924 resultados para time domain analysis
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PURPOSE Based on a nation-wide database, this study analysed the influence of methotrexate (MTX), TNF inhibitors and a combination of the two on uveitis occurrence in JIA patients. METHODS Data from the National Paediatric Rheumatological Database in Germany were used in this study. Between 2002 and 2013, data from JIA patients were annually documented at the participating paediatric rheumatological sites. Patients with JIA disease duration of less than 12 months at initial documentation and ≥2 years of follow-up were included in this study. The impact of anti-inflammatory treatment on the occurrence of uveitis was evaluated by discrete-time survival analysis. RESULTS A total of 3,512 JIA patients (mean age 8.3±4.8 years, female 65.7%, ANA-positive 53.2%, mean age at arthritis onset 7.8±4.8 years) fulfilled the inclusion criteria. Mean total follow-up time was 3.6±2.4 years. Uveitis developed in a total of 180 patients (5.1%) within one year after arthritis onset. Uveitis onset after the first year was observed in another 251 patients (7.1%). DMARD treatment in the year before uveitis onset significantly reduced the risk for uveitis: MTX (HR 0.63, p=0.022), TNF inhibitors (HR 0.56, p<0.001) and a combination of the two (HR 0.10, p<0.001). Patients treated with MTX within the first year of JIA had an even a lower uveitis risk (HR 0.29, p<0.001). CONCLUSION The use of DMARDs in JIA patients significantly reduced the risk for uveitis onset. Early MTX use within the first year of disease and the combination of MTX with a TNF inhibitor had the highest protective effect. This article is protected by copyright. All rights reserved.
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The upper 1200 m of pre-Pliocene sediment recovered by Cape Roberts Project (CRP) drilling off the Victoria Land coast of Antarctica between 1997-1999 has been subdivided into 54 unconformity-bound stratigraphic sequences, spanning the period c. 32 to 17 Ma. The sequences are recognised on the basis of the cyclical vertical stacking of their constituent lithofacies, which are enclosed by erosion surfaces produced during the grounding of the advancing ice margin onto the sea floor. Each sequence represents deposition in a range of offshore shelf to coastal glacimarine sedimentary environments during oscillations in the ice margin across the Western Ross Sea shelf, and coeval fluctuations in water depth. This paper applies spectral analysis techniques to depth- and time-series of sediment grain size (500 samples) for intervals of the core with adequate chronological data. Time series analysis of 0.5-l.0m-spaced grainsize data spanning sequences 9-11 (CRP-2/2A) and sequences 1-7 (CRP-3) suggests that the length of individual sequences correspond to Milankovitch frequencies, probably 41 k.y., but possibly as low as 100 k.y. Higher frequency periodic components at 23 k.y. (orbital precession) and 15-10 k.y. (sub-orbital) are recognised at the intrasequence-scale, and may represent climatic cycles akin to the ice rafting episodes described in the North Atlantic Ocean during the Quaternary. The cyclicity recorded by glacimarine sequences in CRP core provides direct evidence from the periphery of Antarctica for orbital oscillations in the size of the Oligocene-Early Miocene East Antarctic Ice Sheet.
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Detailed stable isotopic and calcium carbonate records (with a sampling resolution of 3000 yr.) from the middle Miocene section of hydraulic piston corer (HPC) Hole 574A provide a sequence that records the major shift in the oxygen isotopic composition of the world's oceans that occurred at about 14 Ma. The data suggest that this transition was rapid and spans about 30,000 yr. of sediment deposition. In intervals before and after the shift, the mean d18O values are characterized by a constant mean with a high degree of variability. The degree of variability in both the d18O and d13C records is comparable to that observed for the Pliocene and earliest Pleistocene and does not show a significant change before or after the major shift in the d18O record. Whereas the oxygen isotopic record is characterized by relatively stable mean values before and after the middle Miocene event, the d13C record shows a number of significant offsets in the mean value separated by intervals of high-frequency variations. Time and frequency domain analysis of all records from Hole 574A indicate that the frequency components shown to be related to orbital changes in the Pleistocene record are also present in the middle Miocene. The high variability observed in the Site 574 isotopic records places important constraints on models describing the role of formation of the Antarctic ice sheet during the middle Miocene climatic transitions. Thus, HPC Hole 574A provides a valuable sequence for detailed study of climatic variability during an important time in the Earth's history, although we cannot provide a definitive explanation of the major oxygen isotopic event of the middle Miocene.
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Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.
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production, during the summer of 2010. This farm is integrated at the Spanish research network for the sugar beet development (AIMCRA) which regarding irrigation, focuses on maximizing water saving and cost reduction. According to AIMCRA 0 s perspective for promoting irrigation best practices, it is essential to understand soil response to irrigation i.e. maximum irrigation length for each soil infiltration capacity. The Use of Humidity Sensors provides foundations to address soil 0 s behavior at the irrigation events and, therefore, to establish the boundaries regarding irrigation length and irrigation interval. In order to understand to what extent farmer 0 s performance at Tordesillas farm could have been potentially improved, this study aims to address suitable irrigation length and intervals for the given soil properties and evapotranspiration rates. In this sense, several humidity sensors were installed: (1) A Frequency Domain Reflectometry (FDR) EnviroScan Probe taking readings at 10, 20, 40 and 60cm depth and (2) different Time Domain Reflectometry (TDR) Echo 2 and Cr200 probes buried in a 50cm x 30cm x 50cm pit and placed along the walls at 10, 20, 30 and 40 cm depth. Moreover, in order to define soil properties, a textural analysis at the Tordesillas Farm was conducted. Also, data from the Tordesillas meteorological station was utilized.
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This article presents a time domain approach to the flutter analysis of a missile-type wing/body configuration with concentrated structural non-linearities. The missile wing is considered fully movable and its rotation angle contains the structural freeplay-type non-linearity. Although a general formulation for flexible configurations is developed, only two rigid degrees of freedom are taken into account for the results: pitching of the whole wing/body configuration and wing rotation angle around its hinge. An unsteady aerodynamic model based on the slender-body approach is used to calculate aerodynamic generalized forces. Limit-cycle oscillations and chaotic motion below the flutter speed are observed in this study.
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Compile-time program analysis techniques can be applied to Web service orchestrations to prove or check various properties. In particular, service orchestrations can be subjected to resource analysis, in which safe approximations of upper and lower resource usage bounds are deduced. A uniform analysis can be simultaneously performed for different generalized resources that can be directiy correlated with cost- and performance-related quality attributes, such as invocations of partners, network traffic, number of activities, iterations, and data accesses. The resulting safe upper and lower bounds do not depend on probabilistic assumptions, and are expressed as functions of size or length of data components from an initiating message, using a finegrained structured data model that corresponds to the XML-style of information structuring. The analysis is performed by transforming a BPEL-like representation of an orchestration into an equivalent program in another programming language for which the appropriate analysis tools already exist.
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Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration
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Mealiness is a textural attribute related to an internal fruit disorder that involves quality loss. It is characterised by the combination of abnormal softness of the fruit and absence of free juiciness in the mouth when eaten by the consumer. Recent research concluded with the development of precise instrumental procedure to measure a scale of mealiness based on the combination of several rheological properties and empirical magnitudes. In this line, time-domain laser reflectance spectroscopy (TDRS) is a medical technology, new in agrofood research, which is capable of obtaining physical and chemical information independently and simultaneously, and this can be of interest to characterise mealiness. Using VIS & NIR lasers as light sources, TDRS was applied in this work to Golden Delicious and Cox apples (n=90), conforming several batches of untreated samples and storage-treated (20°C & 95%RH) to promote the development of mealiness. The collected database was clustered into different groups according to their instrumental test values (Barreiro et al, 1998). The optical coefficients were used as explanatory variables when building discriminant analysis functions for mealiness, achieving a classification score above 80% of correctly identified mealy versus fresh apples.
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This paper presents a time-domain stochastic system identification method based on maximum likelihood estimation (MLE) with the expectation maximization (EM) algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. The benchmark structure is a four-story, two-bay by two-bay steel-frame scale model structure built in the Earthquake Engineering Research Laboratory at the University of British Columbia, Canada. This paper focuses on Phase I of the analytical benchmark studies. A MATLAB-based finite element analysis code obtained from the IASC-ASCE SHM Task Group web site is used to calculate the dynamic response of the prototype structure. A number of 100 simulations have been made using this MATLAB-based finite element analysis code in order to evaluate the proposed identification method. There are several techniques to realize system identification. In this work, stochastic subspace identification (SSI)method has been used for comparison. SSI identification method is a well known method and computes accurate estimates of the modal parameters. The principles of the SSI identification method has been introduced in the paper and next the proposed MLE with EM algorithm has been explained in detail. The advantages of the proposed structural identification method can be summarized as follows: (i) the method is based on maximum likelihood, that implies minimum variance estimates; (ii) EM is a computational simpler estimation procedure than other optimization algorithms; (iii) estimate more parameters than SSI, and these estimates are accurate. On the contrary, the main disadvantages of the method are: (i) EM algorithm is an iterative procedure and it consumes time until convergence is reached; and (ii) this method needs starting values for the parameters. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using both the SSI method and the proposed MLE + EM method. The numerical results show that the proposed method identifies eigenfrequencies, damping ratios and mode shapes reasonably well even in the presence of 10% measurement noises. These modal parameters are more accurate than the SSI estimated modal parameters.
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Recently a new recipe for developing and deploying real-time systems has become increasingly adopted in the JET tokamak. Powered by the advent of x86 multi-core technology and the reliability of the JET’s well established Real-Time Data Network (RTDN) to handle all real-time I/O, an official Linux vanilla kernel has been demonstrated to be able to provide realtime performance to user-space applications that are required to meet stringent timing constraints. In particular, a careful rearrangement of the Interrupt ReQuests’ (IRQs) affinities together with the kernel’s CPU isolation mechanism allows to obtain either soft or hard real-time behavior depending on the synchronization mechanism adopted. Finally, the Multithreaded Application Real-Time executor (MARTe) framework is used for building applications particularly optimised for exploring multicore architectures. In the past year, four new systems based on this philosophy have been installed and are now part of the JET’s routine operation. The focus of the present work is on the configuration and interconnection of the ingredients that enable these new systems’ real-time capability and on the impact that JET’s distributed real-time architecture has on system engineering requirements, such as algorithm testing and plant commissioning. Details are given about the common real-time configuration and development path of these systems, followed by a brief description of each system together with results regarding their real-time performance. A cycle time jitter analysis of a user-space MARTe based application synchronising over a network is also presented. The goal is to compare its deterministic performance while running on a vanilla and on a Messaging Real time Grid (MRG) Linux kernel.
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System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system" [1]. In the context of civil engineering, the system refers to a large scale structure such as a building, bridge, or an offshore structure, and identification mostly involves the determination of modal parameters (the natural frequencies, damping ratios, and mode shapes). This paper presents some modal identification results obtained using a state-of-the-art time domain system identification method (data-driven stochastic subspace algorithms [2]) applied to the output-only data measured in a steel arch bridge. First, a three dimensional finite element model was developed for the numerical analysis of the structure using ANSYS. Modal analysis was carried out and modal parameters were extracted in the frequency range of interest, 0-10 Hz. The results obtained from the finite element modal analysis were used to determine the location of the sensors. After that, ambient vibration tests were conducted during April 23-24, 2009. The response of the structure was measured using eight accelerometers. Two stations of three sensors were formed (triaxial stations). These sensors were held stationary for reference during the test. The two remaining sensors were placed at the different measurement points along the bridge deck, in which only vertical and transversal measurements were conducted (biaxial stations). Point estimate and interval estimate have been carried out in the state space model using these ambient vibration measurements. In the case of parametric models (like state space), the dynamic behaviour of a system is described using mathematical models. Then, mathematical relationships can be established between modal parameters and estimated point parameters (thus, it is common to use experimental modal analysis as a synonym for system identification). Stable modal parameters are found using a stabilization diagram. Furthermore, this paper proposes a method for assessing the precision of estimates of the parameters of state-space models (confidence interval). This approach employs the nonparametric bootstrap procedure [3] and is applied to subspace parameter estimation algorithm. Using bootstrap results, a plot similar to a stabilization diagram is developed. These graphics differentiate system modes from spurious noise modes for a given order system. Additionally, using the modal assurance criterion, the experimental modes obtained have been compared with those evaluated from a finite element analysis. A quite good agreement between numerical and experimental results is observed.
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The analysis of deformation in soils is of paramount importance in geotechnical engineering. For a long time the complex behaviour of natural deposits defied the ingenuity of engineers. The time has come that, with the aid of computers, numerical methods will allow the solution of every problem if the material law can be specified with a certain accuracy. Boundary Techniques (B.E.) have recently exploded in a splendid flowering of methods and applications that compare advantegeously with other well-established procedures like the finite element method (F.E.). Its application to soil mechanics problems (Brebbia 1981) has started and will grow in the future. This paper tries to present a simple formulation to a classical problem. In fact, there is already a large amount of application of B.E. to diffusion problems (Rizzo et al, Shaw, Chang et al, Combescure et al, Wrobel et al, Roures et al, Onishi et al) and very recently the first specific application to consolidation problems has been published by Bnishi et al. Here we develop an alternative formulation to that presented in the last reference. Fundamentally the idea is to introduce a finite difference discretization in the time domain in order to use the fundamental solution of a Helmholtz type equation governing the neutral pressure distribution. Although this procedure seems to have been unappreciated in the previous technical literature it is nevertheless effective and straightforward to implement. Indeed for the special problem in study it is perfectly suited, because a step by step interaction between the elastic and flow problems is needed. It allows also the introduction of non-linear elastic properties and time dependent conditions very easily as will be shown and compares well with performances of other approaches.
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The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.
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En este proyecto se van a aplicar las técnicas de análisis de ruido para caracterizar la respuesta dinámica de varios sensores de temperatura, tanto termorresistencias de platino como de termopares. Estos sensores son imprescindibles para él correcto funcionamiento de las centrales nucleares y requieren vigilancia para garantizar la exactitud de las medidas. Las técnicas de análisis de ruido son técnicas pasivas, es decir, no afectan a la operación de la planta y permiten realizar una vigilancia in situ de los sensores. Para el caso de los sensores de temperatura, dado que se pueden asimilar a sistemas de primer orden, el parámetro fundamental a vigilar es el tiempo de respuesta. Éste puede obtenerse para cada una de las sondas por medio de técnicas en el dominio de la frecuencia (análisis espectral) o por medio de técnicas en el dominio del tiempo (modelos autorregresivos). Además de la estimación del tiempo de respuesta, se realizará una caracterización estadística de las sondas. El objetivo es conocer el comportamiento de los sensores y vigilarlos de manera que se puedan diagnosticar las averías aunque éstas estén en una etapa incipiente. ABSTRACT In this project we use noise analysis technique to study the dynamic response of RTDs (Resistant temperature detectors) and thermocouples. These sensors are essential for the proper functioning of nuclear power plants and therefore need to be monitored to guarantee accurate measurements. The noise analysis techniques do not affect plant operation and allow in situ monitoring of the sensors. Temperature sensors are equivalent to first order systems. In these systems the main parameter to monitor is the response time which can be obtained by means of techniques in the frequency domain (spectral analysis) as well as time domain (autoregressive models). Besides response time estimation the project will also include a statistical study of the probes. The goal is to understand the behavior of the sensors and monitor them in order to detect any anomalies or malfunctions even if they occur in an early stage.