Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

QoS differentiation in IEEE 802.11 wireless local area networks for real-time control

IEEE 802.11 based wireless local area networks (WLANs) are being increasingly deployed for soft real-time control applications. However, they do not provide quality-ofservice (QoS) differentiation to meet the requirements of periodic real-time traffic flows, a unique feature of real-time control systems. This problem becomes evident particularly when the network is under congested conditions. Addressing this problem, a media access control (MAC) scheme, QoS-dif, is proposed in this paper to enable QoS differentiation in IEEE 802.11 networks for different types of periodic real-time traffic flows. It extends the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) by introducing a QoS differentiation method to deal with different types of periodic traffic that have different QoS requirements for real-time control applications. The effectiveness of the proposed QoS-dif scheme is demonstrated through comparisons with the IEEE 802.11e EDCA mechanism.

A proposed Australian industrial control system security curriculum

The security of industrial control systems in critical infrastructure is a concern for the Australian government and other nations. There is a need to provide local Australian training and education for both control system engineers and information technology professionals. This paper proposes a postgraduate curriculum of four courses to provide knowledge and skills to protect critical infrastructure industrial control systems. Our curriculum is unique in that it provides security awareness but also the advanced skills required for security specialists in this area. We are aware that in the Australian context there is a cultural gap between the thinking of control system engineers who are responsible for maintaining and designing critical infrastructure and information technology professionals who are responsible for protecting these systems from cyber attacks. Our curriculum aims to bridge this gap by providing theoretical and practical exercises that will raise the awareness and preparedness of both groups of professionals.

Cell death control : the interplay of apoptosis and autophagy in the pathogenicity of sclerotinia sclerotiorum

Programmed cell death is characterized by a cascade of tightly controlled events that culminate in the orchestrated death of the cell. In multicellular organisms autophagy and apoptosis are recognized as two principal means by which these genetically determined cell deaths occur. During plant-microbe interactions cell death programs can mediate both resistant and susceptible events. Via oxalic acid (OA), the necrotrophic phytopathogen Sclerotinia sclerotiorum hijacks host pathways and induces cell death in host plant tissue resulting in hallmark apoptotic features in a time and dose dependent manner. OA-deficient mutants are non-pathogenic and trigger a restricted cell death phenotype in the host that unexpectedly exhibits markers associated with the plant hypersensitive response including callose deposition and a pronounced oxidative burst, suggesting the plant can recognize and in this case respond, defensively. The details of this plant directed restrictive cell death associated with OA deficient mutants is the focus of this work. Using a combination of electron and fluorescence microscopy, chemical effectors and reverse genetics, we show that this restricted cell death is autophagic. Inhibition of autophagy rescued the non-pathogenic mutant phenotype. These findings indicate that autophagy is a defense response in this necrotrophic fungus/plant interaction and suggest a novel function associated with OA; namely, the suppression of autophagy. These data suggest that not all cell deaths are equivalent, and though programmed cell death occurs in both situations, the outcome is predicated on who is in control of the cell death machinery. Based on our data, we suggest that it is not cell death per se that dictates the outcome of certain plant-microbe interactions, but the manner by which cell death occurs that is crucial.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

Sample selection in a model of female labour supply : an alternative approach

Suggests an alternative and computationally simpler approach of non-random sampling of labour economics and represents an observed outcome of an individual female′s choice of whether or not to participate in the labour market. Concludes that there is an alternative to the Heckman two-step estimator.

Alternative modes of entrepreneurial opportunity exploitation : the case on inter-organizational project

While entrepreneurship research has taken firm formation to be the predominant mode of opportunity exploitation, entrepreneurship can take place through many other types of organizational arrangements. In the present article, we consider one such alternative arrangement, namely the formation of inter-organizational projects (IOPs). We propose a multi-level contingency model that suggests that uncertainty both at the level of the firm and at the level of the environment makes the exploitation of opportunities through IOPs more likely. The model is tested by telephone survey data collected amongst a panel of 1725 SMEs and longitudinal industry data. Our findings provide strong support for the industry-level part of the model, but interestingly, only partial support for the firm level part of the model. This indicates that the effects of uncertainty need to be dissected into different levels of analysis to understand the conditions under which alternative modes of opportunity exploitation can be a prominent entrepreneurial alternative to new firm formation.

Benefiting white noise in developing feedforward active noise control systems

In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.

Binocular rivalry and visuospatial ability in individuals with schizophrenia

Visual abnormalities, both at the sensory input and the higher interpretive levels, have been associated with many of the symptoms of schizophrenia. Individuals with schizophrenia typically experience distortions of sensory perception, resulting in perceptual hallucinations and delusions that are related to the observed visual deficits. Disorganised speech, thinking and behaviour are commonly experienced by sufferers of the disorder, and have also been attributed to perceptual disturbances associated with anomalies in visual processing. Compounding these issues are marked deficits in cognitive functioning that are observed in approximately 80% of those with schizophrenia. Cognitive impairments associated with schizophrenia include: difficulty with concentration and memory (i.e. working, visual and verbal), an impaired ability to process complex information, response inhibition and deficits in speed of processing, visual and verbal learning. Deficits in sustained attention or vigilance, poor executive functioning such as poor reasoning, problem solving, and social cognition, are all influenced by impaired visual processing. These symptoms impact on the internal perceptual world of those with schizophrenia, and hamper their ability to navigate their external environment. Visual processing abnormalities in schizophrenia are likely to worsen personal, social and occupational functioning. Binocular rivalry provides a unique opportunity to investigate the processes involved in visual awareness and visual perception. Binocular rivalry is the alternation of perceptual images that occurs when conflicting visual stimuli are presented to each eye in the same retinal location. The observer perceives the opposing images in an alternating fashion, despite the sensory input to each eye remaining constant. Binocular rivalry tasks have been developed to investigate specific parts of the visual system. The research presented in this Thesis provides an explorative investigation into binocular rivalry in schizophrenia, using the method of Pettigrew and Miller (1998) and comparing individuals with schizophrenia to healthy controls. This method allows manipulations to the spatial and temporal frequency, luminance contrast and chromaticity of the visual stimuli. Manipulations to the rival stimuli affect the rate of binocular rivalry alternations and the time spent perceiving each image (dominance duration). Binocular rivalry rate and dominance durations provide useful measures to investigate aspects of visual neural processing that lead to the perceptual disturbances and cognitive dysfunction attributed to schizophrenia. However, despite this promise the binocular rivalry phenomenon has not been extensively explored in schizophrenia to date. Following a review of the literature, the research in this Thesis examined individual variation in binocular rivalry. The initial study (Chapter 2) explored the effect of systematically altering the properties of the stimuli (i.e. spatial and temporal frequency, luminance contrast and chromaticity) on binocular rivalry rate and dominance durations in healthy individuals (n=20). The findings showed that altering the stimuli with respect to temporal frequency and luminance contrast significantly affected rate. This is significant as processing of temporal frequency and luminance contrast have consistently been demonstrated to be abnormal in schizophrenia. The current research then explored binocular rivalry in schizophrenia. The primary research question was, "Are binocular rivalry rates and dominance durations recorded in participants with schizophrenia different to those of the controls?" In this second study binocular rivalry data that were collected using low- and highstrength binocular rivalry were compared to alternations recorded during a monocular rivalry task, the Necker Cube task to replicate and advance the work of Miller et al., (2003). Participants with schizophrenia (n=20) recorded fewer alternations (i.e. slower alternation rates) than control participants (n=20) on both binocular rivalry tasks, however no difference was observed between the groups on the Necker cube task. Magnocellular and parvocellular visual pathways, thought to be abnormal in schizophrenia, were also investigated in binocular rivalry. The binocular rivalry stimuli used in this third study (Chapter 4) were altered to bias the task for one of these two pathways. Participants with schizophrenia recorded slower binocular rivalry rates than controls in both binocular rivalry tasks. Using a ‘within subject design’, binocular rivalry data were compared to data collected from a backwardmasking task widely accepted to bias both these pathways. Based on these data, a model of binocular rivalry, based on the magnocellular and parvocellular pathways that contribute to the dorsal and ventral visual streams, was developed. Binocular rivalry rates were compared with performance on the Benton’s Judgment of Line Orientation task, in individuals with schizophrenia compared to healthy controls (Chapter 5). The Benton’s Judgment of Line Orientation task is widely accepted to be processed within the right cerebral hemisphere, making it an appropriate task to investigate the role of the cerebral hemispheres in binocular rivalry, and to investigate the inter-hemispheric switching hypothesis of binocular rivalry proposed by Pettigrew and Miller (1998, 2003). The data were suggestive of intra-hemispheric rather than an inter-hemispheric visual processing in binocular rivalry. Neurotransmitter involvement in binocular rivalry, backward masking and Judgment of Line Orientation in schizophrenia were investigated using a genetic indicator of dopamine receptor distribution and functioning; the presence of the Taq1 allele of the dopamine D2 receptor (DRD2) receptor gene. This final study (Chapter 6) explored whether the presence of the Taq1 allele of the DRD2 receptor gene, and thus, by inference the distribution of dopamine receptors and dopamine function, accounted for the large individual variation in binocular rivalry. The presence of the Taq1 allele was associated with slower binocular rivalry rates or poorer performance in the backward masking and Judgment of Line Orientation tasks seen in the group with schizophrenia. This Thesis has contributed to what is known about binocular rivalry in schizophrenia. Consistently slower binocular rivalry rates were observed in participants with schizophrenia, indicating abnormally-slow visual processing in this group. These data support previous studies reporting visual processing abnormalities in schizophrenia and suggest that a slow binocular rivalry rate is not a feature specific to bipolar disorder, but may be a feature of disorders with psychotic features generally. The contributions of the magnocellular or dorsal pathways and parvocellular or ventral pathways to binocular rivalry, and therefore to perceptual awareness, were investigated. The data presented supported the view that the magnocellular system initiates perceptual awareness of an image and the parvocellular system maintains the perception of the image, making it available to higher level processing occurring within the cortical hemispheres. Abnormal magnocellular and parvocellular processing may both contribute to perceptual disturbances that ultimately contribute to the cognitive dysfunction associated with schizophrenia. An alternative model of binocular rivalry based on these observations was proposed.

Image based visual servo control for fixed wing UAVs tracking linear infrastructure in wind

This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

Compaction control of topography and fault network structure along strike-slip faults in sedimentary basins

Strike-slip faults commonly display structurally complex areas of positive or negative topography. Understanding the development of such areas has important implications for earthquake studies and hydrocarbon exploration. Previous workers identified the key factors controlling the occurrence of both topographic modes and the related structural styles. Kinematic and stress boundary conditions are of first-order relevance. Surface mass transport and material properties affect fault network structure. Experiments demonstrate that dilatancy can generate positive topography even under simple-shear boundary conditions. Here, we use physical models with sand to show that the degree of compaction of the deformed rocks alone can determine the type of topography and related surface fault network structure in simple-shear settings. In our experiments, volume changes of ∼5% are sufficient to generate localized uplift or subsidence. We discuss scalability of model volume changes and fault network structure and show that our model fault zones satisfy geometrical similarity with natural flower structures. Our results imply that compaction may be an important factor in the development of topography and fault network structure along strike-slip faults in sedimentary basins.

3D thermal mapping of building interiors using an RGB-D and thermal camera

The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.