982 resultados para Fast methods


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A popular dynamic imaging technique, k-t BLAST (ktB) is studied here for BAR imaging. ktB utilizes correlations in k-space and time, to reconstruct the image time series with only a fraction of the data. The algorithm works by unwrapping the aliased Fourier conjugate space of k-t (y-f-space). The unwrapping process utilizes the estimate of the true y-f-space, by acquiring densely sampled low k-space data. The drawbacks of this method include separate training scan, blurred training estimates and aliased phase maps. The proposed changes are incorporation of phase information from the training map and using generalized-series-extrapolated training map. The proposed technique is compared with ktB on real fMRI data. The proposed changes allow for ktB to operate at an acceleration factor of 6. Performance is evaluated by comparing activation maps obtained using reconstructed images. An improvement of up to 10 dB is observed in thePSNR of activation maps. Besides, a 10% reduction in RMSE is obtained over the entire time series of fMRI images. Peak improvement of the proposed method over ktB is 35%, averaged over five data sets. (C)2010 Elsevier Inc. All rights reserved.

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In this study, we derive a fast, novel time-domain algorithm to compute the nth-order moment of the power spectral density of the photoelectric current as measured in laser-Doppler flowmetry (LDF). It is well established that in the LDF literature these moments are closely related to fundamental physiological parameters, i.e. concentration of moving erythrocytes and blood flow. In particular, we take advantage of the link between moments in the Fourier domain and fractional derivatives in the temporal domain. Using Parseval's theorem, we establish an exact analytical equivalence between the time-domain expression and the conventional frequency-domain counterpart. Moreover, we demonstrate the appropriateness of estimating the zeroth-, first- and second-order moments using Monte Carlo simulations. Finally, we briefly discuss the feasibility of implementing the proposed algorithm in hardware.

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This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

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An algorithm to improve the computation time of packing calculations for macromolecules is presented. This is achieved by reducing the three-dimensional search to a small set of two-dimensional searches.

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A number of AgI based fast ion conducting glasses, with a general formula AgI---Ag2O---MxOy (MxOy=MoO3, SeO3, WO3, V2O5, P2O5, GeO2, B2O3, As2O3, CrO3) have been studied. A chemical approach is made to investigate the origin of fast ion conduction in these glasses. An index known as Image tructural Image npinning Image umber, SUN (S), has been defined for the purpose, based on the unscreened nuclear charge of silver ions and the equilibrium lectronegativities of the halide-oxyanion matrix in these glasses. The variation of the glass transition temperature, Tg, conductivity, σ, and the energy of activation, Ea, with the concentration of AgI are discussed in the light of the structural unpinning number. Conductivities increase uniformly in any given glass series as a smooth function of S and level off at very high values. The entire range of conductivity appears to vary as ln Image , where ln σ0 corresponds roughly to the conductivity of the hypothetical AgI glass and “a” is a constant which could be obtained as the slope in the graph of ln Ea versus S. It is suggested that the increase in the concentration of AgI beyond 75–80 mole% in the glass is not advantageous from the conductivity point of view.

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The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

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Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO2 forcing of similar magnitude.In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen's ``fixed-SST forcing'' method.Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed.

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Silver iodide-based fast ion conducting glasses containing silver phosphate and silver borate have been studied. An attempt is made to identify the interaction between anions by studying the chemical shifts of31P and11B atoms in high resolution (HR) magic angle spinning (MAS) NMR spectra. Variation in the chemical shifts of31P or11B has been observed which is attributed to the change in the partial charge on the31P or11B. This is indicative of the change in the electronegativity of the anion matrix as a whole. This in turn is interpreted as due to significant interaction among anions. The significance of such interaction to the concept of structural unpinning of silver ions in fast ion conducting glasses is discussed.

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Myotonic dystrophies type 1 (DM1) and type 2 (DM2) are the most common forms of muscular dystrophy affecting adults. They are autosomal dominant diseases caused by microsatellite tri- or tetranucleotide repeat expansion mutations in transcribed but not translated gene regions. The mutant RNA accumulates in nuclei disturbing the expression of several genes. The more recently identified DM2 disease is less well known, yet more than 300 patients have been confirmed in Finland thus far, and the true number is believed to be much higher. DM1 and DM2 share some features in general clinical presentation and molecular pathology, yet they show distinctive differences, including disease severity and differential muscle and fiber type involvement. However, the molecular differences underlying DM1 and DM2 muscle pathology are not well understood. Although the primary tissue affected is muscle, both DMs show a multisystemic phenotype due to wide expression of the mutation-carrying genes. DM2 is particularly intriguing, as it shows an incredibly wide spectrum of clinical manifestations. For this reason, it constitutes a real diagnostic challenge. The core symptoms in DM2 include proximal muscle weakness, muscle pain, myotonia, cataracts, cardiac conduction defects and endocrinological disturbations; however, none of these is mandatory for the disease. Myalgic pains may be the most disabling symptom for decades, sometimes leading to incapacity for work. In addition, DM2 may cause major socio-economical consequences for the patient, if not diagnosed, due to misunderstanding and false stigmatization. In this thesis work, we have (I) improved DM2 differential diagnostics based on muscle biopsy, and (II) described abnormalities in mRNA and protein expression in DM1 and DM2 patient skeletal muscles, showing partial differences between the two diseases, which may contribute to muscle pathology in these diseases. This is the first description of histopathological differences between DM1 and DM2, which can be used in differential diagnostics. Two novel high-resolution applications of in situ -hybridization have been described, which can be used for direct visualization of the DM2 mutation in muscle biopsy sections, or mutation size determination on extended DNA-fibers. By measuring protein and mRNA expression in the samples, differential changes in expression patterns affecting contractile proteins, other structural proteins and calcium handling proteins in DM2 compared to DM1 were found. The dysregulation at mRNA level was caused by altered transciption and abnormal splicing. The findings reported here indicate that the extent of aberrant splicing is higher in DM2 compared to DM1. In addition, the described abnormalities to some extent correlate to the differences in fiber type involvement in the two disorders.

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In this thesis, I study the changing ladscape and human environment of the Mätäjoki Valley, West-Helsinki, using reconstructions and predictive modelling. The study is a part of a larger project funded by the city of Helsinki aming to map the past of the Mätäjoki Valley. The changes in landscape from an archipelago in the Ancylus Lake to a river valley are studied from 10000 to 2000 years ago. Alongside shore displacement, we look at the changing environment from human perspective and predict the location of dwelling sitesat various times. As a result, two map series were produced that show how the landscape changed and where inhabitance is predicted. To back them up, we have also looked at what previous research says about the history of the waterways, climate, vegetation and archaeology. The changing landscape of the river valley is reconstructed using GIS methods. For this purpose, new laser point data set was used and at the same time tested in the context landscape modelling. Dwelling sites were modeled with logistic regression analysis. The spatial predictive model combines data on the locations of the known dwelling sites, environmental factors and shore displacement data. The predictions were visualised into raster maps that show the predictions for inhabitance 3000 and 5000 years ago. The aim of these maps was to help archaeologists map potential spots for human activity. The produced landscape reconstructions clarified previous shore displacement studies of the Mätäjoki region and provided new information on the location of shoreline. From the shore displacement history of the Mätäjoki Valley arise the following stages: 1. The northernmost hills of the Mätäjoki Valley rose from Ancylus Lake approximately 10000 years ago. Shore displacement was fast during the following thousand years. 2. The area was an archipelago with a relatively steady shoreline 9000 7000 years ago. 8000 years ago the shoreline drew back in the middle and southern parts of the river valley because of the transgression of the Litorina Sea. 3. Mätäjoki was a sheltered bay of the Litorina Sea 6000 5000 years ago. The Vantaanjoki River started to flow into the Mätäjoki Valley approximately 5000 years ago. 4. The sediment plains in the southern part of the river valley rose from the sea rather quickly 5000 3000 years ago. Salt water still pushed its way into the southermost part of the valley 4000 years ago. 5. The shoreline proceeded to Pitäjänmäki rapids where it stayed at least a thousand years 3000 2000 years ago. The predictive models managed to predict the locations of dwelling sites moderately well. The most accurate predictions were found on the eastern shore and Malminkartano area. Of the environment variables sand and aspect of slope were found to have the best predictive power. From the results of this study we can conclude that the Mätäjoki Valley has been a favorable location to live especially 6000 5000 years ago when the climate was mild and vegetation lush. The laser point data set used here works best in shore displacement studies located in rural areas or if further specific palaeogeographic or hydrologic analysis in the research area is not needed.