15 resultados para Combination of classifiers

em Aston University Research Archive


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We studied the rules by which visual responses to luminous targets are combined across the two eyes. Previous work has found very different forms of binocular combination for targets defined by increments and by decrements of luminance, with decrement data implying a severe nonlinearity before binocular combination. We ask whether this difference is due to the luminance of the target, the luminance of the background, or the sign of the luminance excursion. We estimated the pre-binocular nonlinearity (power exponent) by fitting a computational model to ocular equibrightness matches. The severity of the nonlinearity had a monotonic dependence on the signed difference between target and background luminance. For dual targets, in which there was both a luminance increment and a luminance decrement (e.g. contrast), perception was governed largely by the decrement. The asymmetry in the nonlinearities derived from the subjective matching data made a clear prediction for visual performance: there should be more binocular summation for detecting luminance increments than for detecting luminance decrements. This prediction was confirmed by the results of a subsequent experiment. We discuss the relation between these results and luminance nonlinearities such as a logarithmic transform, as well as the involvement of contemporary model architectures of binocular vision.

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The detection of signals in the presence of noise is one of the most basic and important problems encountered by communication engineers. Although the literature abounds with analyses of communications in Gaussian noise, relatively little work has appeared dealing with communications in non-Gaussian noise. In this thesis several digital communication systems disturbed by non-Gaussian noise are analysed. The thesis is divided into two main parts. In the first part, a filtered-Poisson impulse noise model is utilized to calulate error probability characteristics of a linear receiver operating in additive impulsive noise. Firstly the effect that non-Gaussian interference has on the performance of a receiver that has been optimized for Gaussian noise is determined. The factors affecting the choice of modulation scheme so as to minimize the deterimental effects of non-Gaussian noise are then discussed. In the second part, a new theoretical model of impulsive noise that fits well with the observed statistics of noise in radio channels below 100 MHz has been developed. This empirical noise model is applied to the detection of known signals in the presence of noise to determine the optimal receiver structure. The performance of such a detector has been assessed and is found to depend on the signal shape, the time-bandwidth product, as well as the signal-to-noise ratio. The optimal signal to minimize the probability of error of; the detector is determined. Attention is then turned to the problem of threshold detection. Detector structure, large sample performance and robustness against errors in the detector parameters are examined. Finally, estimators of such parameters as. the occurrence of an impulse and the parameters in an empirical noise model are developed for the case of an adaptive system with slowly varying conditions.

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The subject of investigation of the present research is the use of smart hydrogels with fibre optic sensor technology. The aim was to develop a costeffective sensor platform for the detection of water in hydrocarbon media, and of dissolved inorganic analytes, namely potassium, calcium and aluminium. The fibre optic sensors in this work depend upon the use of hydrogels to either entrap chemotropic agents or to respond to external environmental changes, by changing their inherent properties, such as refractive index (RI). A review of current fibre optic technology for sensing outlined that the main principles utilised are either the measurement of signal loss or a change in wavelength of the light transmitted through the system. The signal loss principle relies on changing the conditions required for total internal reflection to occur. Hydrogels are cross-linked polymer networks that swell but do not dissolve in aqueous environments. Smart hydrogels are synthetic materials that exhibit additional properties to those inherent in their structure. In order to control the non-inherent properties, the hydrogels were fabricated with the addition of chemotropic agents. For the detection of water, hydrogels of low refractive index were synthesized using fluorinated monomers. Sulfonated monomers were used for their extreme hydrophilicity as a means of water sensing through an RI change. To enhance the sensing capability of the hydrogel, chemotropic agents, such as pH indicators and cobalt salts, were used. The system comprises of the smart hydrogel coated onto an exposed section of the fibre optic core, connected to the interrogation system measuring the difference in the signal. Information obtained was analysed using a purpose designed software. The developed sensor platform showed that an increase in the target species caused an increase in the signal lost from the sensor system, allowing for a detection of the target species. The system has potential applications in areas such as clinical point of care, water detection in fuels and the detection of dissolved ions in the water industry.

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Substantial altimetry datasets collected by different satellites have only become available during the past five years, but the future will bring a variety of new altimetry missions, both parallel and consecutive in time. The characteristics of each produced dataset vary with the different orbital heights and inclinations of the spacecraft, as well as with the technical properties of the radar instrument. An integral analysis of datasets with different properties offers advantages both in terms of data quantity and data quality. This thesis is concerned with the development of the means for such integral analysis, in particular for dynamic solutions in which precise orbits for the satellites are computed simultaneously. The first half of the thesis discusses the theory and numerical implementation of dynamic multi-satellite altimetry analysis. The most important aspect of this analysis is the application of dual satellite altimetry crossover points as a bi-directional tracking data type in simultaneous orbit solutions. The central problem is that the spatial and temporal distributions of the crossovers are in conflict with the time-organised nature of traditional solution methods. Their application to the adjustment of the orbits of both satellites involved in a dual crossover therefore requires several fundamental changes of the classical least-squares prediction/correction methods. The second part of the thesis applies the developed numerical techniques to the problems of precise orbit computation and gravity field adjustment, using the altimetry datasets of ERS-1 and TOPEX/Poseidon. Although the two datasets can be considered less compatible that those of planned future satellite missions, the obtained results adequately illustrate the merits of a simultaneous solution technique. In particular, the geographically correlated orbit error is partially observable from a dataset consisting of crossover differences between two sufficiently different altimetry datasets, while being unobservable from the analysis of altimetry data of both satellites individually. This error signal, which has a substantial gravity-induced component, can be employed advantageously in simultaneous solutions for the two satellites in which also the harmonic coefficients of the gravity field model are estimated.

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Many planning and control tools, especially network analysis, have been developed in the last four decades. The majority of them were created in military organization to solve the problem of planning and controlling research and development projects. The original version of the network model (i.e. C.P.M/PERT) was transplanted to the construction industry without the consideration of the special nature and environment of construction projects. It suited the purpose of setting up targets and defining objectives, but it failed in satisfying the requirement of detailed planning and control at the site level. Several analytical and heuristic rules based methods were designed and combined with the structure of C.P.M. to eliminate its deficiencies. None of them provides a complete solution to the problem of resource, time and cost control. VERT was designed to deal with new ventures. It is suitable for project evaluation at the development stage. CYCLONE, on the other hand, is concerned with the design and micro-analysis of the production process. This work introduces an extensive critical review of the available planning techniques and addresses the problem of planning for site operation and control. Based on the outline of the nature of site control, this research developed a simulation based network model which combines part of the logics of both VERT and CYCLONE. Several new nodes were designed to model the availability and flow of resources, the overhead and operating cost and special nodes for evaluating time and cost. A large software package is written to handle the input, the simulation process and the output of the model. This package is designed to be used on any microcomputer using MS-DOS operating system. Data from real life projects were used to demonstrate the capability of the technique. Finally, a set of conclusions are drawn regarding the features and limitations of the proposed model, and recommendations for future work are outlined at the end of this thesis.

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Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.

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Binocular combination for first-order (luminancedefined) stimuli has been widely studied, but we know rather little about this binocular process for spatial modulations of contrast (second-order stimuli). We used phase-matching and amplitude-matching tasks to assess binocular combination of second-order phase and modulation depth simultaneously. With fixed modulation in one eye, we found that binocularly perceived phase was shifted, and perceived amplitude increased almost linearly as modulation depth in the other eye increased. At larger disparities, the phase shift was larger and the amplitude change was smaller. The degree of interocular correlation of the carriers had no influence. These results can be explained by an initial extraction of the contrast envelopes before binocular combination (consistent with the lack of dependence on carrier correlation) followed by a weighted linear summation of second-order modulations in which the weights (gains) for each eye are driven by the first-order carrier contrasts as previously found for first-order binocular combination. Perceived modulation depth fell markedly with increasing phase disparity unlike previous findings that perceived first-order contrast was almost independent of phase disparity. We present a simple revision to a widely used interocular gain-control theory that unifies first- and second-order binocular summation with a single principle-contrast-weighted summation-and we further elaborate the model for first-order combination. Conclusion: Second-order combination is controlled by first-order contrast.

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Energy crops production is considered as environmentally benign and socially acceptable, offering ecological benefits over fossil fuels through their contribution to the reduction of greenhouse gases and acidifying emissions. Energy crops are subjected to persistent policy support by the EU, despite their limited or even marginally negative impact on the greenhouse effect. The present study endeavors to optimize the agricultural income generated by energy crops in a remote and disadvantageous region, with the assistance of linear programming. The optimization concerns the income created from soybean, sunflower (proxy for energy crop), and corn. Different policy scenarios imposed restrictions on the value of the subsidies as a proxy for EU policy tools, the value of inputs (costs of capital and labor) and different irrigation conditions. The results indicate that the area and the imports per energy crop remain unchanged, independently of the policy scenario enacted. Furthermore, corn cultivation contributes the most to iFncome maximization, whereas the implemented CAP policy plays an incremental role in uptaking an energy crop. A key implication is that alternative forms of motivation should be provided to the farmers beyond the financial ones in order the extensive use of energy crops to be achieved.

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A new approach is described herein, where neutron reflectivity measurements that probe changes in the density profile of thin films as they absorb material from the gas phase have been combined with a Love wave based gravimetric assay that measures the mass of absorbed material. This combination of techniques not only determines the spatial distribution of absorbed molecules, but also reveals the amount of void space within the thin film (a quantity that can be difficult to assess using neutron reflectivity measurements alone). The uptake of organic solvent vapours into spun cast films of polystyrene has been used as a model system with a view to this method having the potential for extension to the study of other systems. These could include, for example, humidity sensors, hydrogel swelling, biomolecule adsorption or transformations of electroactive and chemically reactive thin films. This is the first ever demonstration of combined neutron reflectivity and Love wave-based gravimetry and the experimental caveats, limitations and scope of the method are explored and discussed in detail.

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Objectives Effective skin antisepsis and disinfection of medical devices are key factors in preventing many healthcare-acquired infections associated with skin microorganisms, particularly Staphylococcus epidermidis. The aim of this study was to investigate the antimicrobial efficacy of chlorhexidine digluconate (CHG), a widely used antiseptic in clinical practice, alone and in combination with tea tree oil (TTO), eucalyptus oil (EO) and thymol against planktonic and biofilm cultures of S. epidermidis. Methods Antimicrobial susceptibility assays against S. epidermidis in a suspension and in a biofilm mode of growth were performed with broth microdilution and ATP bioluminescence methods, respectively. Synergy of antimicrobial agents was evaluated with the chequerboard method. Results CHG exhibited antimicrobial activity against S. epidermidis in both suspension and biofilm (MIC 2–8 mg/L). Of the essential oils thymol exhibited the greatest antimicrobial efficacy (0.5–4 g/L) against S. epidermidis in suspension and biofilm followed by TTO (2–16 g/L) and EO (4–64 g/L). MICs of CHG and EO were reduced against S. epidermidis biofilm when in combination (MIC of 8 reduced to 0.25–1 mg/L and MIC of 32–64 reduced to 4 g/L for CHG and EO, respectively). Furthermore, the combination of EO with CHG demonstrated synergistic activity against S. epidermidis biofilm with a fractional inhibitory concentration index of <0.5. Conclusions The results from this study suggest that there may be a role for essential oils, in particular EO, for improved skin antisepsis when combined with CHG.

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This thesis presents an investigation into the application of methods of uncertain reasoning to the biological classification of river water quality. Existing biological methods for reporting river water quality are critically evaluated, and the adoption of a discrete biological classification scheme advocated. Reasoning methods for managing uncertainty are explained, in which the Bayesian and Dempster-Shafer calculi are cited as primary numerical schemes. Elicitation of qualitative knowledge on benthic invertebrates is described. The specificity of benthic response to changes in water quality leads to the adoption of a sensor model of data interpretation, in which a reference set of taxa provide probabilistic support for the biological classes. The significance of sensor states, including that of absence, is shown. Novel techniques of directly eliciting the required uncertainty measures are presented. Bayesian and Dempster-Shafer calculi were used to combine the evidence provided by the sensors. The performance of these automatic classifiers was compared with the expert's own discrete classification of sampled sites. Variations of sensor data weighting, combination order and belief representation were examined for their effect on classification performance. The behaviour of the calculi under evidential conflict and alternative combination rules was investigated. Small variations in evidential weight and the inclusion of evidence from sensors absent from a sample improved classification performance of Bayesian belief and support for singleton hypotheses. For simple support, inclusion of absent evidence decreased classification rate. The performance of Dempster-Shafer classification using consonant belief functions was comparable to Bayesian and singleton belief. Recommendations are made for further work in biological classification using uncertain reasoning methods, including the combination of multiple-expert opinion, the use of Bayesian networks, and the integration of classification software within a decision support system for water quality assessment.

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Many pesticides are used increasingly in combinations during crop protection and their stability ensures the presence of such combinations in foodstuffs. The effects of three fungicides, pyrimethanil, cyprodinil and fludioxonil, were investigated together and separately on U251 and SH-SY5Y cells, which can be representative of human CNS glial and neuronal cells respectively. Over 48h, all three agents showed significant reductions in cellular ATP, at concentrations that were more than tenfold lower than those which significantly impaired cellular viability. The effects on energy metabolism were reflected in their marked toxic effects on mitochondrial membrane potential. In addition, evidence of oxidative stress was seen in terms of a fall in cellular thiols coupled with increases in the expression of enzymes associated with reactive species formation, such as GSH peroxidase and superoxide dismutase. The glial cell line showed significant responsiveness to the toxin challenge in terms of changes in antioxidant gene expression, although the neuronal SH-SY5Y line exhibited greater vulnerability to toxicity, which was reflected in significant increases in caspase-3 expression, which is indicative of the initiation of apoptosis. Cyprodinil was the most toxic agent individually, although oxidative stress-related enzyme gene expression increases appeared to demonstrate some degree of synergy in the presence of the combination of agents. This report suggests that the impact of some pesticides, both individually and in combinations, merits further study in terms of their impact on human cellular health.

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The mechanism behind the immunostimulatory effect of the cationic liposomal vaccine adjuvant dimethyldioctadecylammonium and trehalose 6,6′- dibehenate (DDA:TDB) has been linked to the ability of these cationic vesicles to promote a depot after administration, with the liposomal adjuvant and the antigen both being retained at the injection site. This can be attributed to their cationic nature, since reduction in vesicle size does not influence their distribution profile yet neutral or anionic liposomes have more rapid clearance rates. Therefore the aim of this study was to investigate the impact of a combination of reduced vesicle size and surface pegylation on the biodistribution and adjuvanticity of the formulations, in a bid to further manipulate the pharmacokinetic profiles of these adjuvants. From the biodistribution studies, it was found that with small unilamellar vesicles (SUVs), 10% PEGylation of the formulation could influence liposome retention at the injection site after 4 days, whilst higher levels (25 mol%) of PEG blocked the formation of a depot and promote clearance to the draining lymph nodes. Interestingly, whilst the use of 10% PEG in the small unilamellar vesicles did not block the formation of a depot at the site of injection, it did result in earlier antibody response rates and switch the type of T cell responses from a Th1 to a Th2 bias suggesting that the presence of PEG in the formulation not only control the biodistribution of the vaccine, but also results in different types of interactions with innate immune cells. © 2012 Elsevier B.V.

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Lyophilised orally disintegrating tablets (ODTs) have achieved a great success in overcoming dysphagia associated with conventional solid dosage forms. However, the extensive use of saccharides within the formulation limits their use in treatment of chronic illnesses. The current study demonstrates the feasibility of using combination of proline and serine to formulate zero sacharide ODTs and investigates the effect of freezing protocol on sublimation rate and tablets characteristics. The results showed that inclusion of proline and serine improved ODT properties when compared to individual counterparts. Additionally, annealing the ODTs facilitated the sublimation process and shortened the disintegration time. © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.