994 resultados para Sampling rates


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Bioavailable water concentrations of polycyclic aromatic hydrocarbons (PAH), polychlorinated biphenyls (PCB) and organochlorine pesticides (OCP) were measured in the water column from Three Gorges Reservoir (TGR) collected in May 2008 using semipermeable membrane devices (SPMDs). The sampling sites spanned the whole reservoir from the upstream Chongqing to the great dam covering more than 600 km long distance with water flow velocities ranging from <0.05 to 1.5 m s(-1). This is the first experience of SPMD application in the biggest reservoir in the world. The results of water sampling rates based on performance reference compounds (PRC) were tested to be significantly correlated with water flow velocities in the big river. Results of back-calculated aqueous concentrations based on PRC showed obvious regional variations of PAH, PCB and OCP levels in the reservoir. Total PAH ranged from 13.8 to 97.2 ng L-1, with the higher concentrations occurring in the region of upstream and near the dam. Phenanthrene, fluoranthene, pyrene and chrysene were the predominant PAH compounds in TGR water. Total PCB ranged from 0.08 to 0.51 ng L-1, with the highest one occurring in the region near the dam. PCB 28, 52, 101, 138, 153, 180, 118 were the most abundant PCB congeners in the water. The total OCP ranged from 2.33 to 3.60 ng L-1 and the levels showed homogenous distribution in the whole reservoir. HCH, DDT and HCB, PeCB were the major compounds of OCP fingerprints. Based on water quality criteria, the TGR water could be designated as being polluted by HCB and PAH. Data on PAH, PCB and OCP concentrations found in this survey can be used as reference levels for future POP monitoring programmes in TGR. (C) 2009 Elsevier Ltd. All rights reserved.

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The application of fine-grain pipelining techniques in the design of high-performance wave digital filters (WDFs) is described. The problems of latency in feedback loops can be significantly reduced if computations are organized most significant, as opposed to least significant, bit first and if the results are fed back as soon as they are formed. The result is that chips can be designed which offer significantly higher sampling rates than otherwise can be obtained using conventional methods. How these concepts can be extended to the more challenging problem of WDFs is discussed. It is shown that significant increases in the sampling rate of bit-parallel circuits can be achieved using most significant bit first arithmetic.

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Background: Vaginal ring devices are being actively developed for controlled delivery of HIV microbicides and as multi-purpose prevention technology (MPT) products combining hormonal contraception with prevention of HIV and other sexually transmitted diseases. Presently, there is no reliable method for monitoring user adherence in HIV vaginal ring trials; previous acceptability studies have included some type of participant self-reporting mechanism, which have often been unreliable. More objective, quantitative and accurate methods for assessing adherence are needed.
Methods: A silicone elastomer vaginal ring containing an encapsulated miniature temperature recording device has been developed that can capture and store real-time temperature data during the period of designated use. Devices were tested in both simulated vaginal environments and following vaginal placement in cynomolgus macaques. Various use protocols and data sampling rates were tested to simulate typical patient usage scenarios. Results: The temperature logging devices accurately recorded vaginal temperature in macaques, clearly showing the regular diurnal temperature cycle. When environmental temperature and vaginal temperature was significantly different, the device was able to accurately pinpoint the insertion and removal times. Based on the data collected it was possible to infer removal periods as short as 5 min when the external environmental temperature was 25 °C. Accuracy increased with data sampling rate. Conclusions: This work provides proof-of-concept for monitoring adherence using a vaginal ring device containing an encapsulated temperature logger. The addition of one or more active agents into the ring body is not anticipated to affect the temperature monitoring function. A clinical study to compare self- reported user adherence data with that obtained by the device would be highly informative.

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The design and VLSI implementation of two key components of the class-IV partial response maximum likelihood channel (PR-IV) the adaptive filter and the Viterbi decoder are described. These blocks are implemented using parameterised VHDL modules, from a library of common digital signal processing (DSP) and arithmetic functions. Design studies, based on 0.6 micron 3.3V standard cell processes, indicate that worst case sampling rates of 49 mega-samples per second are achievable for this system, with proportionally high sampling rates for full custom designs and smaller dimension processes. Significant increases in the sampling rate, from 49 MHz to approximately 180 MHz, can be achieved by operating four filter modules in parallel, and this implementation has 50% lower power consumption than a pipelined filter operating at the same speed.

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On the basis of its electrochemical behaviour a new flow-injection analysis (FIA) method with amperometric detection has been developed for quantification of the herbicide bentazone (BTZ) in estuarine waters. Standard solutions and samples (200 µL) were injected into a water carrier stream and both pH and ionic strength were automatically adjusted inside the manifold. Optimization of critical FIA conditions indicated that the best analytical results were obtained at an oxidation potential of 1.10 V, pH 4.5, and an overall flow-rate of 2.4 mL min–1. Analysis of real samples was performed by means of calibration curves over the concentration range 2.5x10–6 to 5.0x10–5 mol L–1, and results were compared with those obtained by use of an independent method (HPLC). The accuracy of the amperometric determinations was ascertained; errors relative to the comparison method were below 4% and sampling rates were approximately 100 samples h–1. The repeatability of the proposed method was calculated by assessing the relative standard deviation (%) of ten consecutive determinations of one sample; the value obtained was 2.1%.

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In a sigma-delta analog to digital (A/D) As most of the sigma-delta ADC applications require converter, the most computationally intensive block is decimation filters with linear phase characteristics, the decimation filter and its hardware implementation symmetric Finite Impulse Response (FIR) filters are may require millions of transistors. Since these widely used for implementation. But the number of FIR converters are now targeted for a portable application, filter coefficients will be quite large for implementing a a hardware efficient design is an implicit requirement. narrow band decimation filter. Implementing decimation In this effect, this paper presents a computationally filter in several stages reduces the total number of filter efficient polyphase implementation of non-recursive coefficients, and hence reduces the hardware complexity cascaded integrator comb (CIC) decimators for and power consumption [2]. Sigma-Delta Converters (SDCs). The SDCs are The first stage of decimation filter can be operating at high oversampling frequencies and hence implemented very efficiently using a cascade of integrators require large sampling rate conversions. The filtering and comb filters which do not require multiplication or and rate reduction are performed in several stages to coefficient storage. The remaining filtering is performed reduce hardware complexity and power dissipation. either in single stage or in two stages with more complex The CIC filters are widely adopted as the first stage of FIR or infinite impulse response (IIR) filters according to decimation due to its multiplier free structure. In this the requirements. The amount of passband aliasing or research, the performance of polyphase structure is imaging error can be brought within prescribed bounds by compared with the CICs using recursive and increasing the number of stages in the CIC filter. The non-recursive algorithms in terms of power, speed and width of the passband and the frequency characteristics area. This polyphase implementation offers high speed outside the passband are severely limited. So, CIC filters operation and low power consumption. The polyphase are used to make the transition between high and low implementation of 4th order CIC filter with a sampling rates. Conventional filters operating at low decimation factor of '64' and input word length of sampling rate are used to attain the required transition '4-bits' offers about 70% and 37% of power saving bandwidth and stopband attenuation. compared to the corresponding recursive and Several papers are available in literature that deals non-recursive implementations respectively. The same with different implementations of decimation filter polyphase CIC filter can operate about 7 times faster architecture for sigma-delta ADCs. Hogenauer has than the recursive and about 3.7 times faster than the described the design procedures for decimation and non-recursive CIC filters.

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The similarity between electrochemical noise resistance (Rn) and polarization resistance (Rp) has been confirmed in many laboratories, and a new method for corrosion rate determination has been developed based upon this similarity. However, this method remains controversial. Some researchers have reported experimental results that did not support a similarity between Rp and Rn. Other researchers have found that this similarity does not hold true for every system. To address this controversy, factors affecting the measurement and calculation of Rn were investigated. Several factors - including instrument noise, direct current (DC) trend, noise sampling rates, and noise sampling duration - can affect the accuracy of Rn determination signiftcantly and, in some cases, can cause disagreement between Rn and Rp. It was recommended that a system check be carried out to avoid the influence of these factors.

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The fact that medical images have redundant information is exploited by researchers for faster image acquisition. Sample set or number of measurements were reduced in order to achieve rapid imaging. However, due to inadequate sampling, noise artefacts are inevitable in Compressive Sensing (CS) MRI. CS utilizes the transform sparsity of MR images to regenerate images from under sampled data. Locally sparsified Compressed Sensing is an extension of simple CS. It localises sparsity constraints for sub-regions rather than using a global constraint. This paper, presents a framework to use local CS for improving image quality without increasing sampling rate or without making the acquisition process any slower. This was achieved by exploiting local constraints. Localising image into independent sub-regions allows different sampling rates within image. Energy distribution of MR images is not even and most of noise occurs due to under-sampling in high energy regions. By sampling sub-regions based on energy distribution, noise artefacts can be minimized. Experiments were done using the proposed technique. Results were compared with global CS and summarized in this paper.

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GPS trajectory dataset with high sampling-rates is usually in large volume that challenges the processing efficiency. Most of the data points on trajectories are useless. This paper summarizes trajectories using stop points. We define a new concept of stay stability (i.e., time dividing distance or reciprocal of speed) between any two GPS points to detect stop points on individual trajectories. We propose a novel Mining Repeat Travel Behaviors Using Stop Regions (MRTBUSR) method. In MRTBUSR, a stop region is a popular region containing a certain number of close stop points that can be grouped into a cluster. We then retrieve common sequences of stop regions to denote repeat route patterns and further analyze the stop durations on a stop region to find repeat travel behaviors. The experiments on 20 labeled trajectories selected from GeoLife demonstrated the semantic effect, accuracy and near linear efficiency of our proposed method.

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In this paper a new algorithmic of Analog-to-Digital Converter is presented. This new topology use the current-mode technique that allows a large dynamic range and can be implemented in digital CMOS process. The ADC proposed is very small and can handle high sampling rates. Simulation results using a 1.2um CMOS process show that an 8-b ADC can support a sampling rate of 50MHz.

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This work analyses a real time orbit estimator using the raw navigation solution provided by GPS receivers. The estimation algorithm considers a Kalman filter with a rather simple orbit dynamic model and random walk modeling of the receiver clock bias and drift. Using the Topex/Poseidon satellite as test bed, characteristics of model truncation, sampling rates and degradation of the GPS receiver (Selective Availability) were analysed. Copyright © 2007 by ABCM.

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This article presents a new method to detect damage in structures based on the electromechanical impedance principle. The system follows the variations in the output voltage of piezoelectric transducers and does not compute the impedance itself. The proposed system is portable, autonomous, versatile, and could efficiently replace commercial instruments in different structural health monitoring applications. The identification of damage is performed by simply comparing the variations of root mean square voltage from response signals of piezoelectric transducers, such as lead zirconate titanate patches bonded to the structure, obtained for different frequencies of the excitation signal. The proposed system is not limited by the sampling rate of analog-to-digital converters, dispenses Fourier transform algorithms, and does not require a computer for processing, operating autonomously. A low-cost prototype based on microcontroller and digital synthesizer was built, and experiments were carried out on an aluminum structure and excellent results have been obtained. © The Author(s) 2012.

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A temperatura e umidade do solo são variáveis cujo conhecimento é fundamental para determinar os balanços de energia e água na biosfera. Os regimes térmico e hídrico dos solos sob cada ecossistema apresentam variações consideráveis, de acordo com sua mineralogia, o clima local e a vegetação. Nesse contexto, as temperaturas e umidades do solo foram medidas sob três ecossistemas existentes na região leste da Amazônia, a saber: floresta nativa (FLONA Caxiuanã, 01° 42' 30" S e 51° 31' 45" W), pastagem nativa (Soure, 00° 43' 25" S e 48° 30' 29" W) e área agrícola (!garapé-Açu, 01° 07' 59" S e 47° 36' 55" W). Os dados de campo na floresta e na pastagem foram coletados entre dezembro de 2001 e fevereiro de 2005; enquanto que na área agrícola, o monitoramento foi limitado de agosto de 2003 a fevereiro de 2005. Estas observações das variáveis físicas do solo foram analisadas levando em consideração as variáveis meteorológicas medidas simultaneamente tais como o fluxo de radiação solar incidente e a precipitação pluviométrica, que interferem diretamente nas variáveis do solo em cada sitio escolhido para estudo. As temperaturas do solo foram monitoradas por meio de sondas térmicas em profundidades de 0,05; 0,20 e 0,50 m. Fluxímetros de calor mediram esta variável em níveis de profundidade em 0,05 e 0,20 m. A umidade volumétrica do solo na camada superior de 0,30 m foi medida por sensor de sonda dupla por Reflectometria no Domínio do Tempo (TDR) em cada sitio. Foram feitas analises considerando as respostas do solo durante o período seco e chuvoso local, nestes três ecossistemas representativos do leste da Amazônia. Estimativas de difusividade térmica aparente do solo foram feitas pelos métodos da amplitude e da fase usando os dados de propagação do pulso diário de calor nesses solos. Os resultados mostraram valores bem diferentes, porém,no primeiro método pareceu mais confiável e adequado para o modelamento numérico. Como esperado, considerando a sua pouca cobertura vegetal, as temperaturas dos solos nos níveis superficiais, apresentaram grandes variações na pastagem e na área agrícola. Inesperadamente, as temperaturas na profundidade de 0,5 m abaixo da floresta mostraram maiores variações de amplitude que as profundidades de 0,20 e 0,05 m. O modelamento numérico das variações temporais da temperatura, em função da profundidade, para cada solo foi feito através do método harmônico Os resultados mostraram que o primeiro harmônico representou mais de 90% da variação total observada do pulso diário da temperatura da pastagem e área agrícola em 0,2 e 0,05 m de profundidade. Performance similar do modelamento foi observada na floresta nos níveis de 0,05 e 0,20 m. A magnitude dos fluxos de calor abaixo da pastagem e área agrícola atingiram valores seis vezes maiores que aqueles observados sob a floresta. Os resultados mostraram que, para a camada do solo superior de 0,30 m, a umidade volumétrica do solo sob a floresta é maior que sob os outros ecossistemas estudados neste trabalho. Este resultado é devido aparentemente; à proteção da floresta contra a evaporação da superfície do solo. Uma análise do comportamento sazonal e diário das temperaturas e umidade solos em resposta à radiação solar e precipitação é apresentada. Estudos de caso da taxa de perda da umidade do solo depois de significativa recarga de água por eventos de precipitação, também foram analisados. Algumas estimativas diárias de diminuição de água e recarga durante a noite e madrugada por subida de água de camadas subjacentes para a camada de 0.30 m foram feitas. Este trabalho analisou a maior serie temporal dos dados de temperatura e umidade dos solos coletados com alta freqüência de amostragem disponível até o momento, para o leste da Amazônia. Foi possível caracterizar as diferenças dos regimes destas variáveis físicas, abaixo de três ecossistemas importantes desta região. Estudos futuros dos minerais e materiais orgânicos nestes solos, bem como dos índices de área foliar e da biomassa das coberturas vegetais desses ecossistemas, melhoraria a compreensão dos regimes descritos neste trabalho.

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Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.

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In this thesis, we develop an adaptive framework for Monte Carlo rendering, and more specifically for Monte Carlo Path Tracing (MCPT) and its derivatives. MCPT is attractive because it can handle a wide variety of light transport effects, such as depth of field, motion blur, indirect illumination, participating media, and others, in an elegant and unified framework. However, MCPT is a sampling-based approach, and is only guaranteed to converge in the limit, as the sampling rate grows to infinity. At finite sampling rates, MCPT renderings are often plagued by noise artifacts that can be visually distracting. The adaptive framework developed in this thesis leverages two core strategies to address noise artifacts in renderings: adaptive sampling and adaptive reconstruction. Adaptive sampling consists in increasing the sampling rate on a per pixel basis, to ensure that each pixel value is below a predefined error threshold. Adaptive reconstruction leverages the available samples on a per pixel basis, in an attempt to have an optimal trade-off between minimizing the residual noise artifacts and preserving the edges in the image. In our framework, we greedily minimize the relative Mean Squared Error (rMSE) of the rendering by iterating over sampling and reconstruction steps. Given an initial set of samples, the reconstruction step aims at producing the rendering with the lowest rMSE on a per pixel basis, and the next sampling step then further reduces the rMSE by distributing additional samples according to the magnitude of the residual rMSE of the reconstruction. This iterative approach tightly couples the adaptive sampling and adaptive reconstruction strategies, by ensuring that we only sample densely regions of the image where adaptive reconstruction cannot properly resolve the noise. In a first implementation of our framework, we demonstrate the usefulness of our greedy error minimization using a simple reconstruction scheme leveraging a filterbank of isotropic Gaussian filters. In a second implementation, we integrate a powerful edge aware filter that can adapt to the anisotropy of the image. Finally, in a third implementation, we leverage auxiliary feature buffers that encode scene information (such as surface normals, position, or texture), to improve the robustness of the reconstruction in the presence of strong noise.