958 resultados para Fourier series method
Resumo:
Full-field Fourier-domain optical coherence tomography (3F-OCT) is a full-field version of spectraldomain/swept-source optical coherence tomography. A set of two-dimensional Fourier holograms is recorded at discrete wavenumbers spanning the swept-source tuning range. The resultant three-dimensional data cube contains comprehensive information on the three-dimensional morphological layout of the sample that can be reconstructed in software via three-dimensional discrete Fourier-transform. This method of recording of the OCT signal confers signal-to-noise ratio improvement in comparison with "flying-spot" time-domain OCT. The spatial resolution of the 3F-OCT reconstructed image, however, is degraded due to the presence of a phase cross-term, whose origin and effects are addressed in this paper. We present theoretical and experimental study of imaging performance of 3F-OCT, with particular emphasis on elimination of the deleterious effects of the phase cross-term.
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This paper consides the problem of extracting the relationships between two time series in a non-linear non-stationary environment with Hidden Markov Models (HMMs). We describe an algorithm which is capable of identifying associations between variables. The method is applied both to synthetic data and real data. We show that HMMs are capable of modelling the oil drilling process and that they outperform existing methods.
Resumo:
Most traditional methods for extracting the relationships between two time series are based on cross-correlation. In a non-linear non-stationary environment, these techniques are not sufficient. We show in this paper how to use hidden Markov models (HMMs) to identify the lag (or delay) between different variables for such data. We first present a method using maximum likelihood estimation and propose a simple algorithm which is capable of identifying associations between variables. We also adopt an information-theoretic approach and develop a novel procedure for training HMMs to maximise the mutual information between delayed time series. Both methods are successfully applied to real data. We model the oil drilling process with HMMs and estimate a crucial parameter, namely the lag for return.
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A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.
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To determine the spatial pattern of ß-amyloid (Aß) deposition throughout the temporal lobe in Alzheimer's disease (AD). Methods: Sections of the complete temporal lobe from six cases of sporadic AD were immunolabelled with antibody against Aß. Fourier (spectral) analysis was used to identify sinusoidal patterns in the fluctuation of Aß deposition in a direction parallel to the pia mater or alveus. Results: Significant sinusoidal fluctuations in density were evident in 81/99 (82%) analyses. In 64% of analyses, two frequency components were present with density peaks of Aß deposits repeating every 500–1000 µm and at distances greater than 1000 µm. In 25% of analyses, three or more frequency components were present. The estimated period or wavelength (number of sample units to complete one full cycle) of the first and second frequency components did not vary significantly between gyri of the temporal lobe, but there was evidence that the fluctuations of the classic deposits had longer periods than the diffuse and primitive deposits. Conclusions: (i) Aß deposits exhibit complex sinusoidal fluctuations in density in the temporal lobe in AD; (ii) fluctuations in Aß deposition may reflect the formation of Aß deposits in relation to the modular and vascular structure of the cortex; and (iii) Fourier analysis may be a useful statistical method for studying the patterns of Aß deposition both in AD and in transgenic models of disease.
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Azidoprofen {2-(4-azidophenyl)propionic acid; AZP}, an azido-substituted arylalkanoic acid, was investigated as a model soft drug candidate for a potential topical non-steroidal anti-inflammatory agent (NSAIA). Reversed-phase high performance liquid chromatography (HPLC) methods were developed for the assay of AZP, a series of ester analogues and their· degradation products. 1H-NMR spectroscopy was also employed as an analytical method in selected cases. Reduction of the azido-group to the corresponding amine has been proposed as a potential detoxification mechanism for compounds bearing this substituent. An in vitro assay to measure the susceptibility of azides towards reduction was developed using dithiothreitol as a model reducing agent. The rate of reduction of AZP was found to be base-dependent, hence supporting the postulated mechanism of thiol-mediated reduction via nucleophilic attack by the thiolate anion. Prodrugs may enhance topical bioavailability through the manipulation of physico-chemical properties of the parent drug. A series of ester derivatives of AZP were investigated for their susceptibility to chemical and enzymatic hydrolysis, which regenerates the parent acid. Use of alcoholic cosolvents with differing alkyl functions to that of the ester resulted in transesterification reactions, which were found to be enzyme-mediated. The skin penetration of AZP was assessed using an in vitro hairless mouse skin model, and silastic membrane in some cases. The rate of permeation of AZP was found to be a similar magnitude to that of the well established NSAIA ibuprofen. Penetration rates were dependent on the vehicle pH and drug concentration when solutions were employed. In contrast, flux was independent of pH when suspension formulations were used. Pretreatment of the skin with various enhancer regimes, including oleic acid and azone in propylene glycol, promoted the penetration of AZP. An intense IR absorption due to the azide group serves as a highly diagnostic marker, enabling azido compounds to be detected in the outer layers of the· stratum corneum following their application to skin, using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). This novel application enabled a non-invasive examination of the percutaneous penetration enhancement of a model azido compound in vivo in man, in the presence of the enhancer oleic acid.
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This thesis addresses the problem of information hiding in low dimensional digital data focussing on issues of privacy and security in Electronic Patient Health Records (EPHRs). The thesis proposes a new security protocol based on data hiding techniques for EPHRs. This thesis contends that embedding of sensitive patient information inside the EPHR is the most appropriate solution currently available to resolve the issues of security in EPHRs. Watermarking techniques are applied to one-dimensional time series data such as the electroencephalogram (EEG) to show that they add a level of confidence (in terms of privacy and security) in an individual’s diverse bio-profile (the digital fingerprint of an individual’s medical history), ensure belief that the data being analysed does indeed belong to the correct person, and also that it is not being accessed by unauthorised personnel. Embedding information inside single channel biomedical time series data is more difficult than the standard application for images due to the reduced redundancy. A data hiding approach which has an in built capability to protect against illegal data snooping is developed. The capability of this secure method is enhanced by embedding not just a single message but multiple messages into an example one-dimensional EEG signal. Embedding multiple messages of similar characteristics, for example identities of clinicians accessing the medical record helps in creating a log of access while embedding multiple messages of dissimilar characteristics into an EPHR enhances confidence in the use of the EPHR. The novel method of embedding multiple messages of both similar and dissimilar characteristics into a single channel EEG demonstrated in this thesis shows how this embedding of data boosts the implementation and use of the EPHR securely.
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This paper proposes a new converter protection method, primarily based on a series dynamic resistor (SDR) that avoids the doubly-fed induction generator (DFIG) control being disabled by crowbar protection during fault conditions. A combined converter protection scheme based on the proposed SDR and conventional crowbar is analyzed and discussed. The main protection advantages are due to the series topology when compared with crowbar and dc-chopper protection. Various fault overcurrent conditions (both symmetrical and asymmetrical) are analyzed and used to design the protection in detail, including the switching strategy and coordination with crowbar, and resistance value calculations. PSCAD/EMTDC simulation results show that the proposed method is advantageous for fault overcurrent protection, especially for asymmetrical faults, in which the traditional crowbar protection may malfunction.
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We discuss aggregation of data from neuropsychological patients and the process of evaluating models using data from a series of patients. We argue that aggregation can be misleading but not aggregating can also result in information loss. The basis for combining data needs to be theoretically defined, and the particular method of aggregation depends on the theoretical question and characteristics of the data. We present examples, often drawn from our own research, to illustrate these points. We also argue that statistical models and formal methods of model selection are a useful way to test theoretical accounts using data from several patients in multiple-case studies or case series. Statistical models can often measure fit in a way that explicitly captures what a theory allows; the parameter values that result from model fitting often measure theoretically important dimensions and can lead to more constrained theories or new predictions; and model selection allows the strength of evidence for models to be quantified without forcing this into the artificial binary choice that characterizes hypothesis testing methods. Methods that aggregate and then formally model patient data, however, are not automatically preferred to other methods. Which method is preferred depends on the question to be addressed, characteristics of the data, and practical issues like availability of suitable patients, but case series, multiple-case studies, single-case studies, statistical models, and process models should be complementary methods when guided by theory development.
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The fracture properties of a series of alloys containing 15% chromium and 0.8 to 3.4% carbon are investigated using strain fracture toughness testing techniques. The object of the work is to apply a quantitative method of measuring toughness to abrasion resistant materials, which have previously been assessed on an empirical basis; and to examine the relationship between microstructure and K10 in an attempt to improve the toughness of inherently brittle materials. A review of the relevant literature includes discussion of the background to the alloy series under investigation, a survey of the development of fracture mechanics and the emergence of K10 as a toughness parameter. Metallurgical variables such as composition, heat treatment, grain size, and hot working are ???? to relate microstructure to toughness, and fractographic evidence is used to substantiate the findings. The results are applied to a model correlating ductile fracture with plastic strain instability, and the nucleation of voids. Strain induced martensite formation in austenitic structures is analysed in terms of the plastic energy dissipation mechanisms operating at the crack tip. Emphasis is placed on the lower carbon alloys in the series, and a composition put forward to optimise wear resistance and toughness. The properties of established competitive materials are compared to the proposed alloy on a toughness and cost basis.
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The problem considered is that of determining the fluid velocity for linear hydrostatics Stokes flow of slow viscous fluids from measured velocity and fluid stress force on a part of the boundary of a bounded domain. A variational conjugate gradient iterative procedure is proposed based on solving a series of mixed well-posed boundary value problems for the Stokes operator and its adjoint. In order to stabilize the Cauchy problem, the iterations are ceased according to an optimal order discrepancy principle stopping criterion. Numerical results obtained using the boundary element method confirm that the procedure produces a convergent and stable numerical solution.
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An iterative method for reconstruction of the solution to a parabolic initial boundary value problem of second order from Cauchy data is presented. The data are given on a part of the boundary. At each iteration step, a series of well-posed mixed boundary value problems are solved for the parabolic operator and its adjoint. The convergence proof of this method in a weighted L2-space is included.
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An iterative method for the reconstruction of a stationary three-dimensional temperature field, from Cauchy data given on a part of the boundary, is presented. At each iteration step, a series of mixed well-posed boundary value problems are solved for the heat operator and its adjoint. A convergence proof of this method in a weighted L 2-space is include