998 resultados para neutron detection wall


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Despite changes in surgical techniques, radiotherapy targeting and the apparent earlier detection of cancers, secondary lymphoedema is still a significant problem for about 20–30% of those who receive treatment for cancer, although the incidence and prevalence does seem to be falling. The figures above generally relate to detection of an enlarged limb or other area, but it seems that about 60% of all patients also suffer other problems with how the limb feels, what can or cannot be done with it and a range of social or psychological issues. Often these ‘subjective’ changes occur before the objective ones, such as a change in arm volume or circumference. For most of those treated for cancer lymphoedema does not develop immediately, and, while about 60–70% develop it in the first few years, some do not develop lymphoedema for up to 15 or 20 years. Those who will develop clinically manifest lymphoedema in the future are, for some time, in a latent or hidden phase of lymphoedema. There also seems to be some risk factors which are indicators for a higher likelihood of lymphoedema post treatment, including oedema at the surgical site, arm dominance, age, skin conditions, and body mass index (BMI).

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The story of the fall of the Berlin Wall was an aspect of the “imagination gap” that we had to wrestle with as journalists covering the collapse of the Eastern Bloc in Europe. It was scarcely possible to believe what you found yourself reporting, and that work became a two-track process. On one hand a mass social movement was dictating the pace and direction of events; on the other, the institutional business of politics as usual, to provide a framework for all the change that was happening, had to be managed – and reported on. In later analyseds we could see, that crisis in the Soviet Union led to the crisis over the Berlin Wall; and from the fall of the Wall, came Germany’s reunification, and with that also, formation of the European Union as it is today. The government of the Federal Republic of Germany convinced its neighbours that a reunited Germany, within an expanded EU, would be a very acceptable “European Germany” -- not the leader of a “German Europe”. It committed itself financially, supporting the new Euro currency. The former communist states of Eastern Europe demanded to join and expand the EU; in order to remove themselves from the Soviet Union, enjoy human rights, and share in Western prosperity. So today, following on from the events of 1989, the European Union is an amalgam of 27 member countries, with close to 500 million citizens and accounting for 30 % of world Gross National Product.

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Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

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The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

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This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

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Aims: Influenza is commonly spread by infectious aerosols; however, detection of viruses in aerosols is not sensitive enough to confirm the characteristics of virus aerosols. The aim of this study was to develop an assay for respiratory viruses sufficiently sensitive to be used in epidemiological studies. Method: A two-step, nested real-time PCR assay was developed for MS2 bacteriophage, and for influenza A and B, parainfluenza 1 and human respiratory syncytial virus. Outer primer pairs were designed to nest each existing real-time PCR assay. The sensitivities of the nested real-time PCR assays were compared to those of existing real-time PCR assays. Both assays were applied in an aerosol study to compare their detection limits in air samples. Conclusions: The nested real-time PCR assays were found to be several logs more sensitive than the real-time PCR assays, with lower levels of virus detected at lower Ct values. The nested real-time PCR assay successfully detected MS2 in air samples, whereas the real-time assay did not. Significance and Impact of the Study: The sensitive assays for respiratory viruses will permit further research using air samples from naturally generated virus aerosols. This will inform current knowledge regarding the risks associated with the spread of viruses through aerosol transmission.

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The aetiology of secondary lymphoedema seems to be multifactorial, with acquired abnormalities as well as pre-existing conditions being contributory factors. Many characteristics bear inconsistent relationships to lymphoedema risk, and the few that are consistently associated with an increased risk of developing the condition, do not alone distinguish the at-risk population. Further, our current prevention and management recommendations are not backed by strong evidence. Consequently, there remains much to be learned about who gets it, how can it be prevented and how can we best treat it. Nonetheless, it is clear that lymphoedema is associated with adverse side effects, which have a profound impact on daily life, and that preliminary evidence suggests that early detection may lead to more effective treatment and lack of treatment may lead to progression. These represent important reasons as to why lymphoedema deserves clinical attention. However, several pragmatic issues must be considered when discussing whether a routine objective measure of lymphoedema could be integrated among the standard clinical care of those undertaking treatment for cancers known to be associated with the development of lymphoedema.

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Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

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This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.

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Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task.

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While spoken term detection (STD) systems based on word indices provide good accuracy, there are several practical applications where it is infeasible or too costly to employ an LVCSR engine. An STD system is presented, which is designed to incorporate a fast phonetic decoding front-end and be robust to decoding errors whilst still allowing for rapid search speeds. This goal is achieved through mono-phone open-loop decoding coupled with fast hierarchical phone lattice search. Results demonstrate that an STD system that is designed with the constraint of a fast and simple phonetic decoding front-end requires a compromise to be made between search speed and search accuracy.

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Network-based Intrusion Detection Systems (NIDSs) analyse network traffic to detect instances of malicious activity. Typically, this is only possible when the network traffic is accessible for analysis. With the growing use of Virtual Private Networks (VPNs) that encrypt network traffic, the NIDS can no longer access this crucial audit data. In this paper, we present an implementation and evaluation of our approach proposed in Goh et al. (2009). It is based on Shamir's secret-sharing scheme and allows a NIDS to function normally in a VPN without any modifications and without compromising the confidentiality afforded by the VPN.

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The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

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Aberrations affect image quality of the eye away from the line of sight as well as along it. High amounts of lower order aberrations are found in the peripheral visual field and higher order aberrations change away from the centre of the visual field. Peripheral resolution is poorer than that in central vision, but peripheral vision is important for movement and detection tasks (for example driving) which are adversely affected by poor peripheral image quality. Any physiological process or intervention that affects axial image quality will affect peripheral image quality as well. The aim of this study was to investigate the effects of accommodation, myopia, age, and refractive interventions of orthokeratology, laser in situ keratomileusis and intraocular lens implantation on the peripheral aberrations of the eye. This is the first systematic investigation of peripheral aberrations in a variety of subject groups. Peripheral aberrations can be measured either by rotating a measuring instrument relative to the eye or rotating the eye relative to the instrument. I used the latter as it is much easier to do. To rule out effects of eye rotation on peripheral aberrations, I investigated the effects of eye rotation on axial and peripheral cycloplegic refraction using an open field autorefractor. For axial refraction, the subjects fixated at a target straight ahead, while their heads were rotated by ±30º with a compensatory eye rotation to view the target. For peripheral refraction, the subjects rotated their eyes to fixate on targets out to ±34° along the horizontal visual field, followed by measurements in which they rotated their heads such that the eyes stayed in the primary position relative to the head while fixating at the peripheral targets. Oblique viewing did not affect axial or peripheral refraction. Therefore it is not critical, within the range of viewing angles studied, if axial and peripheral refractions are measured with rotation of the eye relative to the instrument or rotation of the instrument relative to the eye. Peripheral aberrations were measured using a commercial Hartmann-Shack aberrometer. A number of hardware and software changes were made. The 1.4 mm range limiting aperture was replaced by a larger aperture (2.5 mm) to ensure all the light from peripheral parts of the pupil reached the instrument detector even when aberrations were high such as those occur in peripheral vision. The power of the super luminescent diode source was increased to improve detection of spots passing through the peripheral pupil. A beam splitter was placed between the subjects and the aberrometer, through which they viewed an array of targets on a wall or projected on a screen in a 6 row x 7 column matrix of points covering a visual field of 42 x 32. In peripheral vision, the pupil of the eye appears elliptical rather than circular; data were analysed off-line using custom software to determine peripheral aberrations. All analyses in the study were conducted for 5.0 mm pupils. Influence of accommodation on peripheral aberrations was investigated in young emmetropic subjects by presenting fixation targets at 25 cm and 3 m (4.0 D and 0.3 D accommodative demands, respectively). Increase in accommodation did not affect the patterns of any aberrations across the field, but there was overall negative shift in spherical aberration across the visual field of 0.10 ± 0.01m. Subsequent studies were conducted with the targets at a 1.2 m distance. Young emmetropes, young myopes and older emmetropes exhibited similar patterns of astigmatism and coma across the visual field. However, the rate of change of coma across the field was higher in young myopes than young emmetropes and was highest in older emmetropes amongst the three groups. Spherical aberration showed an overall decrease in myopes and increase in older emmetropes across the field, as compared to young emmetropes. Orthokeratology, spherical IOL implantation and LASIK altered peripheral higher order aberrations considerably, especially spherical aberration. Spherical IOL implantation resulted in an overall increase in spherical aberration across the field. Orthokeratology and LASIK reversed the direction of change in coma across the field. Orthokeratology corrected peripheral relative hypermetropia through correcting myopia in the central visual field. Theoretical ray tracing demonstrated that changes in aberrations due to orthokeratology and LASIK can be explained by the induced changes in radius of curvature and asphericity of the cornea. This investigation has shown that peripheral aberrations can be measured with reasonable accuracy with eye rotation relative to the instrument. Peripheral aberrations are affected by accommodation, myopia, age, orthokeratology, spherical intraocular lens implantation and laser in situ keratomileusis. These factors affect the magnitudes and patterns of most aberrations considerably (especially coma and spherical aberration) across the studied visual field. The changes in aberrations across the field may influence peripheral detection and motion perception. However, further research is required to investigate how the changes in aberrations influence peripheral detection and motion perception and consequently peripheral vision task performance.