Signs, symptoms and comorbidities in contact lens-related microbial keratitis

Purpose: The aim of this study was to characterize the clinical signs, symptoms, and ocular and systemic comorbidities in a large case series of contact lens-related microbial keratitis. Methods: Two hundred ninety-seven cases of contact lens-related microbial keratitis, aged between 15 and 64 years were detected through surveillance of hospital and community based ophthalmic practitioners in Australia and New Zealand. Full clinical data were available for 190 cases and 90 were interviewed by telephone. Clinical data included the size, location, and degree of anterior chamber response. Symptom data were available from the practitioner and from participant self-report. Associations between symptoms and disease severity were evaluated. Data on ocular and systemic disease were collected from participants and practitioners. The frequency of comorbidities was compared between the different severities of disease and to population norms. Results: More severe disease was associated with greater symptom severity and pain was the most prevalent symptom reported. Ninety-one percent of cases showed progression of ocular symptoms after lens removal, and symptom progression was associated with all severities of disease. Twenty-five percent of cases reported prior episodes requiring emergency attention. Thyroid disease (p 0.05) and self-reported poor health (p 0.001) were more common in cases compared with age-matched population norms. Discussion: Information on the signs, symptoms, and comorbidities associated with contact lens-related microbial keratitis may be useful in patient education and for practitioners involved in the fitting of lenses and management of complications. Although pain was the most common symptom experienced, progression of symptoms despite lens removal was close to universal. Poor general health, particularly respiratory disease and thyroid disease was more common in cases than in the general population, which may prompt practitioners to recommend flexibility in wear schedules when in poor health or the selection of a lower risk wear schedule in at risk patients

Power management and power flow control with back-to-back converters in a utility connected microgrid

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Flow

This is an entry in an encyclopedia of television which has over 1000 entries. This one by John Hartley is titled "Flow" and begins by attributing the concept of 'flow' to Raymond Williams with TV viewers being persuaded to stay watching by on-screen sequencing.

Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion

In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality.

Obstacle detection using optical flow

Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.

Learning to avoid indoor obstacles from optical flow

Optical flow (OF) is a powerful motion cue that captures the fusion of two important properties for the task of obstacle avoidance − 3D self-motion and 3D environmental surroundings. The problem of extracting such information for obstacle avoidance is commonly addressed through quantitative techniques such as time-to-contact and divergence, which are highly sensitive to noise in the OF image. This paper presents a new strategy towards obstacle avoidance in an indoor setting, using the combination of quantitative and structural properties of the OF field, coupled with the flexibility and efficiency of a machine learning system.The resulting system is able to effectively control the robot in real-time, avoiding obstacles in familiar and unfamiliar indoor environments, under given motion constraints. Furthermore, through the examination of the networks internal weights, we show how OF properties are being used toward the detection of these indoor obstacles.

Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

Virtual force feedback teleoperation of the InsectBot using optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator’s joystick to facilitate collision free teleoperation. Optical flow is measured by a pair of wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. Experimental results are provided on the InsectBot holonomic vehicle platform.

A new framework for force feedback teleoperation of robotic vehicles based on optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator's joystick to facilitate collision free teleoperation. Optic flow is measured by wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. The coupling between optical flow (velocity) and force is modelled as an impedance - in this case an optical impedance. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. The paper focuses on applications to aerial robotics vehicles, however, the ideas apply directly to other force actuated vehicles such as submersibles or space vehicles, and the authors believe the approach has potential for control of terrestrial vehicles and even teleoperation of manipulators. Experimental results are provided for a simulated aerial robot in a virtual environment controlled by a haptic joystick.

Dynamic Image-based visual servo control using centroid and optic flow features

This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

Combined optic-flow and stereo-based navigation of urban canyons for a UAV

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.

Specifying and enforcing a fine-grained information flow policy : model and experiments

In this paper we present a model for defining and enforcing a fine-grained information flow policy. We describe how the policy can be enforced on a typical computer and present experiments using the proposed model. A key feature of the model is that it allows the expression of rules which detail precisely which information elements are allowed to mix together. For example, the model allows the expression of a policy which forbids a doctor from mixing the personal medical details of the patients. The enforcement mechanisms tracks and records information flows within the system so that dynamic changes to the policy can be made with respect to information elements which may have propagated to different locations in the system.

Active flow control bump design using hybrid Nash-game coupled to evolutionary algorithms

In this paper, the optimal design of an active flow control device; Shock Control Bump (SCB) on suction and pressure sides of transonic aerofoil to reduce transonic total drag is investigated. Two optimisation test cases are conducted using different advanced Evolutionary Algorithms (EAs); the first optimiser is the Hierarchical Asynchronous Parallel Evolutionary Algorithm (HAPMOEA) based on canonical Evolutionary Strategies (ES). The second optimiser is the HAPMOEA is hybridised with one of well-known Game Strategies; Nash-Game. Numerical results show that SCB significantly reduces the drag by 30% when compared to the baseline design. In addition, the use of a Nash-Game strategy as a pre-conditioner of global control saves computational cost up to 90% when compared to the first optimiser HAPMOEA.