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Results for “Deterministic Measurement”

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At least 145 records · Page 8Linked to original sources

PubMed2004

Medical privacy protection based on granular computing.

Based on granular computing methodology, we propose two criteria to quantitatively measure privacy invasion. The total cost criterion measures the effort needed for a data recipient to find private information. The average benefit criterion measures the benefit a data recipient obtains when he received the released data. These two criteria remedy the inadequacy of the deterministic privacy formulation proposed in Proceedings of Asia Pacific Medical Informatics Conference, 2000; Int J Med Inform 2003;71:17-23. Granular computing methodology provides a unified framework for these quantitative measurements and previous bin size and logical approaches. These two new criteria are implemented in a prototype system Cellsecu 2.0. Preliminary system performance evaluation is conducted and reviewed.

Computing Methodologies↗

PubMed1999

Quantitative measure of complexity of EEG signal dynamics.

Since electroencephalographic (EEG) signal may be considered chaotic, Nonlinear Dynamics and Deterministic Chaos Theory may supply effective quantitative descriptors of EEG dynamics and of underlying chaos in the brain. We have used Karhunen-Loeve decomposition of the covariance matrix of the EEG signal to analyse EEG signals of 4 healthy subjects, under drug-free condition and under the influence of Diazepam. We found that what we call KL-complexity of the signal differs profoundly for the signals registered in different EEG channels, from about 5-8 for signals in frontal channels up to 40 and more in occipital ones. But no consistency in the influence of Diazepam administration on KL-complexity is observed. We also estimated the embedding dimension of the EEG signals of the same subjects, which turned to be between 7 and 11, so endorsing the presumption about existence of low-dimensional chaotic attractor. We are sure that nonlinear time series analysis can be used to investigate the dynamics underlying the generation of EEG signal. This approach does not seem practical yet, but deserves further study.

Adult↗

PubMed2003

Uncertainty in toxicological risk assessment for non-carcinogenic health effects.

Uncertainty in risk assessment results from the lack of knowledge on toxicity to the target population for a substance. Currently used deterministic risk assessment methods yield human limit values or margins of safety (MOS) without quantitative measurements of uncertainty. Qualitative and quantitative uncertainty analysis would enable risk managers to better judge the consequences of different management options. This article discusses sources of uncertainty and possibilities for quantification of uncertainty associated with different steps in the risk assessment of non-carcinogenic health effects. Knowledge gaps causing uncertainty in risk assessment are overcome by extrapolation. Distribution functions for extrapolation factors are based on empirical data and provide information about the extent of uncertainty introduced by these factors. Whereas deterministic methods can account only qualitatively for uncertainty of the resulting human limit value, probabilistic risk assessment methods are able to quantify several aspects of uncertainty. However, there is only limited experience with these methods in practice. Their acceptance and future application will depend on the establishment of evidence based distribution functions, flexibility and practicability of the methods, and the unambiguity of the results.

Animals↗

PubMed2004

Growth cone pathfinding: a competition between deterministic and stochastic events.

BACKGROUND: Growth cone migratory patterns show evidence of both deterministic and stochastic search modes. RESULTS: We quantitatively examine how these two different migration modes affect the growth cone's pathfinding response, by simulating growth cone contact with a repulsive cue and measuring the resultant turn angle. We develop a dimensionless number, we call the determinism ratio Psi, to define the ratio of deterministic to stochastic influences driving the growth cone's migration in response to an external guidance cue. We find that the growth cone can exhibit three distinct types of turning behaviors depending on the magnitude of Psi. CONCLUSIONS: We conclude, within the context of these in silico studies, that only when deterministic and stochastic migration factors are in balance (i.e. Psi ~ 1) can the growth cone respond constructively to guidance cues.

Algorithms↗

PubMed2005

Pediatric patient surface doses in neuroangiography.

BACKGROUND: Neuroangiographic techniques (diagnostic and interventional) can be lengthy and complex and can be associated with high radiation entrance skin doses from fluoroscopy and digital subtraction angiography (DSA). OBJECTIVE: To measure entrance surface doses received by pediatric patients undergoing neuroangiographic procedures and to (1) compare these doses with thresholds for deterministic effects, (2) compare these doses with those reported in adults, and (3) to understand the dose relationships among diagnostic and interventional procedures, DSA and fluoroscopy. MATERIALS AND METHODS: A neurobiplane unit with fluoroscopic and DSA capabilities was used for all neuroangiographic procedures. An automated patient dosimeter, installed on both planes of the unit, calculated maximum surface dose. The dosimeter also recorded the number of angiographic frames and the length of fluoroscopy time for each procedure. RESULTS: This retrospective study analyzed entrance surface doses to 100 pediatric patients, 76 of whom underwent neuroangiographic diagnostic procedures and 24 of whom underwent neuroangiographic interventional procedures. The DSA acquisitions ranged from 44 frames to 1,428 frames per procedure and fluoroscopy times ranged from 1.1 to 85.6 min per procedure. The mean surface dose from fluoroscopy was 68.1 mGy (max: 397.1 mGy) in the frontal (PA) plane; in the lateral (LAT) plane, the mean surface dose was 40.9 mGy (max: 418.5 mGy). The mean surface doses from DSA were 263.1 and 126.9 mGy in the frontal and lateral planes, with maximum doses of 924.4 and 410.1 mGy, respectively. Mean fluoroscopy dose rates were 5.4 mGy/min in the PA plane and 4.7 mGy/min in the LAT plane. The DSA largely contributed to the overall procedural surface dose, accounting for 82% of the combined surface dose in the each of the imaging planes. CONCLUSION: The surface dose for each procedure measured in this study was found to be below thresholds for deterministic effects. Interventional procedures consistently yield the highest doses.

Adolescent↗

PubMed1997

Detection of chaotic determinism in time series from randomly forced maps.

Time series from biological system often display fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". Despite this effort, it has been difficult to establish the presence of chaos in time series from biological sytems. The output from a biological system is probably the result of both its internal dynamics, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes, i.e., a positive characteristic exponent that leads to sensitivity to initial conditions. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Algorithms↗

PubMed2000

Specificity of postural sway to the demands of a precision task.

We examined a precision aiming task in which a handheld laser pointer was controlled by the postural system. The task was performed in two orientations of the body's coronal plane to the target. In the parallel orientation medio-lateral (ML) sway had to be minimized, in the perpendicular orientation antero-posterior (AP) sway had to be minimized. In the parallel orientation ML sway decreased and AP sway increased with target distance and size. The pattern reversed in the perpendicular orientation. Nonlinear measures found independence of the two directions of sway and differences in their deterministic structure. Apparently a postural organization for upright standing and aiming (as in archery) entails two independent postural subsystems with different but reciprocally related dynamics. Furthermore, it seems as if some amount of postural variability is needed to ensure stability in quiet standing; if postural activity is reduced in one direction it is compensated for in the other direction.

Adult↗

PubMed2000

Single photons on demand from a single molecule at room temperature.

The generation of non-classical states of light is of fundamental scientific and technological interest. For example, 'squeezed' states enable measurements to be performed at lower noise levels than possible using classical light. Deterministic (or triggered) single-photon sources exhibit non-classical behaviour in that they emit, with a high degree of certainty, just one photon at a user-specified time. (In contrast, a classical source such as an attenuated pulsed laser emits photons according to Poisson statistics.) A deterministic source of single photons could find applications in quantum information processing, quantum cryptography and certain quantum computation problems. Here we realize a controllable source of single photons using optical pumping of a single molecule in a solid. Triggered single photons are produced at a high rate, whereas the probability of simultaneous emission of two photons is nearly zero--a useful property for secure quantum cryptography. Our approach is characterized by simplicity, room temperature operation and improved performance compared to other triggered sources of single photons.

Journal Article↗

PubMed2006

Deterministic single photons via conditional quantum evolution.

A source of deterministic single photons is proposed and demonstrated by the application of a measurement-based feedback protocol to a heralded single-photon source consisting of an ensemble of cold rubidium atoms. Our source is stationary and produces a photoelectric detection record with sub-Poissonian statistics.

Journal Article↗

PubMed2002

Prospects for quantitative computed tomography imaging in the presence of foreign metal bodies using statistical image reconstruction.

X-ray computed tomography (CT) images of patients bearing metal intracavitary applicators or other metal foreign objects exhibit severe artifacts including streaks and aliasing. We have systematically evaluated via computer simulations the impact of scattered radiation, the polyenergetic spectrum, and measurement noise on the performance of three reconstruction algorithms: conventional filtered backprojection (FBP), deterministic iterative deblurring, and a new iterative algorithm, alternating minimization (AM), based on a CT detector model that includes noise, scatter, and polyenergetic spectra. Contrary to the dominant view of the literature, FBP streaking artifacts are due mostly to mismatches between FBP's simplified model of CT detector response and the physical process of signal acquisition. Artifacts on AM images are significantly mitigated as this algorithm substantially reduces detector-model mismatches. However, metal artifacts are reduced to acceptable levels only when prior knowledge of the metal object in the patient, including its pose, shape, and attenuation map, are used to constrain AM's iterations. AM image reconstruction, in combination with object-constrained CT to estimate the pose of metal objects in the patient, is a promising approach for effectively mitigating metal artifacts and making quantitative estimation of tissue attenuation coefficients a clinical possibility.

Algorithms↗

PubMed1997

Detection of "noisy" chaos in a time series.

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Algorithms↗

PubMed1998

Modeling the normal and neoplastic cell cycle with "realistic Boolean genetic networks": their application for understanding carcinogenesis and assessing therapeutic strategies.

In this paper we show how Boolean genetic networks could be used to address complex problems in cancer biology. First, we describe a general strategy to generate Boolean genetic networks that incorporate all relevant biochemical and physiological parameters and cover all of their regulatory interactions in a deterministic manner. Second, we introduce "realistic Boolean genetic networks" that produce time series measurements very similar to those detected in actual biological systems. Third, we outline a series of essential questions related to cancer biology and cancer therapy that could be addressed by the use of "realistic Boolean genetic network" modeling.

Cell Cycle↗

PubMedDate not supplied

[Principles and experiences for modeling chaotic attractors of heart rate fluctuations with artificial neural networks].

The aim of the present paper was, using artificial neural networks, to identify chaotic attractors presumed to be responsible for heart rate fluctuations. Chaotic behaviour is based on low-dimensional deterministic processes which are highly sensitive to initial conditions and therefore of limited predictability. Chaotic attractors produce orbits in the phase space where the points are dense. Following transformation of measured heart rate date into the phase space, such heart rate prediction characteristics were found in 6 adult rabbits. A low-dimensional deterministic model was designed by means of an artificial neural network [2*dimension of the time series +1) input neurons, 1 hidden layer, 1 output neuron and was successfully employed to predict the next 5 heart beats. Training of the neural network in terms of the prediction of the suspected chaotic orbits was dramatically improved by considering all possible prediction intervals within the prediction horizon. The trained models enabled the heart rate fluctuations to be distinguished during consciousness, under anaesthesia and additional vagal blockade.

Animals↗

PubMed2006

Combining deterministic and Monte Carlo calculations for fast estimation of scatter intensities in CT.

A side effect of increased volume coverage by using multi-row and flat-panel detectors in computed tomography (CT) is the concurrently growing contribution of scattered radiation to the measured signal. In order to investigate the effect of scatter on x-ray projections used for CT imaging, our study aimed at the development of a simulation tool for fast calculation of primary and scatter intensities. We developed a deterministic method to assess the contribution of single-scatter events to the measured signal. The investigation of multiple scatter by Monte Carlo simulations showed that it results in a smooth signal as compared to single scatter. A hybrid method is proposed in order to optimize the performance of the scatter simulation: a fast and exact analytical calculation of the single-scatter intensity combined with a coarse Monte Carlo (MC) estimate of multiple scatter to reduce overall computational expenses, while assuring an acceptable signal quality. The results of the hybrid simulation of total scatter were in excellent agreement with the corresponding MC only simulations, thereby allowing us to reduce computational time by orders of magnitude. Estimates of two-dimensional scatter distributions for flat-panel CT imaging took about 30-40 s (per projection). The hybrid method provides a realistic simulation of x-ray scatter and offers a basis for scatter correction approaches.

Algorithms↗

PubMed1979

Complexity transmission during replication.

The transmission of complexity during DNA replication has been investigated to clarify the significance of this molecular property in a deterministic process. Complexity was equated with the amount of randomness within an ordered molecular structure and measured by the entropy of a posteriori probabilities for discrete (monomer sequences, atomic bonds) and continuous (torsion angle sequences) structural parameters in polynucleotides, proteins, and ligand molecules. A theoretical analysis revealed that sequence complexity decreases during transmission from DNA to protein. It was also found that sequence complexity limits the attainable complexity in the folding of a polypeptide chain and that a protein cannot interact with a ligand moiety of higher complexity. The analysis indicated, furthermore, that in any deterministic molecular process a cause possesses more complexity than its effect. This outcome broadly complies with Curie's symmetry principle. Results from an analysis of an extensive set of experimental data are presented; they corroborate these findings. It is suggested, therefore, that complexity governs the direction of order-order molecular transformations. Two biological implications are (i) replication of DNA in a stepwise, repetitive manner by a polymerase appears to be a necessary consequence of structural constraints imposed by complexity, and (ii) during evolution, increases in complexity had to involve a nondeterministic mechanism. This latter requirement apparently applied also to development of the first replicating system on earth.

Base Sequence↗

PubMedDate not supplied

An evaluation of conditioning data for solute transport prediction.

The large and diverse body of subsurface characterization data generated at a field research site near Oyster, Virginia, provides a unique opportunity to test the impact of conditioning data of various types on predictions of flow and transport. Bromide breakthrough curves (BTCs) were measured during a forced-gradient local-scale injection experiment conducted in 1999. Observed BTCs are available at 140 sampling points in a three-dimensional array within the transport domain. A detailed three-dimensional numerical model is used to simulate breakthrough curves at the same locations as the observed BTCs under varying assumptions regarding the character of hydraulic conductivity spatial distributions, and variable amounts and types of conditioning data. We present comparative results of six cases ranging from simple (deterministic homogeneous models) to complex (stochastic indicator simulation conditioned to cross-borehole geophysical observations). Quantitative measures of model goodness-of-fit are presented. The results show that conditioning to a large number of small-scale measurements does not significantly improve model predictions, and may lead to biased or overly confident predictions. However, conditioning to geophysical interpretations with larger spatial support significantly improves the accuracy and precision of model predictions. In all cases, the effects of model error appear to be significant in relation to parameter uncertainty.

Forecasting↗

PubMed2006

Simulated maximum likelihood method for estimating kinetic rates in gene expression.

MOTIVATION: Kinetic rate in gene expression is a key measurement of the stability of gene products and gives important information for the reconstruction of genetic regulatory networks. Recent developments in experimental technologies have made it possible to measure the numbers of transcripts and protein molecules in single cells. Although estimation methods based on deterministic models have been proposed aimed at evaluating kinetic rates from experimental observations, these methods cannot tackle noise in gene expression that may arise from discrete processes of gene expression, small numbers of mRNA transcript, fluctuations in the activity of transcriptional factors and variability in the experimental environment. RESULTS: In this paper, we develop effective methods for estimating kinetic rates in genetic regulatory networks. The simulated maximum likelihood method is used to evaluate parameters in stochastic models described by either stochastic differential equations or discrete biochemical reactions. Different types of non-parametric density functions are used to measure the transitional probability of experimental observations. For stochastic models described by biochemical reactions, we propose to use the simulated frequency distribution to evaluate the transitional density based on the discrete nature of stochastic simulations. The genetic optimization algorithm is used as an efficient tool to search for optimal reaction rates. Numerical results indicate that the proposed methods can give robust estimations of kinetic rates with good accuracy.

Algorithms↗

PubMed2004

Establishing mathematical laws of genomic variation.

As the biological arm of the Rasch community, genomic measurement is concerned with asserting and testing hypotheses regarding the quantitative status of genomic variables, including alleles, genotypes, gene expression levels, and phenotypes, as well as DNA, RNA, and protein sequence information. The defining goal of this scientific paradigm, in contrast to the sample-dependent model-fitting and deterministic hypothesis testing of classical statistical genetics, is the identification, validation, and maintenance of a common unit of genomic measurement that maintains its magnitude and meaning, within an allowable range of error, regardless of the laboratory technology used to generate outcomes or the particular group of individuals or organisms under investigation. Such an invariant metric, the basis of a standard genometric scale and associated system of genomic metrology, can be identified, validated, and maintained through 1) routine implementation of the Rasch family of measurement models to construct sample- and scale-free measures from different types of genomic data and 2) cross-calibration of genomic measurement instruments between and among researchers, laboratories, universities, corporations, and databases. This manuscript provides an introductory overview of the guiding principles of fundamental measurement theory and the work of Rasch, connects these concepts to well-known tenets of population genetics, and highlights the potential benefits, both theoretical and applied, associated with achieving objectivity in genomic measurement.

Animals↗