978 resultados para Edge detectors


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First-principles computational studies indicate that (B, N, or O)-doped graphene ribbon edges can substantially reduce the energy barrier for H2 dissociative adsorption. The low barrier is competitive with many widely used metal or metal oxide catalysts. This suggests that suitably functionalized graphene architectures are promising metal-free alternatives for low-cost catalytic processes.

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Accuracy of dose delivery in external beam radiotherapy is usually verified with electronic portal imaging (EPI) in which the treatment beam is used to check the positioning of the patient. However the resulting megavoltage x-ray images suffer from poor quality. The image quality can be improved by developing a special operating mode in the linear accelerator. The existing treatment beam is modified such that it produces enough low-energy photons for imaging. In this work the problem of optimizing the beam/detector combination to achieve optimal electronic portal image quality is addressed. The linac used for this study was modified to produce two experimental photon beams. These beams, named Al6 and Al10, were non-flat and were produced by 4MeV electrons hitting aluminum targets, 6 and 10mm thick respectively. The images produced by a conventional EPI system (6MV treatment beam and camera-based EPID with a Cu plate & Gd2O2S screen ) were compared with the images produced by the experimental beams and various screens with the same camera). The contrast of 0.8cm bone equivalent material in 5 cm water increased from 1.5% for the conventional system to 11% for the combination of Al6 beam with a 200mg/cm2 Gd2O2S screen. The signal-to-noise ratio calculated for 1cGy flood field images increased by about a factor of two for the same EPI systems. The spatial resolution of the two imaging systems was comparable. This work demonstrates that significant improvements in portal image contrast can be obtained by simultaneous optimization of the linac spectrum and EPI detector.

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The purpose of this paper is to investigate the edge condition between the digital layers and the physical layers of the city and how tangible expressions of the interrelationships between them to create and define new experiences of place, creating hybrid place. To date there has been discussion and investigation into understanding the importance of place, similarly into defining hybrid space. This paper explores principles of place and space to question how they can be applied into defining and proposing the notion of hybrid place in urban environments. The integration of media spaces into architecture provide infrastructure for the development of hybrid place. The physical boundaries of urban spaces become blurred through the integration of media such as computer technologies connecting the physical environment with the digital. Literature and case studies that reflect the current trends of use of technology by people in space and place within urban environments are examined.

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Neo-angiogenesis during neoplastic growth involves endothelial mitogenic and migration stimuli produced by cancer or tumour stromal cells. Although this active angiogenesis takes place in the tumour periphery, the process of vessel growth and survival in inner areas and its clinical role remain largely unexplored. The present study compared the microvessel score (MS) as well as the single endothelial cell score (ECS) in the invading edge and in inner areas of non-small cell lung carcinomas (NSCLCs). Three different patterns of vascular growth were distinguished: the edvin (edge vs. inner) type 1, where a low MS was observed in both peripheral and inner tumour areas; the edvin type 2, where a high MS was noted in the invading front but a low MS in inner areas; and the edvin type 3, where both peripheral and inner tumour areas had a high MS. The ECS was high in the invading edge in edvin type 2 and 3 cases and was sharply decreased in both types in inner areas, suggesting that endothelial cell migration is unlikely to contribute to the angiogenic process in areas away from the tumour front. Expression of the vascular endothelial growth factor (VEGF) and of thymidine phosphorylase (TP) was associated with a high MS in the invading edge. VEGF was associated with a high MS in inner areas (edvin 3), while TP expression was associated with edvin type 2, showing that VEGF (and not TP) contributes to the preservation of the inner vasculature. Both edvin type 2 and 3 cases showed an increased incidence of node metastasis, but edvin type 3 cases had a poorer prognosis, even in the N1-stage group. The present study suggests that tumour factors regulating angiogenesis and vascular survival are not identical. A possible method is reported to quantify these two parameters by comparing the MS in the invading edge and inner areas (edvin types). This observation may contribute to the evaluation of the effectiveness of different therapeutic approaches, namely vascular targeting vs. anti-angiogenesis. Copyright (C) 2000 John Wiley and Sons, Ltd.

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Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

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The Australian Government’s Skills for the Carbon Challenge (SCC) initiative aims to accelerate industry and the education sectors response to climate change. As part of the SCC initiative, the Department of Industry, Innovation, Climate Change, Science, Research and Tertiary Education (DIICCSRTE) provided funding to investigate the state of energy efficiency education in engineering-related Australian Technical and Further Education (TAFE) Programs. The following document reports on the outcomes of a multi-stage consultation project that engaged with participants from over 80% of TAFE institutions across Australia with the aim of supporting and enhancing future critical skills development in this area. Specifically, this report presents the findings of a national survey, based on a series of TAFE educator focus groups, conducted in May 2013 aimed at understanding the experiences and insights of Australian TAFE educators teaching engineering-related courses. Responses were received from 224 TAFE Educators across 50 of the 61 TAFE institutions in Australia (82% response rate).

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Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity $D$, and the cell proliferation rate �$\lambda$. Scratch assays are a commonly-reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched and the motion of the front is monitored over a short period of time, often less than 24 hours. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Leading edge data is very convenient since, unlike other methods, it is nondestructive and does not require labeling, tracking or counting individual cells amongst the population. In this work we study short time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allows us to reliably identify $D$ and $\lambda$�. Using a naıve calibration approach where we simply scan the relevant region of the ($D$;$\lambda$�) parameter space, we show that there are many choices of $D$ and $\lambda$� for which our model produces indistinguishable short time leading edge data. Therefore, without due care, it is impossible to estimate $D$ and $\lambda$� from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information we divide the duration of the experiment into two periods, and we estimate $D$ using data from the first period, while we estimate �$\lambda$ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of $D$ and $\lamdba$� that are consistent with previously-reported values except that that our approach is fast, inexpensive, nondestructive and avoids the need for cell labeling and cell counting.

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The formation of clearly separated vertical graphenenanosheets on silicon nanograss support is demonstrated. The plasma-enabled, two-stage mask-free process produced self-organized vertical graphenes of a few carbon layers (as confirmed by advanced microanalysis), prominently oriented in the substrate center–substrate edge direction. It is shown that the width of the alignment zone depends on the substrate conductivity, and thus the electric field in the vicinity of the growth surface is responsible for the graphene alignment. This finding is confirmed by the Monte Carlo simulations of the ion flux distribution in the silicon nanograss pattern.

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Plasma-aided nanofabrication is a rapidly expanding area of research spanning disciplines ranging from physics and chemistry of plasmas and gas discharges to solid state physics, materials science, surface science, nanoscience and nanotechnology and related engineering subjects. The current status of the research field is discussed and examples of superior performance and competitive advantage of plasma processes and techniques are given. These examples are selected to represent a range of applications of two major types of plasmas suitable for nanoscale synthesis and processing, namely thermally non-equilibrium and thermal plasmas. Major concepts and terminology used in the field are introduced. The paper also pinpoints the major challenges facing plasma-aided nanofabrication and identifies some emerging topics for future research. © 2007 IOP Publishing Ltd.

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Purpose Two diodes which do not require correction factors for small field relative output measurements are designed and validated using experimental methodology. This was achieved by adding an air layer above the active volume of the diode detectors, which canceled out the increase in response of the diodes in small fields relative to standard field sizes. Methods Due to the increased density of silicon and other components within a diode, additional electrons are created. In very small fields, a very small air gap acts as an effective filter of electrons with a high angle of incidence. The aim was to design a diode that balanced these perturbations to give a response similar to a water-only geometry. Three thicknesses of air were placed at the proximal end of a PTW 60017 electron diode (PTWe) using an adjustable “air cap”. A set of output ratios (ORfclin Det ) for square field sizes of side length down to 5 mm was measured using each air thickness and compared to ORfclin Det measured using an IBA stereotactic field diode (SFD). k fclin, f msr Qclin,Qmsr was transferred from the SFD to the PTWe diode and plotted as a function of air gap thickness for each field size. This enabled the optimal air gap thickness to be obtained by observing which thickness of air was required such that k fclin, f msr Qclin,Qmsr was equal to 1.00 at all field sizes. A similar procedure was used to find the optimal air thickness required to make a modified Sun Nuclear EDGE detector (EDGEe) which s “correction-free” in small field relative dosimetry. In addition, the feasibility of experimentally transferring k fclin, f msr Qclin,Qmsr values from the SFD to unknown diodes was tested by comparing the experimentally transferred k fclin, f msr Qclin,Qmsr values for unmodified PTWe and EDGEe diodes to Monte Carlo simulated values. Results 1.0 mm of air was required to make the PTWe diode correction-free. This modified diode (PTWeair) produced output factors equivalent to those in water at all field sizes (5–50 mm). The optimal air thickness required for the EDGEe diode was found to be 0.6 mm. The modified diode (EDGEeair) produced output factors equivalent to those in water, except at field sizes of 8 and 10 mm where it measured approximately 2% greater than the relative dose to water. The experimentally calculated k fclin, f msr Qclin,Qmsr for both the PTWe and the EDGEe diodes (without air) matched Monte Carlo simulated results, thus proving that it is feasible to transfer k fclin, f msr Qclin,Qmsr from one commercially available detector to another using experimental methods and the recommended experimental setup. Conclusions It is possible to create a diode which does not require corrections for small field output factor measurements. This has been performed and verified experimentally. The ability of a detector to be “correction-free” depends strongly on its design and composition. A nonwater-equivalent detector can only be “correction-free” if competing perturbations of the beam cancel out at all field sizes. This should not be confused with true water equivalency of a detector.

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The use of bat detectors to monitor bat activity is common. Although several papers have compared the performance of different brands, none have dealt with the effect of different habitats nor have they compared narrow- and broad-band detectors. In this study the performance of four brands of ultrasonic bat detector, including three narrowband and one broad-band model, were compared for their ability to detect a 40 kHz continuous sound of variable amplitude along 100 metre transects. Transects were laid out in two contrasting bat habitat types: grassland and forest. Results showed that the different brands of detector differed in their ability to detect the source in terms of maximum and minimum detectable distance of the source. The rate of sound degradation with distance as measured by each brand was also different. Significant differences were also found in the performance of different brands in open grassland versus deep forest. No significant differences were found within any brand of detector. Though not as sensitive as narrow-band detectors, broad-band models hold an advantage in their ability to identify species where several species are found sympatrically.

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Urban morphology as a field of study has developed primarily in Europe and North America, and more recently emerging as a recurrent topic in China and South America. As a counterpoint to this centric view, the ISUF 2013 conference explored aspects of ‘urban form at the edge’. In particular the conference examined ‘off centre areas’ such as India, Africa, Middle East, Central Asia and Australasia which require innovative approaches to the study of traditional, as well as post-colonial and contemporary, morphologies. Broader interpretations of urban form at the edge focus on minor centres and suburbia, with their developing and transilient character; edge cities and regional centres; and new technologies and approaches that are developing alongside established methods, tools and theories of urban morphology...

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Corner detection has shown its great importance in many computer vision tasks. However, in real-world applications, noise in the image strongly affects the performance of corner detectors. Few corner detectors have been designed to be robust to heavy noise by now, partly because the noise could be reduced by a denoising procedure. In this paper, we present a corner detector that could find discriminative corners in images contaminated by noise of different levels, without any denoising procedure. Candidate corners (i.e., features) are firstly detected by a modified SUSAN approach, and then false corners in noise are rejected based on their local characteristics. Features in flat regions are removed based on their intensity centroid, and features on edge structures are removed using the Harris response. The detector is self-adaptive to noise since the image signal-to-noise ratio (SNR) is automatically estimated to choose an appropriate threshold for refining features. Experimental results show that our detector has better performance at locating discriminative corners in images with strong noise than other widely used corner or keypoint detectors.