Monitoring children's progress using child portfolios

Introduces a method to early childhood professionals of observing children as they are involved in everyday play episodes, record children's development and plan for this, while utilising the knowledge and input of the key players in the partnership, parents and teachers.

Monitoring energy performance of air conditioners in classrooms

Air quality and temperatures in classrooms are important factors influencing the student learning process. To improve the thermal comfort of classrooms for Queensland State Schools, Queensland Government initiated the "Cooler Schools Program". One of the key objectives under this program was to develop low energy cooling systems as an alternative to high energy demand conventioanl split system of air conditioning (AC) systems. In order to compare and evaluate the energy performance of different types of air conditioners installed in classrooms, monitoring systems were installed in a state primary school located in the greater outer urban area of Brisbane, Australia. It was found that the installation of monitoring systems could have a significant impact on the accuracy of the data being collected. By comparing the estimated energy efficiency ratio (EER)for four qualified air conditioners included in this study, it was also found that AC6, a hybrid air conditioner newly developed by the Queensland Department of Public Works (DPW), had the best energy performance, although the current data were not able to show the full advantages of the system.

Technical report : acoustic analysis of the natural environment

This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the advantage of cheaper and increased sampling but make available so much data that automated analysis becomes essential. The report describes a number of tools for automated analysis of recordings, including noise removal from spectrograms, acoustic event detection, event pattern recognition, spectral peak tracking, syntactic pattern recognition applied to call syllables, and oscillation detection. These algorithms are applied to a number of animal call recognition tasks, chosen because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are frequent contaminants of recordings of the terrestrial environment; (2) the detection of bird and calls; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.

Acknowledging social justice and equity through good practice for monitoring student learning engagement in FYE

As higher education institutions respond to government targets to widen participation, their student populations will become increasingly diverse, and the issues around student success and retention will be more closely scrutinised. The concept of student engagement is a key factor in student achievement and retention and Australasian institutions have a range of initiatives aimed at monitoring and intervening with students who are at risk of disengaging. Within the widening participation agenda, it is absolutely critical that these initiatives are designed to enable success for all students, particularly those for whom social and cultural disadvantage have been a barrier. Consequently, for the sector, initiatives of this type must be consistent with the concept of social justice and a set of principles would provide this foundation. This session will provide an opportunity for participants to examine a draft set of principles and to discuss their potential value for the participants’ institutional contexts.

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 standalone 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 powering a nanosensor and a transmitter under different weather conditions. We analyze trends of energy conversion efficiency after 60 days of operation. 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 variable programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. Although this technology is at an early stage of development, these experiments provide useful data for future outdoor applications such as nanosensor network nodes.

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.

Simulation of inplane and out of plane AE source in thin plate

In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in a wide spectrum of areas, ranging from nondestructive testing for the detection of materials defects to monitoring of microseismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary longitudinal waves), S waves (shear/transverse waves) and Rayleigh (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use acoustic emission technique for accurate identification of source, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals along with the characteristics of the source. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location and its characteristics in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.

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.

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

Archiving nature’s heartbeat using smart phones

The impact of urban development and climate change has created the impetus to monitor changes in the environment, particularly, the behaviour, habitat and movement of fauna species. The aim of this chapter is to present the design and development of a sensor network based on smart phones to automatically collect and analyse acoustic and visual data for environmental monitoring purposes. Due to the communication and sophisticated programming facilities offered by smart phones, software tools can be developed to allow data to be collected, partially processed and sent to a remote server over the network for storage and further processing. This sensor network which employs a client-server architecture has been deployed in three applications: monitoring a rare bird species near Brisbane Airport, study of koalas behaviour at St Bees Island, and detection of fruit flies. The users of this system include scientists (e.g. ecologists, ornithologists, computer scientists) and community groups participating in data collection or reporting on the environment (e.g. students, bird watchers). The chapter focuses on the following aspects of our research: issues involved in using smart phones as sensors; the overall framework for data acquisition, data quality control, data management and analysis; current and future applications of the smart phone-based sensor network, and our future research directions.

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.

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.