistemology relates to teaching, and how personal epistemologies change. We concluded that all of the chapters discussed the distinction between constructivist and transmission teaching practices, while suggesting that there are many inconsistencies in understanding the relationship between the nature of beliefs and teachers’ practices regardless of the relative sophistication of teachers’ personal epistemologies. We also summarized a multi-component instructional model for calibrating teaching practices based on suggestions in each of the chapters, and made four suggestions for future research, including the need for an integrated theory that accounts for the development and manifestations of personal pistemology in the classroom, the generalizability of fi ndings across different measurements, a set of guidelines to promote teacher epistemological change, and an explicit instructional model that explains the development and calibration of beliefs and practices. The goal of this volume was to examine the relationship between teachers’ personal epistemologies and teacher education. Sixteen different chapters addressed one or more aspects of this issue. Although each of the chapters addressed different aspects of teachers’ personal epistemologies, a number of common themes are apparent across the chapters. We believe it is useful to articulate these themes in greater detail to provide a better retrospective understanding of this volume, as well as a better prospective framework for future research and changes to teacher training programs. We divide this chapter into two main sections. The fi rst section addresses four key questions about the nature of teachers’ personal epistemologies that were discussed in the introductory chapter as part of a larger set of questions. These questions focus on how to conceptualize these beliefs as explicit models; whether beliefs are domain-specifi c or domain-general; how beliefs are related to teaching; and how beliefs change over time. We provide a summary of each chapter in terms of these four questions. The second section proposes four general suggestions for future research based on the studies reported within this volume.

Persistent ocean monitoring with underwater gliders : adapting sampling resolution

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

Designing and using historical vignettes in science teaching : a personal account

Historical vignettes are interesting short stories which encapsulate a brief period of scientific history. They can be useful tools for teaching the nature of science, demonstrating the practices of science and making science fun. Historical vignettes illustrate the role of people and social processes in science. In this paper I describe my experience with writing and presenting an historical vignette during a Biology unit. Included is a copy of the vignette and I have identified some possible improvements that might lead to better outcomes. This may be helpful for other teachers who wish to try this strategy for themselves.