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Results for “Deterministic Measurement”

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At least 433 records · Page 24Linked to original sources
PubMed1994

Omega-dimension of chaotic time series.

New characteristics, Omega-dimension (D(Omega)) and spectral density of dimension (D'(Omega)), of deterministically generated irregular signals are proposed. They are the functions that are calculated employing spectral transformation such as filtering with limit transmission frequency Omega. The Omega-dimension of the time series generated by a dynamical system with a homogeneous strange attractor does not depend on Omega and coincides with the dimension measured using a standard technique. If the time series does not possess the similarity property as the time scale changes (i.e., it is multiscaled in time), the calculation of D(Omega) gives additional information on the properties of the signal. In particular, it allows for the estimation of additional degrees of freedom in the time series on signal transmission through the communication channel and preliminary processing.

Journal Article↗
PubMed2003

Uncertainty in the output of artificial neural networks.

Analysis of the performance of artificial neural networks (ANNs) is usually based on aggregate results on a population of cases. In this paper, we analyze ANN output corresponding to the individual case. We show variability in the outputs of multiple ANNs that are trained and "optimized" from a common set of training cases. We predict this variability from a theoretical standpoint on the basis that multiple ANNs can be optimized to achieve similar overall performance on a population of cases, but produce different outputs for the same individual case because the ANNs use different weights. We use simulations to show that the average standard deviation in the ANN output can be two orders of magnitude higher than the standard deviation in the ANN overall performance measured by the Az value. We further show this variability using an example in mammography where the ANNs are used to classify clustered microcalcifications as malignant or benign based on image features extracted from mammograms. This variability in the ANN output is generally not recognized because a trained individual ANN becomes a deterministic model. Recognition of this variability and the deterministic view of the ANN present a fundamental contradiction. The implication of this variability to the classification task warrants additional study.

Algorithms↗
PubMed1999

Experimental studies of extinction dynamics

Extinction of populations occurs naturally, but global extinction rates are accelerating, making understanding extinction a high priority for conservation. Extinction in experimental populations of brine shrimp (Artemia franciscana) was measured to assess hypothesized extinction processes. Greater initial population size, greater maximum population size supported by the environment, and lower variation in environmental conditions reduced the likelihood of extinction, as hypothesized. However, initial population size was less important, and maximum population size and environmental variation were more important than often hypothesized. Unexpectedly, deterministic oscillations in population size due to inherent nonlinear dynamics and overcrowding were as important or more important than hypothesized processes.

Journal Article↗
PubMed1993

Nonlinear predictive interpolation. A new method for the correction of ectopic beats for heart rate variability analysis.

Heart rate variability (HRV) analysis is a technique that uses the beat-to-beat variations in RR intervals as a measure of the level of activity of the autonomic nervous system. However, the presence of ectopic beats can alter measures of HRV by introducing mathematical artifact and thus, prevent accurate determinations of HRV. Simple exclusion of those portions of data that contain ectopy from analysis inappropriate because (1) it can lead to a substantial reduction in the amount of data available for analysis and (2) if the presence (and frequency) of ectopic beats is correlated with specific alterations in autonomic tone, then the utilization of only ectopy-free data for analysis will lead to bias in the measures. For this reason, methods for the correction of ectopic beats have been devised and applied in the determination of HRV. The authors therefore propose a new method for the correction of ectopic beats: nonlinear predictive interpolation. Using the fact that beat-to-beat changes in heart rate occur in a deterministic fashion as the only assumption, the authors apply the methods of chaos theory in order to locate ectopy-free portions of the RR interval sequence that describe trajectories in phase space that are locally similar to that of the ectopy-containing segments. The authors then determine which of these trajectories most closely approximates that of a particular ectopy-containing segment, and use it to determine replacement RR intervals for the ectopic beats.

Arrhythmias, Cardiac↗
PubMed2005

Potential public health impact of imperfect HIV type 1 vaccines.

The potential public health impact of imperfect human immunodeficiency virus (HIV) type 1 vaccines was examined by use of deterministic mathematical models of virus transmission. Imperfect vaccines are defined as those that act to favorably alter the typical clinical course of disease in those immunized who acquire infection. The properties examined include a lengthened incubation period; reduced virus load, which acts to lower infectiousness; reduced susceptibility on exposure to infection; and an increase in risk behaviors by those vaccinated. Analyses suggest that, although imperfect vaccines would struggle to block transmission via cohort vaccination of those entering the sexually active age classes, they could have a substantial public health impact, as measured by reduced prevalence and mortality induced by acquired immunodeficiency syndrome (AIDS), provided the case reproductive number of HIV-1 among vaccinated individuals (R(0v)) was less than that among unvaccinated individuals (R(0)). This requires that any lengthening in the incubation period and, hence, the time period over which an infected vaccine recipient can transmit to susceptible sex partners, as well as any increase in risk behaviors, are more than offset by other effects, such as reduced susceptibility to infection and reduced infectiousness. Numerical studies based on a more complex model, which included representation of age, sex, heterogeneity in sexual activity, variable infectiousness, and different mixing patterns between risk groups, were used to confirm the general insights gained from a simple deterministic model.

AIDS Vaccines↗
PubMed1995

Approximate entropy (ApEn) as a complexity measure.

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity, which appears to have potential application to a wide variety of relatively short (greater than 100 points) and noisy time-series data. The development of ApEn was motivated by data length constraints commonly encountered, e.g., in heart rate, EEG, and endocrine hormone secretion data sets. We describe ApEn implementation and interpretation, indicating its utility to distinguish correlated stochastic processes, and composite deterministic/ stochastic models. We discuss the key technical idea that motivates ApEn, that one need not fully reconstruct an attractor to discriminate in a statistically valid manner-marginal probability distributions often suffice for this purpose. Finally, we discuss why algorithms to compute, e.g., correlation dimension and the Kolmogorov-Sinai (KS) entropy, often work well for true dynamical systems, yet sometimes operationally confound for general models, with the aid of visual representations of reconstructed dynamics for two contrasting processes. (c) 1995 American Institute of Physics.

Journal Article↗
PubMed1996

Dynamic complexity of visuo-motor coordination: an extension of Bernstein's conception of the degrees-of-freedom problem.

Extending Bernstein's spatial conception of the degrees-of-freedom problem in the human motor system, we introduce a method developed from the theory of non-linear dynamics that allows one to quantify the spatio-temporal, i.e. dynamic, complexity of visuo-motor coordination. The correlation dimension D is used to measure the effective number of dynamic degrees of freedom in the coordination that a subject uses when performing a visuo-motor tracking task. The validity of the estimator employed is demonstrated. Visuo-motor coordination had a low-dimensional (mean D-SD=6.07 -0.82) dynamic structure, which was consistent with deterministic chaos rather than with pure stochastic noise. D correlated with tracking performance, P. Both D and P were closely related to the degree of visuo-motor compatibility that the task presented to the subject. However, for short periods of training P increased, but D did not. As these seemingly contradictory results suggest, our dynamic conception of the degrees-of-freedom problem may reveal far more intricate visuo-motor interactions than Bernstein could identify on the basis of his spatial analyses of bodily movement patterns and by the methods of evaluation that were available to him at the time.

Adult↗
PubMedDate not supplied

In silico prediction of buffer solubility based on quantum-mechanical and HQSAR- and topology-based descriptors.

We present an artificial neural network (ANN) model for the prediction of solubility of organic compounds in buffer at pH 6.5, thus mimicking the medium in the human gastrointestinal tract. The model was derived from consistently performed solubility measurements of about 5000 compounds. Semiempirical VAMP/AM1 quantum-chemical wave function derived, HQSAR-derived logP, and topology-based descriptors were employed after preselection of significant contributors by statistical and data mining approaches. Ten ANNs were trained each with 90% as a training set and 10% as a test set, and deterministic analysis of prediction quality was used in an iterative manner to optimize ANN architecture and descriptor space, based on Corina 3D molecular structure and AM1/COSMO single point wave function. In production mode, a mean prediction value of the 10 ANNs is created, as is a standard deviation based quality parameter. The productive ANN based on Corina geometries and AM1/COSMO wave function gives an r2cv of 0.50 and a root-mean-square error of 0.71 log units, with 87 and 96% of the compounds having an error of less than 1 and 1.5 log units, respectively. The model is able to predict permanently charged species, e.g. zwitterions or quaternary amines, and problematic structures such as tautomers and unresolved diastereomers almost as well as neutral compounds.

Buffers↗
PubMed2000

Scaling structure of electrocardiographic waveform during prolonged ventricular fibrillation in swine.

Ventricular fibrillation (VF) is the most common arrhythmia causing sudden cardiac death. However, the likelihood of successful defibrillation declines with increasing duration of VF. Because the morphology of the electrocardiogram (ECG) waveform during VF also changes with time, this study examined a new measure that describes the VF waveform and distinguishes between early and late VF. Surface ECG recordings were digitized at 200 samples/s from nine swine with induced VF. A new measure called the scaling exponent was calculated by examining the power-law relationship between the summation of amplitudes of a 1,024-point (5.12 second) waveform segment and the time scale of measurement. The scaling exponent is a local estimate of the fractal dimension of the ECG waveform. A consistent power-law relationship was observed for measurement time scales of 0.005-0.040 seconds. Calculation of the scaling exponent produced similar results between subjects, and distinguished early VF (< 4-minute duration) from late VF (> or = 4-minute duration). The scaling exponent was dependent on the order of the data, supporting the hypothesis that the surface ECG during VF is a deterministic rather than a random signal. The waveform of VF results from the interaction of multiple fronts of depolarization within the heart, and may be described using the tools of nonlinear dynamics. As a quantitative descriptor of waveform structure, the scaling exponent characterizes the time dependent organization of VF.

Animals↗
PubMed2000

An iterative approach to the beam hardening correction in cone beam CT.

In computed tomography (CT), the beam hardening effect has been known to be one of the major sources of deterministic error that leads to inaccuracy and artifact in the reconstructed images. Because of the polychromatic nature of the x-ray source used in CT and the energy-dependent attenuation of most materials, Beer's law no longer holds. As a result, errors are present in the acquired line integrals or measurements of the attenuation coefficients of the scanned object. In the past, many studies have been conducted to combat image artifacts induced by beam hardening. In this paper, we present an iterative beam hardening correction approach for cone beam CT. An algorithm that utilizes a tilted parallel beam geometry is developed and subsequently employed to estimate the projection error and obtain an error estimation image, which is then subtracted from the initial reconstruction. A theoretical analysis is performed to investigate the accuracy of our methods. Phantom and animal experiments are conducted to demonstrate the effectiveness of our approach.

Algorithms↗
PubMedDate not supplied

[Occupational accidents at an Acute Care Hospital].

BACKGROUND: To obtain a better knowledge of the determining factors and circumstances giving rise to occupational accidents will foster the implementation of corrective measures. The aim of this study is that of describing the trend of occupational accidents (OA's) over the course of time and of determining the risk factors regarding workers being forced to take time off for sick leave at the "Dr. Peset" Hospital in Valencia. METHODS: Description and retrospective analysis of the occupational accidents having occurred at the "Dr. Peset" Hospital in Valencia throughout the 1992-1995 period. The trend and seasonality of the series (seasonal indexes, SI's) were estimated by deterministic methods. A logistic regression model was employed to identify the factors providing a prior indication workers being off on sick leave and to determine the probability of the occurrence thereof. RESULTS: The highest OA rates were found among the kitchen and laundry workers (10.00 OA's per 100 workers/year). The OA's involving sick leave continued to show a trend of around zero, February being the months showing the highest SI (SI = 139.8). Those processed without sick leave showed an upward trend (r2 = 0.23, p < 0.0001), May being the month involving the largest number of casualties (SI = 134.2). The probability of an accident resulting in a worker being forced to take time of for sick leave increases significantly with age, when the accident in question takes place in the afternoon/evening, if it takes place in the kitchen/laundry, and if a sprain or tendinitis is involved. CONCLUSIONS: The measures taken involving the number of casualties entailing OA's which result in temporary incapacity should revolve around the less-skilled positions and the kitchen and laundry departments.

Accidents, Occupational↗
PubMed2000

RESEARCH: Projected Climate Change Effects on Winterkill in Shallow Lakes in the Northern United States.

/ Each winter, hundreds of ice-covered, shallow lakes in the northern United States are aerated to prevent winterkill, the death of fish due to oxygen depletion under the ice. How will the projected climate warming influence winterkill and the need to artificially aerate lakes? To answer this question, a deterministic, one-dimensional year-round water quality model, which simulates daily dissolved oxygen (DO) profiles and associated water temperatures as well as ice/snow covers on lakes, was applied. Past and projected climate scenarios were investigated. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous United States for the period 1961-1979 were used to represent past climate conditions. The projected climate change due to a doubling of atmospheric CO(2) was obtained from the output of the Canadian Climate Center General Circulation Model. To illustrate the effect of projected climate change on lake DO characteristics, we present herein DO information simulated, respectively, with inputs of past climate conditions (1961-1979) and with a projected 2 x CO(2) climate scenario, as well as differences of those values. Specific parameters obtained were minimum under-ice and lake bottom DO concentration in winter, duration of under-ice anoxic conditions (<0.1 mg/liter) and low DO conditions (<3 mg/liter), and percentage of anoxic and low DO lake volumes during the ice cover period. Under current climate conditions winterkill occurs typically in shallow eutrophic lakes of the northern contiguous United States. Climate warming is projected to eliminate winterkill in these lakes. This would be a positive effect of climate warming. Fish species under ice may still experience periods of stress and zero growth due to low DO (<3 mg/liter) conditions under projected climate warming.

Journal Article↗
PubMedDate not supplied

Spatial regression models for large-cohort studies linking community air pollution and health.

Cohort study designs are often used to assess the association between community-based ambient air pollution concentrations and health outcomes, such as mortality, development and prevalence of disease, and pulmonary function. Typically, a large number of subjects are enrolled in the study in each of a small number of communities. Fixed-site monitors are used to determine long-term exposure to ambient pollution. The association between community average pollution levels and health is determined after controlling for risk factors of the health outcome measured at the individual level (i.e., smoking). We present a new spatial regression model linking spatial variation in ambient air pollution to health. Health outcomes can be measured as continuous variables (pulmonary function), binary variables (prevalence of disease), or time-to-event data (survival or development of disease). The model incorporates risk factors measured at the individual level, such as smoking, and at the community level, such as air pollution. We demonstrate that the spatial autocorrelation in community health outcomes, an indication of not fully characterizing potentially confounding risk factors to the air pollution--health association, can be accounted for through the inclusion of location in the deterministic component of the model assessing the effects of air pollution on health or through a distance-decay spatial autocorrelation function in the stochastic component of the model, or both. We present a statistical approach that can be implemented for very large cohort studies. Our methods are illustrated with an analysis of the American Cancer Society cohort to determine whether the prevalence of heart disease is associated with concentrations of sulfate particles. From a statistical point of view, it appears that a location surface in the deterministic component of the model was preferred to a distance-decay autocorrelation structure in the model's stochastic component.

Air Pollution↗
PubMedDate not supplied

Random drug excess.

If a patient is treated in a hospital, drugs are administered at 'deterministic', known times. However, if the patient is not supervised the times of drug intake may be less 'deterministic' and less well known. It seems therefore worthwhile to make a theoretical experiment in which one assumes that drugs are applied according to a random process. In the present article it is proposed that shot noise models could be used to represent concentration curves in such situations. By means of Monte Carlo methods different measures of random drug excess are described. An included program may encourage readers to consider these methods and to perform computer experiments.

Drug Administration Schedule↗
PubMed1987

A model for the spatio-temporal organization of DNA replication in mammalian cells.

The spatio-temporal organization of chromosomal DNA replication was analyzed using a model based on a "DNA unit" (or decondensation unit) hypothesis. The model is an extension of the fork movement theory of Huberman & Riggs (1968) and can account for a partially deterministic and partially stochastic order of DNA replication in chromosomes. It presumes that each chromosome is composed of DNA units that are arranged in sequence and that are replicated in parallel. A deterministic wave of chromatin decondensation propagates along the DNA unit continuously and progressively providing a field for the random activation of replication origin. Assignment of replication times to DNA compartments by a Monte Carlo method was programmed based on the model and the program was used to stimulate DNA synthesis rate curves that can be measured by the method of Dolbeare et al. (1983, 1985). The shape of the curve is shown to constrain possible parameter values of the model, which include the rate of fork movement, the fraction of chromatin that is decondensed at the start of S-phase, the initial number of origins activated, the rate at which new origins are activated, etc. The chromosomal organization that controls the molecular level of DNA replication is briefly reviewed and its relevance to the model is also discussed.

Algorithms↗
PubMed2005

Measurement of Hurst exponents for semiconductor laser phase dynamics.

The phase dynamics of a semiconductor laser with optical feedback is studied by construction of the Hilbert phase from its experimentally measured intensity time series. The Hurst exponent is evaluated for the phase fluctuations and grows from 0.5 to approximately 0.7 (indicating fractional Brownian motion) as the feedback strength is increased. A comparison with numerical computations based on a delay-differential equation model shows excellent agreement and reveals the relative roles of spontaneous emission noise and deterministic dynamics for different feedback strengths.

Journal Article↗
PubMed2006

Effects of geometric head model perturbations on the EEG forward and inverse problems.

We study the effect of geometric head model perturbations on the electroencephalography (EEG) forward and inverse problems. Small magnitude perturbations of the shape of the head could represent uncertainties in the head model due to errors on images or techniques used to construct the model. They could also represent small scale details of the shape of the surfaces not described in a deterministic model, such as the sulci and fissures of the cortical layer. We perform a first-order perturbation analysis, using a meshless method for computing the sensitivity of the solution of the forward problem to the geometry of the head model. The effect on the forward problem solution is treated as noise in the EEG measurements and the Cramér-Rao bound is computed to quantify the effect on the inverse problem performance. Our results show that, for a dipolar source, the effect of the perturbations on the inverse problem performance is under the level of the uncertainties due to the spontaneous brain activity. Thus, the results suggest that an extremely detailed model of the head may be unnecessary when solving the EEG inverse problem.

Brain↗