Channel-aware routing in MANETs with route handoff

In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad-hoc On-Demand Multipath Distance Vector routing protocol (AOMDV) to accommodate channel fading. Specifically, the proposed Channel Aware AOMDV (CA-AOMDV) uses the channel average non-fading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintain reliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiple path system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into the differences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV.

Models of collective cell spreading with variable cell aspect ratio : a motivation for degenerate diffusion models

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multi-scale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (pme). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the pme to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

A novel load transfer scheme for peak load management in rural areas

This paper proposes a novel peak load management scheme for rural areas. The scheme transfers certain customers onto local nonembedded generators during peak load periods to alleviate network under voltage problems. This paper develops and presents this system by way of a case study in Central Queensland, Australia. A methodology is presented for determining the best location for the nonembedded generators as well as the number of generators required to alleviate network problems. A control algorithm to transfer and reconnect customers is developed to ensure that the network voltage profile remains within specification under all plausible load conditions. Finally, simulations are presented to show the performance of the system over a typical maximum daily load profile with large stochastic load variations.

The role of informal networks in providing effective work opportunities for people with an intellectual disability

Being in paid employment is socially valued, and is linked to health, financial security and time use. Issues arising from a lack of occupational choice and control, and from diminished role partnerships are particularly problematic in the lives of people with an intellectual disability. Informal support networks are shown to influence work opportunities for people without disabilities, but their impact on the work experiences of people with disability has not been thoroughly explored. The experience of 'work' and preparation for work was explored with a group of four people with an intellectual disability (the participants) and the key members of their informal support networks (network members) in New South Wales, Australia. Network members and participants were interviewed and participant observations of work and other activities were undertaken. Data analysis included open, conceptual and thematic coding. Data analysis software assisted in managing the large datasets across multiple team members. The insight and actions of network members created and sustained the employment and support opportunities that effectively matched the needs and interests of the participants. Recommendations for future research are outlined.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Use of IEEE 1588-2008 for a sampled value process bus in transmission substations

IEC Technical Committee 57 (TC57) published a series of standards and technical reports for “Communication networks and systems for power utility automation” as the IEC 61850 series. Sampled value (SV) process buses allow for the removal of potentially lethal voltages and damaging currents inside substation control rooms and marshalling kiosks, reduce the amount of cabling required in substations, and facilitate the adoption of non-conventional instrument transformers. IEC 61850-9-2 provides an inter-operable solution to support multi-vendor process bus solutions. A time synchronisation system is required for a SV process bus, however the details are not defined in IEC 61850-9-2. IEEE Std 1588-2008, Precision Time Protocol version 2 (PTPv2), provides the greatest accuracy of network based time transfer systems, with timing errors of less than 100 ns achievable. PTPv2 is proposed by the IEC Smart Grid Strategy Group to synchronise IEC 61850 based substation automation systems. IEC 61850-9-2, PTPv2 and Ethernet are three complementary protocols that together define the future of sampled value digital process connections in substations. The suitability of PTPv2 for use with SV is evaluated, with preliminary results indicating that steady state performance is acceptable (jitter < 300 ns), and that extremely stable grandmaster oscillators are required to ensure SV timing requirements are met when recovering from loss of external synchronisation (such as GPS).

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Non-pharmacological interventions in secondary schizophrenia

Schizophrenia may not be a single disease, but the result of a diverse set of related conditions. Modern neuroscience is beginning to reveal some of the genetic and environmental underpinnings of schizophrenia; however, an approach less well travelled is to examine the medical disorders that produce symptoms resembling schizophrenia. This book is the first major attempt to bring together the diseases that produce what has been termed 'secondary schizophrenia'. International experts from diverse backgrounds ask the questions: does this medical disorder, or drug, or condition cause psychosis? If yes, does it resemble schizophrenia? What mechanisms form the basis of this relationship? What implications does this understanding have for aetiology and treatment? The answers are a feast for clinicians and researchers of psychosis and schizophrenia. They mark the next step in trying to meet the most important challenge to modern neuroscience – understanding and conquering this most mysterious of human diseases.

Performance comparison of VSC-based shunt and series compensators used for load voltage control in distribution systems

In this paper, the performance of voltage-source converter-based shunt and series compensators used for load voltage control in electrical power distribution systems has been analyzed and compared, when a nonlinear load is connected across the load bus. The comparison has been made based on the closed-loop frequency resopnse characteristics of the compensated distribution system. A distribution static compensator (DSTATCOM) as a shunt device and a dynamic voltage restorer (DVR) as a series device are considered in the voltage-control mode for the comparison. The power-quality problems which these compensator address include voltage sags/swells, load voltage harmonic distortions, and unbalancing. The effect of various system parameters on the control performance of the compensator can be studied using the proposed analysis. In particular, the performance of the two compensators are compared with the strong ac supply (stiff source) and weak ac-supply (non-still source) distribution system. The experimental verification of the analytical results derived has been obtained using a laboratory model of the single-phase DSTATCOM and DVR. A generalized converter topology using a cascaded multilevel inverter has been proposed for the medium-voltage distribution system. Simulation studies have been performed in the PSCAD/EMTDC software to verify the results in the three-phase system.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

Preparation of porous calcium phosphate ceramic scaffold in bone tissue engineering

Calcium Phosphate ceramic has been widely used in bone tissue engineering due to its excellent biocompatibility and biodegradability. However, low mechanical properties and biodegradability limit their potential applications. In this project, hydroxyapatite (HA) and calcium phosphate bioglass were used to produce porous tri-calcium phosphate (TCP) bio-ceramic scaffolds. It was found that porous TCP bioceramic could be obtained when 20wt percent bioglass addition and sintered in 1400 degrees celsius for 3 h. Significantly higher compressive strength (9.98 MPa) was achieved in the scaffolds as compared to those produced from tCP power (<3 MPa). The biocompatibility of the scaffold was also estimated.

Interpreting regional frequencies from synchronized phasor measurement in multi-area power systems

In this paper a new approach is proposed for interpreting of regional frequencies in multi machine power systems. The method uses generator aggregation and system reduction based on coherent generators in each area. The reduced system structure is able to be identified and a kalman estimator is designed for the reduced system to estimate the inter-area modes using the synchronized phasor measurement data. The proposed method is tested on a six machine, three area test system and the obtained results show the estimation of inter-area oscillations in the system with a high accuracy.

Innovation networks in the construction arena : the strategic management of mixed enterprises

The building and construction sector is one of the five largest contributors to the Australian economy and is a key performance component in the economy of many other jurisdictions. However, the ongoing viability of this sector is increasingly reliant on its ability to foster and transfer innovated products and practices. Interorganisational networks, which bring together key industry stakeholders and facilitate the flows of information, resources and trust necessary to secure innovation, have emerged as a key growth strategy within this and other arenas. The blending of organisations, resources and purposes creates new, hybrid institutional forms that draw on a mix of contract, structure and interpersonal relationship as integration processes. This paper argues that hybrid networked arrangements, because they incorporate relational elements, require management strategies and techniques that not always synonymous with conventional management approaches, including those used within the building and construction sector. It traces the emergence of the Construction Innovation Project in Australia as a hybrid institutional arrangement moulding public, private and academic stakeholders of the building and construction industry into a coherent collective force aimed at fostering innovation and its application within all levels of the industry. Specifically, the paper examines the Construction Innovation Project to ascertain the impact of relational governance and its management to harness and leverage the skills, resources and capacities of members to secure innovative outcomes. Finally, the paper offers some prospects to guide the ongoing work of this body and any other charged with a similar integrative responsibility.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Textures of optical flow for real-time anomaly detection in crowds

Automated visual surveillance of crowds is a rapidly growing area of research. In this paper we focus on motion representation for the purpose of abnormality detection in crowded scenes. We propose a novel visual representation called textures of optical flow. The proposed representation measures the uniformity of a flow field in order to detect anomalous objects such as bicycles, vehicles and skateboarders; and can be combined with spatial information to detect other forms of abnormality. We demonstrate that the proposed approach outperforms state-of-the-art anomaly detection algorithms on a large, publicly-available dataset.