995 resultados para OPTICAL EQUIPMENT


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We develop a framework for estimating the quality of transmission (QoT) of a new lightpath before it is established, as well as for calculating the expected degradation it will cause to existing lightpaths. The framework correlates the QoT metrics of established lightpaths, which are readily available from coherent optical receivers that can be extended to serve as optical performance monitors. Past similar studies used only space (routing) information and thus neglected spectrum, while they focused on oldgeneration noncoherent networks. The proposed framework accounts for correlation in both the space and spectrum domains and can be applied to both fixed-grid wavelength division multiplexing (WDM) and elastic optical networks. It is based on a graph transformation that exposes and models the interference between spectrum-neighboring channels. Our results indicate that our QoT estimates are very close to the actual performance data, that is, to having perfect knowledge of the physical layer. The proposed estimation framework is shown to provide up to 4 × 10-2 lower pre-forward error correction bit error ratio (BER) compared to theworst-case interference scenario,which overestimates the BER. The higher accuracy can be harvested when lightpaths are provisioned with low margins; our results showed up to 47% reduction in required regenerators, a substantial savings in equipment cost.

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The presence of microorganisms in ophthalmic instruments and surfaces can lead to the exposure of patients to several infections. However, there is no information regarding fungal and bacteria contamination in optical shops. This study aims to characterize fungi and bacteria contamination in air and surfaces from 10 optical shops covering also ophthalmic instruments. Air samples were collected through an impaction method onto malt extract agar (MEA) supplemented with chloramphenicol (0.05%) used for fungi and Tryptic Soy Agar (TSA) supplemented with nystatin (0.2%) used for bacteria. Outdoor samples were also performed to be used as reference. Surface and equipment’s swab samples were also collected side-by-side. All the collected samples were incubated at 27ºC for 5 to 7 days (fungi) or at 30º for 7 days (bacteria). Regarding fungal distribution, thirteen different species/genera were found in the air, being the most common Alternaria sp. (62.0%). Eight different species/genera were identified in the surfaces, ranging from 2 to 5x104 CFU/m2, being the most common A. versicolor complex and Penicillium sp. (40.0%). The trial frames were the most contaminated equipment, since 50.0% of the collected samples were with countless colonies. The airborne bacterial population indicated higher concentrations in the contactology office (average: 133 CFU/m3) than in the client’s waiting rooms (average: 126 CFU/m3). The surface samples indicated bacterial concentrations ranging from 2x104 to 1x106 CFU/m2, pointing out the automatic refractometer as the surface with higher bacterial load.

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In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations.

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Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

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Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.