945 resultados para filters
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Resources created at the University of Southampton for the module Remote Sensing for Earth Observation
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In Nuclear Medicine, radioiodine, in various chemical forms, is a key tracer used in diagnostic practices and/or therapy. Due to its high volatility, medical professionals may incorporate radioactive iodine during the preparation of the dose to be administered to the patient. In radioactive iodine therapy doses ranging from 3.7 to 7.4GBq per patient are employed. Thus, aiming at reducing the risk of occupational contamination, we developed a low cost filter to be installed at the exit of the exhaust system where doses of radioactive iodine are fractionated, using domestic technology. The effectiveness of radioactive iodine retention by silver impregnated silica [10%] crystals and natural activated carbon was verified using radiotracer techniques. The results showed that natural activated carbon is effective for I2 capture for a large or small amount of substrate but its use is restricted due to its low flash point (150º C). Besides, when poisoned by organic solvents, this flash point may become lower, causing explosions if absorbing large amounts of nitrates. To hold the CH3I gas, it was necessary to increase the volume of natural activated carbon since it was not absorbed by SiO2 + Ag crystals. We concluded that, for an exhaust flow range of (306 4) m3/h, a double stage filter using SiO2 + Ag in the first stage and natural activated carbon in the second is sufficient to meet radiological safety requirements.
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The main aim of this work is to develop a methodology to evaluate the characteristics of porous media in filter using the radio-tracing technique. To do this, an experimental prototype filter made up of an acrylic cylinder, vertically mounted and supported on the lower side by a controlled leaking valve was developed. Two filters (spheres of acrylic and silica crystals) were used to check the movement of the water through the porous media using 123I in its MIBG (iodine-123-meta-iodo benzyl-guanidine) form. Further up the filter an instantaneous injection of the substance makes it possible to see the passage of radioactive clouds through the two scintillatory detectors NaI (2x2)” positioned before and immediately after the cylinder with the filtering element (porous media). The are caused by the detectors on the passage of the radioactive cloud are analyzed through statistical functions using the weighted moment method which makes it possible to calculate the Residence-Time (the amount of time the tracer takes to thoroughly pass through the filter) per the equation of dispersion in tubular flow and the one-directional flow of the radiotracer in the porous media.
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This thesis focuses on the private membership test (PMT) problem and presents three single server protocols to resolve this problem. In the presented solutions, a client can perform an inclusion test for some record x in a server's database, without revealing his record. Moreover after executing the protocols, the contents of server's database remain secret. In each of these solutions, a different cryptographic protocol is utilized to construct a privacy preserving variant of Bloom filter. The three suggested solutions are slightly different from each other, from privacy perspective and also from complexity point of view. Therefore, their use cases are different and it is impossible to choose one that is clearly the best between all three. We present the software developments of the three protocols by utilizing various pseudocodes. The performance of our implementation is measured based on a real case scenario. This thesis is a spin-off from the Academy of Finland research project "Cloud Security Services".
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This document describes the kinds of items accepted for recycling at Lexington County recycling centers.
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Several Cronobacter outbreaks have implicated contaminated drinking water. This study assessed the impact of granular activated carbon (GAC) on the microbial quality of the water produced. A simulated water filter system was installed by filling plastic columns with sterile GAC, followed by sterile water with a dilute nutrient flowing through the column at a steady rate. Carbon columns were inoculated with Cronobacter on the surface, and the effluent monitored for Cronobacter levels. During a second phase, commercial faucet filters were distributed to households for 4-month use. Used filters were backwashed with sterile peptone water, and analyzed for Cronobacter, total aerobic plate count, coliform bacteria and Enterobacteriaceae. Cronobacter colonized the simulated GAC and grew when provided minimal levels of nutrients. Backwashed used filters used in home settings yielded presumptive Escherichia coli, Pseudomonas and other waterborne bacteria. Presumptive Cronobacter strains were identified as negative through biochemical and genetic test.
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The particulate matter distribution (PM) trends that exist in catalyzed particulate filters (CPFs) after loading, passive oxidation, active regeneration, and post loading conditions are not clearly understood. These data are required to optimize the operation of CPFs, prevent damage to the CPFs caused by non-uniform distributions, and develop accurate CPF models. To develop an understanding of PM distribution trends, multiple tests were conducted and the PM distribution was measured in three dimensions using a terahertz wave scanner. The results of this work indicate that loading, passive oxidation, active regeneration, and post loading can all cause non-uniform PM distributions. The density of the PM in the substrate after loading and the amount of PM that is oxidized during passive oxidations and active regenerations affect the uniformity of the distribution. Post loading that occurs after active regenerations result in distributions that are less uniform than post loading that occurs after passive oxidations.
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This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.
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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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Aims: This study investigated the effect of simulated visual impairment on the speed and accuracy of performance on a series of commonly used cognitive tests. ----- Methods: Cognitive performance was assessed for 30 young, visually normal subjects (M=22.0yrs ± 3.1 yrs) using the Digit Symbol Substitution Test (DSST), Trail Making Test (TMT) A and B and the Stroop Colour Word Test under three visual conditions: normal vision and two levels of visually degrading filters (VistechTM) administered in a random order. Distance visual acuity and contrast sensitivity were also assessed for each filter condition. ----- Results: The visual filters, which degraded contrast sensitivity to a greater extent than visual acuity, significantly increased the time to complete (p<0.05), but not the number of errors made, on the DSST and the TMT A and B and affected only some components of the Stroop test.----- Conclusions: Reduced contrast sensitivity had a marked effect on the speed but not the accuracy of performance on commonly used cognitive tests, even in young individuals; the implications of these findings are discussed.
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Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.
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Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.
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Purpose: In 1970, Enright observed a distortion of perceived driving speed, induced by monocular application of a neutral density (ND) filter. If a driver looks out of the right side of a vehicle with a filter over the right eye, the driver perceives a reduction of the vehicle’s apparent velocity, while applying a ND filter over the left eye increases the vehicle’s apparent velocity. The purpose of the current study was to provide the first empirical measurements of the Enright phenomenon. Methods: Ten experienced drivers were tested and drove an automatic sedan on a closed road circuit. Filters (0.9 ND) were placed over the left, right or both eyes during a driving run, in addition to a control condition with no filters in place. Subjects were asked to look out of the right side of the car and adjust their driving speed to either 40 km/h or 60 km/h. Results: Without a filter or with both eyes filtered subjects showed good estimation of speed when asked to travel at 60 km/h but travelled a mean of 12 to 14 km/h faster than the requested 40 km/h. Subjects travelled faster than these baselines by a mean of 7 to 9 km/h (p < 0.001) with the filter over their right eye, and 3 to 5 km/h slower with the filter over their left eye (p < 0.05). Conclusions: The Enright phenomenon causes significant and measurable distortions of perceived driving speed under realworld driving conditions.