950 resultados para approximate analytical optical transfer function
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Spatially dense observations of gust speeds are necessary for various applications, but their availability is limited in space and time. This work presents an approach to help to overcome this problem. The main objective is the generation of synthetic wind gust velocities. With this aim, theoretical wind and gust distributions are estimated from 10 yr of hourly observations collected at 123 synoptic weather stations provided by the German Weather Service. As pre-processing, an exposure correction is applied on measurements of the mean wind velocity to reduce the influence of local urban and topographic effects. The wind gust model is built as a transfer function between distribution parameters of wind and gust velocities. The aim of this procedure is to estimate the parameters of gusts at stations where only wind speed data is available. These parameters can be used to generate synthetic gusts, which can improve the accuracy of return periods at test sites with a lack of observations. The second objective is to determine return periods much longer than the nominal length of the original time series by considering extreme value statistics. Estimates for both local maximum return periods and average return periods for single historical events are provided. The comparison of maximum and average return periods shows that even storms with short average return periods may lead to local wind gusts with return periods of several decades. Despite uncertainties caused by the short length of the observational records, the method leads to consistent results, enabling a wide range of possible applications.
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The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics.
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Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.
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A method is proposed for merging different nadir-sounding climate data records using measurements from high-resolution limb sounders to provide a transfer function between the different nadir measurements. The two nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global-mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present, and providing a simple framework for extending the SSU record into the future using AMSU. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The near-global-mean linear temperature trends for extended SSU for 1980–2012 are −0.63 ± 0.13, −0.71 ± 0.15 and −0.80 ± 0.17 K decade−1 (95 % confidence) for channels 1, 2 and 3, respectively. The extended SSU temperature changes are in good agreement with those from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004 to 2012. The extended SSU record is found to be in agreement with high-top coupled atmosphere–ocean models over the 1980–2012 period, including the continued cooling over the first decade of the 21st century.
Examining the relationships between Holocene climate change, hydrology, and human society in Ireland
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This thesis explores human-environment interactions during the Mid-Late Holocene in raised bogs in central Ireland. The raised bogs of central Ireland are widely-recognised for their considerable palaeoenvironmental and archaeological resources: research over the past few decades has established the potential for such sites to preserve sensitive records of Holocene climatic variability expressed as changes in bog surface wetness (BSW); meanwhile archaeological investigations over the past century have uncovered hundreds of peatland archaeological features dating from the Neolithic through to the Post-Medieval period including wooden trackways, platforms, and deposits of high-status metalwork. Previous studies have attempted to explore the relationship between records of past environmental change and the occurrence of peatland archaeological sites reaching varying conclusions. More recently, environmentally-deterministic models of human-environment interaction in Irish raised bogs at the regional scale have been explicitly tested leading to the conclusion that there is no relationship between BSW and past human activity. These relationships are examined in more detail on a site-by-site basis in this thesis. To that end, testate amoebae-derived BSW records from nine milled former raised bogs in central Ireland were produced from sites with known and dated archaeological records. Relationships between BSW records and environmental conditions within the study area were explored through both the development of a new central Ireland testate amoebae transfer function and through comparisons between recent BSW records and instrumental weather data. Compilation of BSW records from the nine fossil study sites show evidence both for climate forcing, particularly during 3200-2400 cal BP, as well as considerable inter-site variability. Considerable inter-site variability was also evident in the archaeological records of the same sites. Whilst comparisons between BSW and archaeological records do not show a consistent linear relationship, examination of records on a site-by-site basis were shown to reveal interpretatively important contingent relationships. It is concluded therefore, that future research on human-environment interactions should focus on individual sites and should utilise theoretical approaches from the humanities in order to avoid the twin pitfalls of masking important local patterns of change, and of environmental determinism.
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Separating edaphic impacts on tree distributions from those of climate and geography is notoriously difficult. Aboveground and belowground factors play important roles, and determining their relative contribution to tree success will greatly assist in refining predictive models and forestry strategies in a changing climate. In a common glasshouse, seedlings of interior Douglas-fir (Pseudotsuga menziesii var. glauca) from multiple populations were grown in multiple forest soils. Fungicide was applied to half of the seedlings to separate soil fungal and nonfungal impacts on seedling performance. Soils of varying geographic and climatic distance from seed origin were compared, using a transfer function approach. Seedling height and biomass were optimized following seed transfer into drier soils, whereas survival was optimized when elevation transfer was minimised. Fungicide application reduced ectomycorrhizal root colonization by c. 50%, with treated seedlings exhibiting greater survival but reduced biomass. Local adaptation of Douglas-fir populations to soils was mediated by soil fungi to some extent in 56% of soil origin by response variable combinations. Mediation by edaphic factors in general occurred in 81% of combinations. Soil biota, hitherto unaccounted for in climate models, interacts with biogeography to influence plant ranges in a changing climate.
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In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.
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We study the influence of ferromagnetic and antiferromagnetic bond defects on the ground-state energy of antiferromagnetic spin chains. In the absence of translational invariance, the energy spectrum of the full Hamiltonian is obtained numerically, by an iterative modi. cation of the power algorithm. In parallel, approximate analytical energies are obtained from a local-bond approximation, proposed here. This approximation results in significant improvement upon the mean-field approximation, at negligible extra computational effort. (C) 2008 Published by Elsevier B.V.
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This paper examined the transmission mechanism of international prices of agricultural commodities into the real exchange rate in Brazil for the period from January 2000 to February 2010. We used time series models (ARIMA Model, Transfer Model, Intervention Analysis, Johansen Cointegration Test) in determination of the short and long run elasticities. Transfer Function Model results show that changes in international prices of agricultural commodities are transmitted to the real exchange rate in Brazil in the short run, however, that transmission is less than unity, thus configuring the inelastic relationship. Johansen cointegration tests show that these variables are not co-integrated, no longer converge to the long-run equilibrium. These results are in agreement Cashim et al. (2004), which also found no long run relationship between real exchange rate and commodity prices in the case of Brazil. These results show that monetary shocks have greater weight on changes of the real exchange rate than real shocks.
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In this work, a performance analysis of transmission schemes employing turbo trellis coded modulation. In general, the performance analysis of such schemes is guided by evaluating the error probability of these schemes. The exact evaluation of this probability is very complex and inefficient from the computational point of view, a widely used alternative is the use of union bound of error probability, because of its easy implementation and computational produce bounds that converge quickly. Since it is the union bound, it should use to expurge some elements of distance spectrum to obtain a tight bound. The main contribution of this work is that the listing proposal is carried out from the puncturing at the level of symbol rather than bit-level as in most works of literature. The main reason for using the symbol level puncturing lies in the fact that the enummerating function of the turbo scheme is obtained directly from complex sequences of signals through the trellis and not indirectly from the binary sequences that require further binary to complex mapping, as proposed by previous works. Thus, algorithms can be applied through matrix from the adjacency matrix, which is obtained by calculating the distances of the complex sequences of the trellis. This work also presents two matrix algorithms for state reduction and the evaluation of the transfer function of this. The results presented in comparisons of the bounds obtained using the proposed technique with some turbo codes of the literature corroborate the proposition of this paper that the expurgated bounds obtained are quite tight and matrix algorithms are easily implemented in any programming software language
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Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to reduce elevated blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient are time varying. the objective of the study is to develop a procedure for blood pressure control i the presence of uncertainty of parameters and considerable time delays. So, a methodology was developed multi-model, and for each such model a Preditive Controller can be a priori designed. An adaptive mechanism is then needed for deciding which controller should be dominant for a given plant
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Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature
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Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction of block diagrams for systems with complex interrelationships. Signal-flow graphs reduction can be made without graphic manipulations of diagrams, and it is attractive for a computational implementation. In this paper the authors propose a computational method for direct reduction of signal-flow graphs. This method uses results presented in this paper about the calculation of literal determinants without symbolic mathematics tools. The Cramer's rule is applied for the solution of a set of linear equations, A program in MATLAB language for reduction of signal-flow graphs with the proposed method is presented.
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This paper presents a hybrid way mixing time and frequency domain for transmission lines modelling. The proposed methodology handles steady fundamental signal mixed with fast and slow transients, including impulsive and oscillatory behaviour. A transmission line model is developed based on lumped elements representation and state-space techniques. The proposed methodology represents an easy and practical procedure to model a three-phase transmission line directly in time domain, without the explicit use of inverse transforms. The proposed methodology takes into account the frequency-dependent parameters of the line, considering the soil and skin effects. In order to include this effect in the state matrices, a fitting method is applied. Furthermore the accuracy of proposed the developed model is verified, in frequency domain, by a simple methodology based on line distributed parameters and transfer function related to the input/output signals of the lumped parameters representation. In addition, this article proposes the use of a fast and robust analytic integration procedure to solve the state equations, enabling transient and steady-state simulations. The results are compared with those obtained by the commercial software Microtran (EMTP), taking into account a three-phase transmission line, typical in the Brazilian transmission system.
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This article shows a transmission line model for simulation of fast and slow transients, applied to symmetrical or asymmetrical configurations. A transmission line model is developed based on lumped elements representation and state-space techniques. The proposed methodology represents a practical procedure to model three-phase transmission lines directly in time domain, without the explicit or implicit use of inverse transforms. In three-phase representation, analysis modal techniques are applied to decouple the phases in their respective propagation modes, using a correction procedure to set a real and constant matrix for untransposed lines with or without vertical symmetry plane. The proposed methodology takes into account the frequency-dependent parameters of the line and in order to include this effect in the state matrices, a fitting procedure is applied. To verify the accuracy of the proposed state-space model in frequency domain, a simple methodology is described based on line distributed parameters and transfer function associated with input/output signals of the lumped parameters representation. In addition, this article proposes the use of a fast and robust integration procedure to solve the state equations, enabling transient and steady-state simulations. The results obtained by the proposed methodology are compared with several established transmission line models in EMTP, taking into account an asymmetrical three-phase transmission line. The principal contribution of the proposed methodology is to handle a steady fundamental signal mixed with fast and slow transients, including impulsive and oscillatory behavior, by a practical procedure applied directly in time domain for symmetrical or asymmetrical representations. (C) 2011 Elsevier Ltd. All rights reserved.