Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Turning gaming EEG peripherals into trainable brain computer interfaces

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimina tion between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2% for two types of non-linear classifiers.

Submission to the draft Migration Assurance Policy - Improving the transition to the fixed-line national broadband network review

The rights of individuals to self-determination and participation in social, political and economic life are recognised and supported by Articles 1, 3 and 25 of the International Covenant on Civil and Political Rights 1966.4 Article 1 of the United Nations’ Human Rights Council’s Resolution on the Promotion and Protection of Human Rights on the Internet of July 2012 confirms individuals have the same rights online as offline. Access to the internet is essential and as such the UN: Calls upon all States to promote and facilitate access to the Internet and international cooperation aimed at the development of media and information and communications facilities in all countries (Article 3) Accordingly, access to the internet per se is a fundamental human right, which requires direct State recognition and support.5 The obligations of the State to ensure its citizens are able, and are enabled, to access the internet, are not matters that should be delegated to commercial parties. Quite simply – access to the internet, and high-speed broadband, by whatever means are “essential services” and therefore “should be treated as any other utility service”...

Comparative genomic analysis of human Chlamydia pneumoniae isolates from respiratory, brain and cardiac tissues

Chlamydia pneumoniae is an obligate intracellular bacterium implicated in a wide range of human diseases including atherosclerosis and Alzheimer's disease. Efforts to understand the relationships between C. pneumoniae detected in these diseases have been hindered by the availability of sequence data for non-respiratory strains. In this study, we sequenced the whole genomes for C. pneumoniae isolates from atherosclerosis and Alzheimer's disease, and compared these to previously published C. pneumoniae genomes. Phylogenetic analyses of these new C. pneumoniae strains indicate two sub-groups within human C. pneumoniae, and suggest that both recombination and mutation events have driven the evolution of human C. pneumoniae. Further fine-detailed analyses of these new C. pneumoniae sequences show several genetically variable loci. This suggests that similar strains of C. pneumoniae are found in the brain, lungs and cardiovascular system and that only minor genetic differences may contribute to the adaptation of particular strains in human disease.

Building instance knowledge network for word sense disambiguation

In this paper, a new high precision focused word sense disambiguation (WSD) approach is proposed, which not only attempts to identify the proper sense for a word but also provides the probabilistic evaluation for the identification confidence at the same time. A novel Instance Knowledge Network (IKN) is built to generate and maintain semantic knowledge at the word, type synonym set and instance levels. Related algorithms based on graph matching are developed to train IKN with probabilistic knowledge and to use IKN for probabilistic word sense disambiguation. Based on the Senseval-3 all-words task, we run extensive experiments to show the performance enhancements in different precision ranges and the rationality of probabilistic based automatic confidence evaluation of disambiguation. We combine our WSD algorithm with five best WSD algorithms in senseval-3 all words tasks. The results show that the combined algorithms all outperform the corresponding algorithms.

Measurement of transit network accessibility based on access stop choice behaviour

This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.

Stabilization of exotic minority phases in a multicomponent self-assembled molecular network

Trimesic acid (TMA) and alcohols were recently shown to self-assemble into a stable, two-component linear pattern at the solution/highly oriented pyrolytic graphite (HOPG) interface. Away from equilibrium, the TMA/alcohol self-assembled molecular network (SAMN) can coexist with pure-TMA networks. Here, we report on some novel characteristics of these non-equilibrium TMA structures, investigated by scanning tunneling microscopy (STM). We observe that both the chicken-wire and flower-structure TMA phases can host 'guest' C60 molecules within their pores, whereas the TMA/alcohol SAMN does not offer any stable adsorption sites for the C60 molecules. The presence of the C60 molecules at the solution/solid interface was found to improve the STM image quality. We have taken advantage of the high-quality imaging conditions to observe unusual TMA bonding geometries at domain boundaries in the TMA/alcohol SAMN. Boundaries between aligned TMA/alcohol domains can give rise to doubled TMA dimer rows in two different configurations, as well as a tripled-TMA row. The boundaries created between non-aligned domains can create geometries that stabilize TMA bonding configurations not observed on surfaces without TMA/alcohol SAMNs, including small regions of the previously predicted 'super flower' TMA bonding geometry and a tertiary structure related to the known TMA phases. These structures are identified as part of a homologic class of TMA bonding motifs, and we explore some of the reasons for the stabilization of these phases in our multicomponent system.

Materials and technologies for energy conversion, saving and storage: A global network enabling capacity-building for sustainable energy in developing countries

Access to energy is a fundamental component of poverty abatement. People who live in homes without electricity are often dependent on dirty, time-consuming and disproportionately expensive solid fuel sources for heating and cooking. [1] In developing countries, the Human Development Index (HDI), which comprises measures of standard of living, longevity and educational attainment, increases rapidly with per capita electricity use. [2] For these reasons the United Nations has been making a concerted effort to promote global access to energy, first by naming 2012 the Year of Sustainable Energy for All, [3] and now by declaring 2014-2024 the Decade of Sustainable Energy for All. [4]

From “somatic scandals” to “a constant potential for violence”? The culture of dissection, brain-based learning, and the rewriting/rewiring of “the child”

This article analyzes the “messy and numberless beginnings” of the hope placed upon neurological foundationalism to provide a solution to the “problem” of differences between students and to the achievement of educational goals. Rather than arguing for or against educational neuroscience, the article moves through five levels to examine the conditions of possibility for subscribing to the brain as a causal organological locus of learning.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

The experience of forging new emergency nursing curriculum development, through a course advisory network

Queensland University of Technology (QUT), School of Nursing (SoN), has offered a postgraduate Graduate Certificate in Emergency Nursing since 2003, for registered nurses practising in an emergency clinical area, who fulfil key entry criteria. Feedback from industry partners and students evidenced support for flexible and extended study pathways in emergency nursing. Therefore, in the context of a growing demand for emergency health services and the need for specialist qualified staff, it was timely to review and redevelop our emergency specialist nursing courses. The QUT postgraduate emergency nursing study area is supported by a course advisory group, whose aim is to provide input and focus development of current and future course planning. All members of the course advisory were invited to form an expert panel to review current emergency course documents. A half day “brainstorm session”, planning and development workshop was held to review the emergency courses to implement changes from 2009. Results from the expert panel planning day include: proposal for a new emergency specialty unit; incorporation of the College of Emergency Nurses (CENA) Standards for Emergency Nursing Specialist in clinical assessment; modification of the present core emergency unit; enhancing the focus of the two other units that emergency students undertake; and opening the emergency study area to the Graduate Diploma in Nursing (Emergency Nursing) and Master of Nursing (Emergency Nursing). The conclusion of the brainstorm session resulted in a clearer conceptualisation, of the study pathway for students. Overall, the expert panel group of enthusiastic emergency educators and clinicians provided viable options for extending the career progression opportunities for emergency nurses. In concluding, the opportunity for collaboration across university and clinical settings has resulted in the design of a course with exciting potential and strong clinical relevance.

MEG Adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses

An unresolved goal in face perception is to identify brain areas involved in face processing and simultaneously understand the timing of their involvement. Currently, high spatial resolution imaging techniques identify the fusiform gyrus as subserving processing of invariant face features relating to identity. High temporal resolution imaging techniques localize an early latency evoked component—the N/M170—as having a major generator in the fusiform region; however, this evoked component is not believed to be associated with the processing of identity. To resolve this, we used novel magnetoencephalographic beamformer analyses to localize cortical regions in humans spatially with trial-by-trial activity that differentiated faces and objects and to interrogate their functional sensitivity by analyzing the effects of stimulus repetition. This demonstrated a temporal sequence of processing that provides category-level and then item-level invariance. The right fusiform gyrus showed adaptation to faces (not objects) at ∼150 ms after stimulus onset regardless of face identity; however, at the later latency of ∼200–300 ms, this area showed greater adaptation to repeated identity faces than to novel identities. This is consistent with an involvement of the fusiform region in both early and midlatency face-processing operations, with only the latter showing sensitivity to invariant face features relating to identity.

Oxygen transport in a three-dimensional microvascular network incorporated with early tumour growth and preexisting vessel cooption: Numerical simulation study

We propose a dynamic mathematical model of tissue oxygen transport by a preexisting three-dimensional microvascular network which provides nutrients for an in situ cancer at the very early stage of primary microtumour growth. The expanding tumour consumes oxygen during its invasion to the surrounding tissues and cooption of host vessels. The preexisting vessel cooption, remodelling and collapse are modelled by the changes of haemodynamic conditions due to the growing tumour. A detailed computational model of oxygen transport in tumour tissue is developed by considering (a) the time-varying oxygen advection diffusion equation within the microvessel segments, (b) the oxygen flux across the vessel walls, and (c) the oxygen diffusion and consumption with in the tumour and surrounding healthy tissue. The results show the oxygen concentration distribution at different time points of early tumour growth. In addition, the influence of preexisting vessel density on the oxygen transport has been discussed. The proposed model not only provides a quantitative approach for investigating the interactions between tumour growth and oxygen delivery, but also is extendable to model other molecules or chemotherapeutic drug transport in the future study.