959 resultados para local processing bias


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Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

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This paper proposes a denoising algorithm which performs non-local means bilateral filtering. As existing literature suggests, non-local means (NLM) is one of the widely used denoising techniques, but has a critical drawback of smoothing of edges. In order to improve this, we perform fast and efficient NLM using Approximate Nearest Neighbour Fields and improve the edge content in denoising by formulating a joint-bilateral filter. Using the proposed joint bilateral, we are able to denoise smooth regions using the NLM approach and efficient edge reconstruction is obtained from the bilateral filter. Furthermore, to avoid tedious parameter selection, we carry out a noise estimation before performing joint bilateral filtering. The proposed approach is observed to perform well on high noise images.

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Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

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Hydrogen rearrangements at the H*2 complex are used as a model of low energy, local transitions in the two-hydrogen density of states of hydrogenated amorphous silicon (a-Si:H). These are used to account for the low activation energy motion of H observed by nuclear magnetic resonance, the low energy defect annealing of defects formed by bias stress in thin film transistors, and the elimination of hydrogen from the growth zone during the low temperature plasma deposition of a-Si:H. © 1998 Elsevier Science B.V. All rights reserved.

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This study addresses the problem of obtaining reliable velocities and displacements from accelerograms, a concern which often arises in earthquake engineering. A closed-form acceleration expression with random parameters is developed to test any strong-motion accelerogram processing method. Integration of this analytical time history yields the exact velocities, displacements and Fourier spectra. Noise and truncation can also be added. A two-step testing procedure is proposed and the original Volume II routine is used as an illustration. The main sources of error are identified and discussed. Although these errors may be reduced, it is impossible to extract the true time histories from an analog or digital accelerogram because of the uncertain noise level and missing data. Based on these uncertainties, a probabilistic approach is proposed as a new accelerogram processing method. A most probable record is presented as well as a reliability interval which reflects the level of error-uncertainty introduced by the recording and digitization process. The data is processed in the frequency domain, under assumptions governing either the initial value or the temporal mean of the time histories. This new processing approach is tested on synthetic records. It induces little error and the digitization noise is adequately bounded. Filtering is intended to be kept to a minimum and two optimal error-reduction methods are proposed. The "noise filters" reduce the noise level at each harmonic of the spectrum as a function of the signal-to-noise ratio. However, the correction at low frequencies is not sufficient to significantly reduce the drifts in the integrated time histories. The "spectral substitution method" uses optimization techniques to fit spectral models of near-field, far-field or structural motions to the amplitude spectrum of the measured data. The extremes of the spectrum of the recorded data where noise and error prevail are then partly altered, but not removed, and statistical criteria provide the choice of the appropriate cutoff frequencies. This correction method has been applied to existing strong-motion far-field, near-field and structural data with promising results. Since this correction method maintains the whole frequency range of the record, it should prove to be very useful in studying the long-period dynamics of local geology and structures.

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As borne out by everyday social experience, social cognition is highly dependent on context, modulated by a host of factors that arise from the social environment in which we live. While streamlined laboratory research provides excellent experimental control, it can be limited to telling us about the capabilities of the brain under artificial conditions, rather than elucidating the processes that come into play in the real world. Consideration of the impact of ecologically valid contextual cues on social cognition will improve the generalizability of social neuroscience findings also to pathology, e.g., to psychiatric illnesses. To help bridge between laboratory research and social cognition as we experience it in the real world, this thesis investigates three themes: (1) increasing the naturalness of stimuli with richer contextual cues, (2) the potentially special contextual case of social cognition when two people interact directly, and (3) a third theme of experimental believability, which runs in parallel to the first two themes. Focusing on the first two themes, in work with two patient populations, we explore neural contributions to two topics in social cognition. First, we document a basic approach bias in rare patients with bilateral lesions of the amygdala. This finding is then related to the contextual factor of ambiguity, and further investigated together with other contextual cues in a sample of healthy individuals tested over the internet, finally yielding a hierarchical decision tree for social threat evaluation. Second, we demonstrate that neural processing of eye gaze in brain structures related to face, gaze, and social processing is differently modulated by the direct presence of another live person. This question is investigated using fMRI in people with autism and controls. Across a range of topics, we demonstrate that two themes of ecological validity — integration of naturalistic contextual cues, and social interaction — influence social cognition, that particular brain structures mediate this processing, and that it will be crucial to study interaction in order to understand disorders of social interaction such as autism.

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(Sardinella) are available all year round in Sierra Leone. The best time to use them for baiting herrings is during the dry season when they are fattest and feeding well. The most common method of processing herring locally is hot smoking to give either soft, moist and cooked product or a dry, brittle product with very low moisture content. The author describes a curing method intended to add variety to the types of products that can be obtained from local herring. It is only mildly preservative, the product cannot be kept more than 24 hours without refrigeration. Particular attention is paid to the source and quality of the raw material used, and the processing method is detailed with attention to washing, splitting, brining, smoking, and the application of the Torry fish smoking kiln to the process.

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Sinais diversos estão presentes em nosso cotidiano, assim como nas medidas realizadas nas atividades de ciência e tecnologia. Dentre estes sinais, tem grande importância tecnológica aqueles associados à corrosão de estruturas metálicas. Assim, esta tese propõe o estudo de um esquema local de transformada de Fourier janelada, com a janela variando em função da curtose, aplicada a sinais de ruído eletroquímico. A curtose foi avaliada nos domínios do tempo e da frequência e processada pelo programa desenvolvido para esse fim. O esquema foi aplicado a sinais de ruído eletroquímico dos aços UNS S31600, UNS G10200 e UNS S32750 imersos em três soluções: FeCl3 0,1 mol=L (cloreto férrico), H2SO4 5%(ácido sulfúrico) e NaOH 0,1%(hidróxido de sódio). Para os aços inoxidáveis, estas soluções promovem corrosão localizada, uniforme e passivação, respectivamente. Visando testar o desempenho do esquema de Fourier desenvolvido, testes foram realizados utilizando-se inicialmente sinais sintéticos e em seguida sinais de ruído eletroquímico. Notou-se que os sinais têm características de não-estacionaridade e a maior parte da energia está presente em baixa frequência. Os intervalos de tempo e de frequência onde se concentra a maior parte da energia do sinal foram correlacionados. Para os picos máximos dos sinais de potencial e corrente obtidos de amperimetria de resistência nula, a correlação entre eles foi baixa, independente da forma de corrosão presente. Conclui-se que o método se adaptou bastante bem às características locais do sinal eletroquímico permitindo o monitoramento dos espectros tempo-frequência. O fato de ser sensível às características locais do sinal permite analisar aspectos dos sinais que do modo clássico não podem ser diretamente processados. O método da transformada de Fourier janelada variável (Variable Short-Time Fourier Transform - VSTFT) adaptou-se muito bem no monitoramento dos sinais originados de potencial de circuito aberto e amperimetria de resistência nula.

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The fishery sector in Uganda has seen important changes in the last two decades. Among the changes registered, is the expansion of fish markets locally, regionally and internationally. Upon which, remarkable benefits have been realized at local and national levels, for instance, it is estimated that an average of 40m$ is being earned annually as foreign exchange. Besides, presently fish accounts for over 50% of total animal protein in take. However, it is argued that sustaining these gains has become an up hill task due to failure to maintain fish quality as a result of the rudimentary and inappropriate sanitary, fish handling and artisanal fish processing practices that both directly and indirectly affect the quality of fish and fish products. Therefore, against this background, a study of 507 respondents was undertaken among the Lake Victoria Communities specifically in Wakiso, Mayuge and Mukono districts. The study examined the perceptions of fishers on the social cultural practices of sanitation, fish handling and artisanal fish processing and consequently identified factors that influenced these practices.

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The agar-bearing seaweeds Gracilaria and Gelidium grow abundantly in the Asia-Pacific region. Production and post-harvest techniques and methods for processing Gracilaria to produce agar suitable for local market is necessary to increase the meager income of coastal dwellers. A flow diagram of a village level agar production is provided. A guide is also given for the quality of dried seaweeds, which are divided into 3 classes.

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State and regional policies, such as low carbon fuel standards (LCFSs), increasingly mandate that transportation fuels be examined according to their greenhouse gas (GHG) emissions. We investigate whether such policies benefit from determining fuel carbon intensities (FCIs) locally to account for variations in fuel production and to stimulate improvements in FCI. In this study, we examine the FCI of transportation fuels on a lifecycle basis within a specific state, Minnesota, and compare the results to FCIs using national averages. Using data compiled from 18 refineries over an 11-year period, we find that ethanol production is highly variable, resulting in a 42% difference between carbon intensities. Historical data suggests that lower FCIs are possible through incremental improvements in refining efficiency and the use of biomass for processing heat. Stochastic modeling of the corn ethanol FCI shows that gains in certainty due to knowledge of specific refinery inputs are overwhelmed by uncertainty in parameters external to the refiner, including impacts of fertilization and land use change. The LCA results are incorporated into multiple policy scenarios to demonstrate the effect of policy configurations on the use of alternative fuels. These results provide a contrast between volumetric mandates and LCFSs. © 2011 Elsevier Ltd.