969 resultados para Measuring method


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We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a lab experiment consisting of a vibrating object that was recorded with a high-speed camera working at 1000 fps. We managed to track displacements with an accuracy of hundredths of pixel or even of thousandths of pixel in the case of tracking harmonic vibrations. The method is widely applicable because it can be used for distance measuring amplitude and frequency of vibrations with a vision system.

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Complementary programs

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Software for video-based multi-point frequency measuring and mapping: http://hdl.handle.net/10045/53429

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Thesis (Master's)--University of Washington, 2016-06

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Limitations have been detected in a recently published method for macroion valence determination by an ultracentrifugal procedure for quantifying the Dorman distribution of small ions in macroion solutions dialyzed against buffer supplemented with chromate as an indicator ion. The limitation reflects an implicit assumption that sedimentation velocity affords an unequivocal means of separating effects of chromate binding from those reflecting the Dorman redistribution of small ions. Although the assumed absence of significant Dorman redistribution of small ions across the sedimenting macroion boundary seemingly holds for some systems, this approximation is demonstrably invalid for others. Despite preliminary signs of promise, the ultracentrifugal procedure does not afford a simple, readily applied solution to the problem of unequivocal macroion valence determination. (C) 2004 Elsevier Inc. All rights reserved.

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We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.

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We produce and holographically measure entangled qudits encoded in transverse spatial modes of single photons. With the novel use of a quantum state tomography method that only requires two-state superpositions, we achieve the most complete characterization of entangled qutrits to date. Ideally, entangled qutrits provide better security than qubits in quantum bit commitment: we model the sensitivity of this to mixture and show experimentally and theoretically that qutrits with even a small amount of decoherence cannot offer increased security over qubits.

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The diffusion of styrene into linear low density polyethylene in a solution of supercritical CO2 was investigated using NMR microimaging. For both pure styrene and styrene dissolved in supercritical CO2, the diffusion was found to follow Fickian kinetics. Supercritical CO2 was found to enhance the rate and extent of diffusion of styrene into the substrate by up to three times under the conditions of this investigation, compared to pure styrene. NMR imaging was used to measure the concentration profiles of the styrene penetrants in real time, and the results were fitted to a Fickian model for diffusion. At a CO2 pressure of 150 bar and temperature of 40 degrees C, the diffusion coefficient of a 30 wt-% solution of styrene into LLDPE was calculated to be 1 X 10(-11) m(2). s(-1). This is significantly faster than the diffusion coefficient measured for pure styrene diffusion at 40 degrees C (3 x 10(-12) m(2). s(-1)). The diffusion coefficients determined by gravimetric analysis were slightly higher than those determined by the imaging method. This was probably due to residual styrene and/or polystyrene adhering to the surface of the films in the gravimetric technique.

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If a quantity has been measured by two different methods, the degree of agreement between them should not be tested using Pearson’s correlation coefficient ‘r’. Instead the differences between the two methods should be compared with their mean difference using a Bland and Altman plot. Such a plot illustrates the level of agreement between two methods and enables the degree of bias of one method over the other to be calculated and applied if necessary as a correction factor.

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Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using χ2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

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PURPOSE: To design and validate a vision-specific quality-of-life assessment tool to be used in a clinical setting to evaluate low-vision rehabilitation strategy and management. METHODS: Previous vision-related questionnaires were assessed by low-vision rehabilitation professionals and patients for relevance and coverage. The 74 items selected were pretested to ensure correct interpretation. One hundred and fifty patients with low vision completed the chosen questions on four occasions to allow the selection of the most appropriate items. The vision-specific quality of life of patients with low vision was compared with that of 70 age-matched and gender-matched patients with normal vision and before and after low-vision rehabilitation in 278 patients. RESULTS: Items that were unreliable, internally inconsistent, redundant, or not relevant were excluded, resulting in the 25-item Low Vision Quality-of-Life Questionnaire (LVQOL). Completion of the LVQOL results in a summed score between 0 (a low quality of life) and 125 (a high quality of life). The LVQOL has a high internal consistency (α = 0.88) and good reliability (0.72). The average LVQOL score for a population with low vision (60.9 ± 25.1) was significantly lower than the average score of those with normal vision (100.3 ± 20.8). Rehabilitation improved the LVQOL score of those with low vision by an average of 6.8 ± 15.6 (17%). CONCLUSIONS: The LVQOL was shown to be an internally consistent, reliable, and fast method for measuring the vision-specific quality of life of the visually impaired in a clinical setting. It is able to quantify the quality of life of those with low vision and is useful in determining the effects of low-vision rehabilitation. Copyright (C) 2000 Elsevier Science Inc.

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Objectives: The study of aggression and anger in competitive sport relies on accurate and economical measurement via observation, interview and questionnaire. Unfortunately, extant questionnaires have been criticised for having poor validity, are not sport specific, or reflect mood states rather than trait qualities. Therefore, a measure of trait anger and aggressiveness in competitive athletes was developed. Method: A list of statements representing aggressiveness and anger was generated and distributed to competitive athletes from diverse sports. Exploratory and confirmatory analyses were used to verify the theoretically predicted factor structure. Correlations with an extant measure of aggression and anger were used to ascertain concurrent validity. Discriminant validity was tested by comparing males with females, and aggressive with non-aggressive footballers. Results: A 12-item scale (Competitive Aggressiveness and Anger Scale, CAAS) consisting of two subscales was derived using principal component factor analysis with oblimin rotation. Confirmatory factor analysis using structural equation modelling confirmed the overall structure. Test-retest correlation, construct and discriminant validities were good, supporting the utility of the scale as a measure of athlete trait aggressiveness and anger. Conclusions: The CAAS appears to be a useful measure of athletic anger and aggressiveness. Its brevity and ability to discriminate aggressive from non-aggressive athletes should prove useful for future research concerning aggressive behaviour in competitive athletes. © 2006 Elsevier Ltd. All rights reserved.

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Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data. In this paper, we propose a semi-oriented radial measure, which permits the presence of variables which can take both negative and positive values. The model is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA: The modified slacks-based model suggested by Sharp et al. [Sharp, J.A., Liu, W.B., Meng, W., 2006. A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs. Journal of Operational Research Society 57 (11) 1–6] and the range directional model developed by Portela et al. [Portela, M.C.A.S., Thanassoulis, E., Simpson, G., 2004. A directional distance approach to deal with negative data in DEA: An application to bank branches. Journal of Operational Research Society 55 (10) 1111–1121]. A further example explores the advantages of using the new model.

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The pathological lesions characteristic of Alzheimer's disease (AD), viz., senile plaques (SP) and neurofibrillary tangles (NFT) may not be randomly distributed with reference to each other but exhibit a degree of sptial association or correlation, information on the degree of association between SP and NFT or between the lesions and normal histological features, such as neuronal perikarya and blood vessels, may be valuable in elucidating the pathogenesis of AD. This article reviews the statistical methods available for studying the degree of spatial association in histological sections of AD tissue. These include tests of interspecific association between two or more histological features using chi-square contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, analyses of association using correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

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The thesis presents new methodology and algorithms that can be used to analyse and measure the hand tremor and fatigue of surgeons while performing surgery. This will assist them in deriving useful information about their fatigue levels, and make them aware of the changes in their tool point accuracies. This thesis proposes that muscular changes of surgeons, which occur through a day of operating, can be monitored using Electromyography (EMG) signals. The multi-channel EMG signals are measured at different muscles in the upper arm of surgeons. The dependence of EMG signals has been examined to test the hypothesis that EMG signals are coupled with and dependent on each other. The results demonstrated that EMG signals collected from different channels while mimicking an operating posture are independent. Consequently, single channel fatigue analysis has been performed. In measuring hand tremor, a new method for determining the maximum tremor amplitude using Principal Component Analysis (PCA) and a new technique to detrend acceleration signals using Empirical Mode Decomposition algorithm were introduced. This tremor determination method is more representative for surgeons and it is suggested as an alternative fatigue measure. This was combined with the complexity analysis method, and applied to surgically captured data to determine if operating has an effect on a surgeon’s fatigue and tremor levels. It was found that surgical tremor and fatigue are developed throughout a day of operating and that this could be determined based solely on their initial values. Finally, several Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networks were evaluated. The results suggest that it is possible to monitor surgeon tremor variations during surgery from their EMG fatigue measurements.