939 resultados para Spectral analysis method


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This article presents a thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum Exergetic Production Cost (EPC), based on the Second Law of Thermodynamics. The variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as final output. (C) 2003 Elsevier Ltd. All rights reserved.

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Low-frequency multipath is still one of the major challenges for high precision GPS relative positioning. In kinematic applications, mainly, due to geometry changes, the low-frequency multipath is difficult to be removed or modeled. Spectral analysis has a powerful technique to analyze this kind of non-stationary signals: the wavelet transform. However, some processes and specific ways of processing are necessary to work together in order to detect and efficiently mitigate low-frequency multipath. In this paper, these processes are discussed. Some experiments were carried out in a kinematic mode with a controlled and known vehicle movement. The data were collected in the presence of a reflector surface placed close to the vehicle to cause, mainly, low-frequency multipath. From theanalyses realized, the results in terms of double difference residuals and statistical tests showed that the proposed methodology is very efficient to detect and mitigate low-frequency multipath effects. © 2008 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Type Ia supernovae have been successfully used as standardized candles to study the expansion history of the Universe. In the past few years, these studies led to the exciting result of an accelerated expansion caused by the repelling action of some sort of dark energy. This result has been confirmed by measurements of cosmic microwave background radiation, the large-scale structure, and the dynamics of galaxy clusters. The combination of all these experiments points to a “concordance model” of the Universe with flat large-scale geometry and a dominant component of dark energy. However, there are several points related to supernova measurements which need careful analysis in order to doubtlessly establish the validity of the concordance model. As the amount and quality of data increases, the need of controlling possible systematic effects which may bias the results becomes crucial. Also important is the improvement of our knowledge of the physics of supernovae events to assure and possibly refine their calibration as standardized candle. This thesis addresses some of those issues through the quantitative analysis of supernova spectra. The stress is put on a careful treatment of the data and on the definition of spectral measurement methods. The comparison of measurements for a large set of spectra from nearby supernovae is used to study the homogeneity and to search for spectral parameters which may further refine the calibration of the standardized candle. One such parameter is found to reduce the dispersion in the distance estimation of a sample of supernovae to below 6%, a precision which is comparable with the current lightcurve-based calibration, and is obtained in an independent manner. Finally, the comparison of spectral measurements from nearby and distant objects is used to test the possibility of evolution with cosmic time of the intrinsic brightness of type Ia supernovae.

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The purpose of this research project is to study an innovative method for the stability assessment of structural steel systems, namely the Modified Direct Analysis Method (MDM). This method is intended to simplify an existing design method, the Direct Analysis Method (DM), by assuming a sophisticated second-order elastic structural analysis will be employed that can account for member and system instability, and thereby allow the design process to be reduced to confirming the capacity of member cross-sections. This last check can be easily completed by substituting an effective length of KL = 0 into existing member design equations. This simplification will be particularly useful for structural systems in which it is not clear how to define the member slenderness L/r when the laterally unbraced length L is not apparent, such as arches and the compression chord of an unbraced truss. To study the feasibility and accuracy of this new method, a set of 12 benchmark steel structural systems previously designed and analyzed by former Bucknell graduate student Jose Martinez-Garcia and a single column were modeled and analyzed using the nonlinear structural analysis software MASTAN2. A series of Matlab-based programs were prepared by the author to provide the code checking requirements for investigating the MDM. By comparing MDM and DM results against the more advanced distributed plasticity analysis results, it is concluded that the stability of structural systems can be adequately assessed in most cases using MDM, and that MDM often appears to be a more accurate but less conservative method in assessing stability.

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High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1(st) and 2(nd) ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

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Patients with diabetes mellitus (DM) often have alterations of the autonomic nervous system (ANS), even early in their disease course. Previous research has not evaluated whether these changes may have consequences on adaptation mechanisms in DM, e.g. to mental stress. We therefore evaluated whether patients with DM who already had early alterations of the ANS reacted with an abnormal regulatory pattern to mental stress. We used the spectral analysis technique, known to be valuable and reliable in the investigation of disturbances of the ANS. We investigated 34 patients with DM without clinical evidence of ANS dysfunction (e.g. orthostatic hypotension) and 44 normal control subjects (NC group). No patients on medication known to alter ANS responses were accepted. The investigation consisted of a resting state evaluation and a mental stress task (BonnDet). In basal values, only the 21 patients with type 2 DM were different in respect to body mass index and systolic blood pressure. In the study parameters we found significantly lower values in resting and mental stress spectral power of mid-frequency band (known to represent predominantly sympathetic influences) and of high-frequency and respiration bands (known to represent parasympathetic influences) in patients with DM (types 1 and 2) compared with NC group (5.3 +/- 1.2 ms2 vs. 6.1 +/- 1.3 ms2, and 5.5 +/- 1.6 ms2 vs. 6.2 +/- 1.5 ms2, and 4.6 +/- 1.7 ms2 vs. 6.2 +/- 1.5 ms2, for resting values respectively; 4.7 +/- 1.4 ms2 vs. 5.9 +/- 1.2 ms2, and 4.6 +/- 1.9 ms2 vs. 5.6 +/- 1.7 ms2, and 3.7 +/- 2.1 ms2 vs. 5.6 +/- 1.7 ms2, for stress values respectively; M/F ratio 6/26 vs. 30/14). These differences remained significant even when controlled for age, sex, and body weight. However, patients with DM type 2 (and significantly higher body weight) showed only significant values in mental stress modulus values. There were no specific group effects in the patients with DM in adaptation mechanisms to mental stress compared with the NC group. These findings demonstrate that power spectral examinations at rest are sufficiently reliable to diagnose early alterations in ANS in patients with DM. The spectral analysis technique is sensitive and reliable in investigation of ANS in patients with DM without clinically symptomatic autonomic dysfunction.