136 resultados para Kautz filters


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PURPOSE: We sought to determine whether conjunctival ultraviolet autofluorescence (UVAF), a biomarker of outdoor light exposure, is associated with myopia. METHODS: We performed a cross-sectional study on Norfolk Island and recruited individuals aged ≥ 15 years. Participants completed a sun-exposure questionnaire and underwent non-cycloplegic autorefraction. Conjunctival UVAF used a specially adapted electronic flash system fitted with UV-transmission filters (transmittance range 300-400 nm, peak 365 nm) as the excitation source. Temporal and nasal conjunctival UVAF was measured in both eyes using computerized photographic analysis with the sum referred to as "total UVAF." RESULTS: In 636 participants, prevalence of myopia decreased with an increasing quartile of total UVAF (P(trend) = 0.002). Median total UVAF was lower in subjects with myopia (spherical equivalent [SE] ≤ -1.0 diopter [D]) than participants without myopia: 16.6 mm(2) versus 28.6 mm(2), P = 0.001. In the multivariable model that adjusted for age, sex, smoking, cataract, height and weight, UVAF was independently associated with myopia (SE ≤ -1.0 D): odds ratio (OR) for total UVAF (per 10 mm(2)) was 0.81, 95% confidence interval (CI) 0.69 to 0.94, P = 0.007. UVAF was also significantly associated with myopia when analysis was restricted to subjects <50 years, and in moderate-severe myopia (SE ≤ -3.0 D). Prevalence of myopia decreased with increasing time outdoors (P(trend) = 0.03), but time outdoors was not associated with myopia on multivariable analysis. CONCLUSIONS: Study authors identified a protective association between increasing UVAF and myopia. The protective association of higher UVAF against myopia was stronger than that of increased levels of time spent outdoors as measured by this study's questionnaire. Future studies should investigate the association between UVAF and incident myopia, and its relationship to myopic progression.

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This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

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Results of an interlaboratory comparison on size characterization of SiO2 airborne nanoparticles using on-line and off-line measurement techniques are discussed. This study was performed in the framework of Technical Working Area (TWA) 34—“Properties of Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS) in the project no. 3 “Techniques for characterizing size distribution of airborne nanoparticles”. Two types of nano-aerosols, consisting of (1) one population of nanoparticles with a mean diameter between 30.3 and 39.0 nm and (2) two populations of non-agglomerated nanoparticles with mean diameters between, respectively, 36.2–46.6 nm and 80.2–89.8 nm, were generated for characterization measurements. Scanning mobility particle size spectrometers (SMPS) were used for on-line measurements of size distributions of the produced nano-aerosols. Transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were used as off-line measurement techniques for nanoparticles characterization. Samples were deposited on appropriate supports such as grids, filters, and mica plates by electrostatic precipitation and a filtration technique using SMPS controlled generation upstream. The results of the main size distribution parameters (mean and mode diameters), obtained from several laboratories, were compared based on metrological approaches including metrological traceability, calibration, and evaluation of the measurement uncertainty. Internationally harmonized measurement procedures for airborne SiO2 nanoparticles characterization are proposed.

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This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide a theoretical justification for the widespread application of approximate filters and controllers in the common situation where system models are not known with complete certainty. This research also provides useful tools for approximate filter designs, which are applied to hybrid filtering of uncertain nonlinear systems. As a contribution towards applications, this thesis also investigates air traffic separation control in the presence of measurement uncertainties.

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In many applications, where encrypted traffic flows from an open (public) domain to a protected (private) domain, there exists a gateway that bridges the two domains and faithfully forwards the incoming traffic to the receiver. We observe that indistinguishability against (adaptive) chosen-ciphertext attacks (IND-CCA), which is a mandatory goal in face of active attacks in a public domain, can be essentially relaxed to indistinguishability against chosen-plaintext attacks (IND-CPA) for ciphertexts once they pass the gateway that acts as an IND-CCA/CPA filter by first checking the validity of an incoming IND-CCA ciphertext, then transforming it (if valid) into an IND-CPA ciphertext, and forwarding the latter to the recipient in the private domain. “Non-trivial filtering'' can result in reduced decryption costs on the receivers' side. We identify a class of encryption schemes with publicly verifiable ciphertexts that admit generic constructions of (non-trivial) IND-CCA/CPA filters. These schemes are characterized by existence of public algorithms that can distinguish between valid and invalid ciphertexts. To this end, we formally define (non-trivial) public verifiability of ciphertexts for general encryption schemes, key encapsulation mechanisms, and hybrid encryption schemes, encompassing public-key, identity-based, and tag-based encryption flavours. We further analyze the security impact of public verifiability and discuss generic transformations and concrete constructions that enjoy this property.

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Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.

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Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

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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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Aim Evidence linking the accumulation of exotic species to the suppression of native diversity is equivocal, often relying on data from studies that have used different methods. Plot-level studies often attribute inverse relationships between native and exotic diversity to competition, but regional abiotic filters, including anthropogenic influences, can produce similar patterns.We seek to test these alternatives using identical scale-dependent sampling protocols in multiple grasslands on two continents. Location Thirty-two grassland sites in North America and Australia. Methods We use multiscale observational data, collected identically in grain and extent at each site, to test the association of local and regional factors with the plot-level richness and abundance of native and exotic plants. Sites captured environmental and anthropogenic gradients including land-use intensity, human population density, light and soil resources, climate and elevation. Site selection occurred independently of exotic diversity, meaning that the numbers of exotic species varied randomly thereby reducing potential biases if only highly invaded sites were chosen. Results Regional factors associated directly or indirectly with human activity had the strongest associations with plot-level diversity. These regional drivers had divergent effects: urban-based economic activity was associated with high exotic : native diversity ratios; climate- and landscape-based indicators of lower human population density were associated with low exotic : native ratios. Negative correlations between plot-level native and exotic diversity, a potential signature of competitive interactions, were not prevalent; this result did not change along gradients of productivity or heterogeneity. Main conclusion We show that plot-level diversity of native and exotic plants are more consistently associatedwith regional-scale factors relating to urbanization and climate suitability than measures indicative of competition. These findings clarify the long-standing difficulty in resolving drivers of exotic diversity using single-factor mechanisms, suggesting that multiple interacting anthropogenic-based processes best explain the accumulation of exotic diversity in modern landscapes.

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Protecting slow sand filters from high turbidity waters by pre-treatment using Pebble Matrix Filtration (PMF) has been studied in the laboratory at University College London followed by pilot field trials in Papua New Guinea and Serbia. Subsequently, the construction of two full-scale PMF units, one out of concrete (4.8m x4.8m x 3.0m high) and the other using pre-cast Ferro-cement panels (900mm x 1600mm x 20mm thick) with an effective diameter of 4.7m and 3m height, and the combined effective plan area of 40 m2 was completed to protect an existing Slow Sand Filter system at the National Water Supply Drainage Board (NWSDB) in Sri Lanka. Although the plant was completed in April 2008 due to some major repairs to address some leaks and other construction defects in both filters, monitoring was intermittent until November 2008. The results on the plant performance are presented here along with some of the construction problems encountered during the project.

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In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.

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For many years materials such as quarried sand, anthracite, and granular activated carbon have been the principal media-products traditionally used in water and wastewater filtration plants. Pebble Matrix Filtration (PMF) is a novel non-chemical, sustainable pre-treatment method of protecting Slow Sand Filters (SSF) from high turbidity during heavy monsoon periods. PMF uses sand and pebbles as the filter media and the sustainability of this new technology might depend on availability and supply of pebbles and sand, both finite resources. In many countries there are two principal methods of obtaining pebbles and sand, namely dredging from rivers and beaches, and due to the scarcity of these resources in some countries the cost of pebbles is often 4-5 times higher than that of sand. In search for an alternative medium to pebbles after some preliminary laboratory tests conducted in Colombo-Sri Lanka, Poznan-Poland and Cambridge-UK, a 100-year-old brick factory near Sudbury, Suffolk, has produced hand-made clay pebbles satisfying the PMF quality requirements. As an alternative to sand, crushed recycled glass from a UK supplier was used and the PMF system was operated together with hand-made clay balls in the laboratory for high turbidity removal effectively. The results of laboratory experiments with alternative media are presented in this paper. There are potential opportunities for recycled crushed glass and clay ball manufacturing processes in some countries where they can be used as filter media.

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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

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This work investigated the impact of the HVAC filtration system and indoor particle sources on the relationship between indoor and outdoor airborne particle size and concentrations in an operating room. Filters with efficiency between 65% and 99.97% were used in the investigation and indoor and outdoor particle size and concentrations were measured. A balance mass model was used for the simulation of the impact of the surgical team, deposition rate, HVAC exhaust and air change rates on indoor particle concentration. The experimental results showed that high efficiency filters would not be expected to decrease the risk associated with indoor particles larger than approximately 1 µm in size because normal filters are relatively efficient for these large particles. A good fraction of outdoor particles were removed by deposition on the HVAC system surfaces and this deposition increased with particle size. For particles of 0.3-0.5 µm in diameter, particle reduction was about 23%, while for particles >10 µm the loss was about 78%. The modelling results showed that depending on the type of filter used, the surgical team generated between 93-99% of total particles, while the outdoor air contributed only 1-6%.

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This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.