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.

PDMS spreading morphological patterns on substrates of different hydrophilicity in air vacuum and water

In paper has been to investigate the morphological patterns and kinetics of PDMS spreading on silicon wafer using combination of techniques like ellipsometry, atomic force microscope (AFM), scanning electron microscope (SEM) and optical microscopy. A macroscopic silicone oil drops as well as PDMS water based emulsions were studied after deposition on a flat surface of silicon wafer in air, water and vacuum. our own measurements using an imaging ellipsometer, which also clearly shows the presence of a precursor film. The diffusion constant of this film, measured with a 60 000 cS PDMS sample spreading on a hydrophilic silicon wafer, is Df = 1.4  10-11 m2/s. Regardless of their size, density and method of deposition, droplets on both types of wafer (hydrophilic and hydrophobic) flatten out over a period of many hours, up to 3 days. During this process neighbouring droplets may coalesce, but there is strong evidence that some of the PDMS from the droplets migrates into a thin, continuous film that covers the surface in between droplets. The thin film appears to be ubiquitous if there has been any deposition of PDMS. However, this statement needs further verification. One question is whether the film forms immediately after forced drying, or whether in some or all cases it only forms by spreading from isolated droplets as they slowly flatten out.

Patterns of engagement in workplace learning amongst employees from social sectors

Continuous learning and development has become increasingly important in the information age. However, employees with limited formal education in lower status occupations may be disadvantaged in their opportunities for development, as their jobs tend to require more limited knowledge and skills. In mature age, such workers may be subject to cumulative disadvantage with respect to work related learning and development, as well as negative stereotyping. This thesis concerns work related learning and development from a lifespan development psychology perspective. Development across the lifespan is grounded in biocultural co-constructivism. That is, the reciprocal influences of the individual and environment produce change in the individual. Existing theories and models of adaptive development attempt to explain how developmental resources are allocated across the lifespan. These included the Meta- theory of Selective Optimisation with Compensation, Dual Process Model of Self Regulation, and Developmental Regulation via Optimisation and Primary and Secondary Control. These models were integrated to create the Model of Adaptive Development for Work Related Learning. The Learning and Development Survey (LDS) was constructed to measure the hypothesised processes of adaptive development for work related learning, which were individual goal selection, individual goal engagement, individual goal disengagement, organisational opportunities (selection and engagement), and organisational constraints. Data collection was undertaken in two phases: the pilot study and the main study. The objective of the pilot study was to test the LDS on a target population of 112 employees from a local government organisation. Exploratory factor analysis reduced the pilot version of the survey to 38 items encompassing eight constructs which covered the processes of the model of adaptive development for work related learning. In the main study, the Revised Learning and Development Survey (R-LDS) was administered to another group of 137 employees from the local government organisation, as well as 110 employees from a private healthcare organisation. The purpose of the main study was to validate the R-LDS on two different groups to provide evidence of stability, and compare survey scores according to age and occupational status to determine construct validity. Findings from the main study indicated that only four constructs of the R-LDS were stable, which were organisational opportunities – selection, individual goal engagement, organisational constraints – disengagement and organisational opportunities – engagement. In addition, MANOVA studies revealed that the demographic variables affected organisational opportunities and constraints in the workplace, although individual goal engagement was not influenced by age. The findings from the pilot and main study partially supported the model of adaptive development for work related learning. Given that only four factors displayed adequate reliability in terms of internal consistency and stability, the findings suggest that individual goal selection and individual goal disengagement are less relevant to work related learning and development. Some recent research which emerged during the course of the current study has suggested that individual goal selection and individual goal disengagement are more relevant when goal achievement is impeded by biological constraints such as ageing. However, correlations between the retained factors support the model of adaptive development for work related learning, and represent the role of biocultural co-constructivism in development. Individual goal engagement was positively correlated with both opportunity factors (selection and engagement), while organisational constraints – disengagement was negatively correlated with organisational opportunities – selection. Demographic findings indicated that higher occupational status was associated with more opportunities for development. Age was associated with fewer opportunities or greater constraints for development, especially for lower status workers.

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.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Investigating the patterns and determinants of life satisfaction in Germany following reunification

This paper investigates the patterns and determinants of life satisfaction in Germany following reunification. We implement a new fixed-effect estimator for ordinal life satisfaction in the German Socio-Economic Panel and find negative effects on life satisfaction from being recently fired, losing a spouse through either death or separation, and time spent in hospital, while we find strong positive effects from income and marriage. Using a new causal decomposition technique, we find that East Germans experienced a continued improvement in life satisfaction to which increased household incomes contributed around 12 percent. Most of the improvement is explained by better average circumstances, such as greater political freedom. For West Germans, we find little change in average life satisfaction over this period.

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.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

Patterns, correlates, and prognostic significance of quality of life following breast cancer

Objective To describe quality of life (QOL) over a 12-month period among women with breast cancer, consider the association between QOL and overall survival (OS), and explore characteristics associated with QOL declines. Methods A population-based sample of Australian women (n=287) with invasive, unilateral breast cancer (Stage I+), was observed prospectively for a median of 6.6 years. QOL was assessed at six, 12 and 18 months post-diagnosis, using the Functional Assessment of Cancer Therapy, Breast (FACT-B+4) questionnaire. Raw scores for the FACT-B+4 and subscales were computed and individuals were categorized according to whether QOL declined, remained stable or improved between six and 18 months. Kaplan-Meier and Cox proportional hazards survival methods were used to estimate OS and its associations with QOL. Logistic regression models identified factors associated with QOL decline. Results Within FACT-B+4 sub-scales, between 10% and 23% of women showed declines in QOL. Following adjustment for established prognostic factors, emotional wellbeing and FACT-B+4 scores at six months post-diagnosis were associated with OS (p<0.05). Declines in physical (p<0.01) or functional (p=0.02) well-being between six and 18 months post-diagnosis were also associated significantly with OS. Receiving multiple forms of adjuvant treatment, a perception of not handling stress well and reporting one or more other major life events at six months post-diagnosis were factors associated with declines in QOL in multivariable analyses. Conclusions Interventions targeted at preventing QOL declines may ultimately improve quantity as well as quality of life following breast cancer.

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.