935 resultados para point-to-segment algorithm


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A new control algorithm using parallel braking resistor (BR) and serial fault current limiter (FCL) for power system transient stability enhancement is presented in this paper. The proposed control algorithm can prevent transient instability during first swing by immediately taking away the transient energy gained in faulted period. It can also reduce generator oscillation time and efficiently make system back to the post-fault equilibrium. The algorithm is based on a new system energy function based method to choose optimal switching point. The parallel BR and serial FCL resistor can be switched at the calculated optimal point to get the best control result. This method allows optimum dissipation of the transient energy caused by disturbance so to make system back to equilibrium in minimum time. Case studies are given to verify the efficiency and effectiveness of this new control algorithm.

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AMS subject classification: 90B80.

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As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

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There is a growing evidence-base in the epidemiological literature that demonstrates significant associations between people’s living circumstances – including their place of residence – and their health-related practices and outcomes (Leslie, 2005; Karpati, Bassett, & McCord, 2006; Monden, Van Lenthe, & Mackenbach, 2006; Parkes & Kearns, 2006; Cummins, Curtis, Diez-Roux, & Macintyre, 2007; Turrell, Kavanagh, Draper, & Subramanian, 2007). However, these findings raise questions about the ways in which living places, such as households and neighbourhoods, figure in the pathways connecting people and health (Frolich, Potvin, Chabot, & Corin, 2002; Giles-Corti, 2006; Brown et al, 2006; Diez Roux, 2007). This thesis addressed these questions via a mixed methods investigation of the patterns and processes connecting people, place, and their propensity to be physically active. Specifically, the research in this thesis examines a group of lower-socioeconomic residents who had recently relocated from poorer suburbs to a new urban village with a range of health-related resources. Importantly, the study contrasts their historical relationship with physical activity with their reactions to, and everyday practices in, a new urban setting designed to encourage pedestrian mobility and autonomy. The study applies a phenomenological approach to understanding living contexts based on Berger and Luckman’s (1966) conceptual framework in The Social Construction of Reality. This framework enables a questioning of the concept of context itself, and a treatment of it beyond environmental factors to the processes via which experiences and interactions are made meaningful. This approach makes reference to people’s histories, habituations, and dispositions in an exploration between social contexts and human behaviour. This framework for thinking about context is used to generate an empirical focus on the ways in which this residential group interacts with various living contexts over time to create a particular construction of physical activity in their lives. A methodological approach suited to this thinking was found in Charmaz’s (1996; 2001; 2006) adoption of a social constructionist approach to grounded theory. This approach enabled a focus on people’s own constructions and versions of their experiences through a rigorous inductive method, which provided a systematic strategy for identifying patterns in the data. The findings of the study point to factors such as ‘childhood abuse and neglect’, ‘early homelessness’, ‘fear and mistrust’, ‘staying indoors and keeping to yourself’, ‘conflict and violence’, and ‘feeling fat and ugly’ as contributors to an ongoing core category of ‘identity management’, which mediates the relationship between participants’ living contexts and their physical activity levels. It identifies barriers at the individual, neighbourhood, and broader ecological levels that prevent this residential group from being more physically active, and which contribute to the ways in which they think about, or conceptualise, this health-related behaviour in relationship to their identity and sense of place – both geographic and societal. The challenges of living well and staying active in poorer neighbourhoods and in places where poverty is concentrated were highlighted in detail by participants. Participants’ reactions to the new urban neighbourhood, and the depth of their engagement with the resources present, are revealed in the context of their previous life-experiences with both living places and physical activity. Moreover, an understanding of context as participants’ psychological constructions of various social and living situations based on prior experience, attitudes, and beliefs was formulated with implications for how the relationship between socioeconomic contextual effects on health are studied in the future. More detailed findings are presented in three published papers with implications for health promotion, urban design, and health inequalities research. This thesis makes a substantive, conceptual, and methodological contribution to future research efforts interested in how physical activity is conceptualised and constructed within lower socioeconomic living contexts, and why this is. The data that was collected and analysed for this PhD generates knowledge about the psychosocial processes and mechanisms behind the patterns observed in epidemiological research regarding socioeconomic health inequalities. Further, it highlights the ways in which lower socioeconomic living contexts tend to shape dispositions, attitudes, and lifestyles, ultimately resulting in worse health and life chances for those who occupy them.

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People with intellectual disability are a relatively new but growing minority group within Australia's ageing population. Disability policies point to the equal right of people with disabilities to a quality of life similar to that of other citizens. Disability services are increasingly required to provide individualised and responsive services, irrespective of age, for people with lifelong disabilities. The present study explored the everyday lives of older people with intellectual disability in Victoria and Queensland, examining their experiences of using disability services and the ways in which services responded to their ageing. The aim of the study was to inform practice and service development for older people with intellectual disability. The findings suggest that services facilitate important social relationships with other service users and staff. Most older people had a sense of belonging and led busy but directionless lives in two disconnected worlds. Their lives were subject to significant external present-focused control. Yet, despite this, neither services nor family members took responsibility for ensuring their sense of continuity or supporting the development of plans about their future. The experiences described suggest an urgent need for, but significant challenges in the implementation of, holistic indivdualised planning similar to the UK concept of person-centred planning.

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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.

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Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

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Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

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In dynamic and uncertain environments such as healthcare, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. The uncertainty stems from the unpredictability of users’ operational needs as well as their private incentives to misuse permissions. In Role Based Access Control (RBAC), a user’s legitimate access request may be denied because its need has not been anticipated by the security administrator. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. This paper introduces a novel approach to access control under uncertainty and presents it in the context of RBAC. By taking insights from the field of economics, in particular the insurance literature, we propose a formal model where the value of resources are explicitly defined and an RBAC policy (entailing those predictable access needs) is only used as a reference point to determine the price each user has to pay for access, as opposed to representing hard and fast rules that are always rigidly applied.

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The technology and innovation management literature offers somewhat conflicting evidence with regards to the formation of spinoff companies for radically new technologies. Sometimes spinoffs seem to be a very effective strategy—but not always. An obvious question emerges: under what conditions is a spinoff the best way to pursue a radical technology? This paper sheds light on this question by presenting case study evidence from spinoff firms within the Shell Technology Ventures portfolio. The data point to industry clockspeed as a potentially important variable in the decision to create a spinoff or not.

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1. Overview of hotspot identification (HSID)methods 2. Challenges with HSID 3. Bringing crash severity into the ‘mix’ 4. Case Study: Truck Involved Crashes in Arizona 5. Conclusions • Heavy duty trucks have different performance envelopes than passenger cars and have more difficulty weaving, accelerating, and braking • Passenger vehicles have extremely limited sight distance around trucks • Lane and shoulder widths affect truck crash risk more than passenger cars • Using PDOEs to model truck crashes results in a different set of locations to examine for possible engineering and behavioral problems • PDOE models point to higher societal cost locations, whereas frequency models point to higher crash frequency locations • PDOE models are less sensitive to unreported crashes • PDOE models are a great complement to existing practice

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We analyse the electronic portfolio (ePortfolio) in higher education policy and practice. While evangelical accounts of the ePortfolio celebrate its power as a new eLearning technology, we argue that it allows the mutually-reinforcing couple of neoliberalism and the enterprising self to function in ways in which individual difference can be presented, cultured and grown, all the time within a standardised framework which relentlessly polices the limits of the acceptable and unacceptable. We point to the ePortfolio as a practice of (self-) government, arguing that grander policy coalesces out of a halting, experimental set of technological instruments for thinking about how life should be lived.

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Aim The purpose of this study was to examine the relationship between registered nurses’ (RN) job satisfaction and their intention to leave critical care nursing in Saudi Arabia. Background Many studies have identified critical care areas as stressful work environments for nurses and have identified factors contributing to job satisfaction and staff retention. However, very little research has examined these relationships in the Saudi context. Design and Methods This study utilised an exploratory, cross-sectional survey design to examine the relationship between RN job satisfaction and intention to leave at King Abdul-Aziz University Hospital, Saudi Arabia. Respondents completed a self-administered survey including demographic items and validated measures of job satisfaction and intention to leave. A convenience sample of 182 RNs working in critical care areas during the data collection period were included. Results Regression analysis predicting RN intention to leave found that demographic variables including age, parental status and length of ICU experience, and three of the job satisfaction subscales including perceived workload, professional support and pay and prospects for promotion, were significantly associated with the outcome variable. Conclusion This study adds to the existing literature on the relationship between job satisfaction and intention to leave critical care areas among RNs working in Saudi Arabia. These findings point to the need for management and policy interventions targeting nurses’ workloads, professional support and pay and promotion in order to improve nurse retention.

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A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.

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The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.