Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Positive-negative corresponding normalized ghost imaging based on an adaptive threshold

NASA Astrophysics Data System (ADS)

Li, G. L.; Zhao, Y.; Yang, Z. H.; Liu, X.

2016-11-01

Ghost imaging (GI) technology has attracted increasing attention as a new imaging technique in recent years. However, the signal-to-noise ratio (SNR) of GI with pseudo-thermal light needs to be improved before it meets engineering application demands. We therefore propose a new scheme called positive-negative correspondence normalized GI based on an adaptive threshold (PCNGI-AT) to achieve a good performance with less amount of data. In this work, we use both the advantages of normalized GI (NGI) and positive-negative correspondence GI (P-NCGI). The correctness and feasibility of the scheme were proved in theory before we designed an adaptive threshold selection method, in which the parameter of object signal selection conditions is replaced by the normalizing value. The simulation and experimental results reveal that the SNR of the proposed scheme is better than that of time-correspondence differential GI (TCDGI), avoiding the calculation of the matrix of correlation and reducing the amount of data used. The method proposed will make GI far more practical in engineering applications.

Unipolar Terminal-Attractor Based Neural Associative Memory with Adaptive Threshold

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Barhen, Jacob (Inventor); Farhat, Nabil H. (Inventor); Wu, Chwan-Hwa (Inventor)

1996-01-01

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner-product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Unipolar terminal-attractor based neural associative memory with adaptive threshold

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Barhen, Jacob (Inventor); Farhat, Nabil H. (Inventor); Wu, Chwan-Hwa (Inventor)

1993-01-01

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Synergy of adaptive thresholds and multiple transmitters in free-space optical communication.

PubMed

Louthain, James A; Schmidt, Jason D

2010-04-26

Laser propagation through extended turbulence causes severe beam spread and scintillation. Airborne laser communication systems require special considerations in size, complexity, power, and weight. Rather than using bulky, costly, adaptive optics systems, we reduce the variability of the received signal by integrating a two-transmitter system with an adaptive threshold receiver to average out the deleterious effects of turbulence. In contrast to adaptive optics approaches, systems employing multiple transmitters and adaptive thresholds exhibit performance improvements that are unaffected by turbulence strength. Simulations of this system with on-off-keying (OOK) showed that reducing the scintillation variations with multiple transmitters improves the performance of low-frequency adaptive threshold estimators by 1-3 dB. The combination of multiple transmitters and adaptive thresholding provided at least a 10 dB gain over implementing only transmitter pointing and receiver tilt correction for all three high-Rytov number scenarios. The scenario with a spherical-wave Rytov number R=0.20 enjoyed a 13 dB reduction in the required SNR for BER's between 10(-5) to 10(-3), consistent with the code gain metric. All five scenarios between 0.06 and 0.20 Rytov number improved to within 3 dB of the SNR of the lowest Rytov number scenario.

Graded-threshold parametric response maps: towards a strategy for adaptive dose painting

NASA Astrophysics Data System (ADS)

Lausch, A.; Jensen, N.; Chen, J.; Lee, T. Y.; Lock, M.; Wong, E.

2014-03-01

Purpose: To modify the single-threshold parametric response map (ST-PRM) method for predicting treatment outcomes in order to facilitate its use for guidance of adaptive dose painting in intensity-modulated radiotherapy. Methods: Multiple graded thresholds were used to extend the ST-PRM method (Nat. Med. 2009;15(5):572-576) such that the full functional change distribution within tumours could be represented with respect to multiple confidence interval estimates for functional changes in similar healthy tissue. The ST-PRM and graded-threshold PRM (GT-PRM) methods were applied to functional imaging scans of 5 patients treated for hepatocellular carcinoma. Pre and post-radiotherapy arterial blood flow maps (ABF) were generated from CT-perfusion scans of each patient. ABF maps were rigidly registered based on aligning tumour centres of mass. ST-PRM and GT-PRM analyses were then performed on overlapping tumour regions within the registered ABF maps. Main findings: The ST-PRMs contained many disconnected clusters of voxels classified as having a significant change in function. While this may be useful to predict treatment response, it may pose challenges for identifying boost volumes or for informing dose-painting by numbers strategies. The GT-PRMs included all of the same information as ST-PRMs but also visualized the full tumour functional change distribution. Heterogeneous clusters in the ST-PRMs often became more connected in the GT-PRMs by voxels with similar functional changes. Conclusions: GT-PRMs provided additional information which helped to visualize relationships between significant functional changes identified by ST-PRMs. This may enhance ST-PRM utility for guiding adaptive dose painting.

Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring

NASA Astrophysics Data System (ADS)

Zhang, Shiqi; Hui, Mei; Liu, Ming; Zhao, Zhu; Dong, Liquan; Liu, Xiaohua; Zhao, Yuejin

2015-08-01

In the research of optical synthetic aperture imaging system, phase congruency is the main problem and it is necessary to detect sub-aperture phase. The edge of the sub-aperture system is more complex than that in the traditional optical imaging system. And with the existence of steep slope for large-aperture optical component, interference fringe may be quite dense when interference imaging. Deep phase gradient may cause a loss of phase information. Therefore, it's urgent to search for an efficient edge detection method. Wavelet analysis as a powerful tool is widely used in the fields of image processing. Based on its properties of multi-scale transform, edge region is detected with high precision in small scale. Longing with the increase of scale, noise is reduced in contrary. So it has a certain suppression effect on noise. Otherwise, adaptive threshold method which sets different thresholds in various regions can detect edge points from noise. Firstly, fringe pattern is obtained and cubic b-spline wavelet is adopted as the smoothing function. After the multi-scale wavelet decomposition of the whole image, we figure out the local modulus maxima in gradient directions. However, it also contains noise, and thus adaptive threshold method is used to select the modulus maxima. The point which greater than threshold value is boundary point. Finally, we use corrosion and expansion deal with the resulting image to get the consecutive boundary of image.

Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

NASA Astrophysics Data System (ADS)

Li, Liangliang; Si, Yujuan; Jia, Zhenhong

2018-03-01

In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric.

QUEST+: A general multidimensional Bayesian adaptive psychometric method.

PubMed

Watson, Andrew B

2017-03-01

QUEST+ is a Bayesian adaptive psychometric testing method that allows an arbitrary number of stimulus dimensions, psychometric function parameters, and trial outcomes. It is a generalization and extension of the original QUEST procedure and incorporates many subsequent developments in the area of parametric adaptive testing. With a single procedure, it is possible to implement a wide variety of experimental designs, including conventional threshold measurement; measurement of psychometric function parameters, such as slope and lapse; estimation of the contrast sensitivity function; measurement of increment threshold functions; measurement of noise-masking functions; Thurstone scale estimation using pair comparisons; and categorical ratings on linear and circular stimulus dimensions. QUEST+ provides a general method to accelerate data collection in many areas of cognitive and perceptual science.

An adaptive design for updating the threshold value of a continuous biomarker

PubMed Central

Spencer, Amy V.; Harbron, Chris; Mander, Adrian; Wason, James; Peers, Ian

2017-01-01

Potential predictive biomarkers are often measured on a continuous scale, but in practice, a threshold value to divide the patient population into biomarker ‘positive’ and ‘negative’ is desirable. Early phase clinical trials are increasingly using biomarkers for patient selection, but at this stage, it is likely that little will be known about the relationship between the biomarker and the treatment outcome. We describe a single-arm trial design with adaptive enrichment, which can increase power to demonstrate efficacy within a patient subpopulation, the parameters of which are also estimated. Our design enables us to learn about the biomarker and optimally adjust the threshold during the study, using a combination of generalised linear modelling and Bayesian prediction. At the final analysis, a binomial exact test is carried out, allowing the hypothesis that ‘no population subset exists in which the novel treatment has a desirable response rate’ to be tested. Through extensive simulations, we are able to show increased power over fixed threshold methods in many situations without increasing the type-I error rate. We also show that estimates of the threshold, which defines the population subset, are unbiased and often more precise than those from fixed threshold studies. We provide an example of the method applied (retrospectively) to publically available data from a study of the use of tamoxifen after mastectomy by the German Breast Study Group, where progesterone receptor is the biomarker of interest. PMID:27417407

Contributions of adaptation currents to dynamic spike threshold on slow timescales: Biophysical insights from conductance-based models

NASA Astrophysics Data System (ADS)

Yi, Guosheng; Wang, Jiang; Wei, Xile; Deng, Bin; Li, Huiyan; Che, Yanqiu

2017-06-01

Spike-frequency adaptation (SFA) mediated by various adaptation currents, such as voltage-gated K+ current (IM), Ca2+-gated K+ current (IAHP), or Na+-activated K+ current (IKNa), exists in many types of neurons, which has been shown to effectively shape their information transmission properties on slow timescales. Here we use conductance-based models to investigate how the activation of three adaptation currents regulates the threshold voltage for action potential (AP) initiation during the course of SFA. It is observed that the spike threshold gets depolarized and the rate of membrane depolarization (dV/dt) preceding AP is reduced as adaptation currents reduce firing rate. It is indicated that the presence of inhibitory adaptation currents enables the neuron to generate a dynamic threshold inversely correlated with preceding dV/dt on slower timescales than fast dynamics of AP generation. By analyzing the interactions of ionic currents at subthreshold potentials, we find that the activation of adaptation currents increase the outward level of net membrane current prior to AP initiation, which antagonizes inward Na+ to result in a depolarized threshold and lower dV/dt from one AP to the next. Our simulations demonstrate that the threshold dynamics on slow timescales is a secondary effect caused by the activation of adaptation currents. These findings have provided a biophysical interpretation of the relationship between adaptation currents and spike threshold.

Modern Adaptive Analytics Approach to Lowering Seismic Network Detection Thresholds

NASA Astrophysics Data System (ADS)

Johnson, C. E.

2017-12-01

Modern seismic networks present a number of challenges, but perhaps most notably are those related to 1) extreme variation in station density, 2) temporal variation in station availability, and 3) the need to achieve detectability for much smaller events of strategic importance. The first of these has been reasonably addressed in the development of modern seismic associators, such as GLASS 3.0 by the USGS/NEIC, though some work still remains to be done in this area. However, the latter two challenges demand special attention. Station availability is impacted by weather, equipment failure or the adding or removing of stations, and while thresholds have been pushed to increasingly smaller magnitudes, new algorithms are needed to achieve even lower thresholds. Station availability can be addressed by a modern, adaptive architecture that maintains specified performance envelopes using adaptive analytics coupled with complexity theory. Finally, detection thresholds can be lowered using a novel approach that tightly couples waveform analytics with the event detection and association processes based on a principled repicking algorithm that uses particle realignment for enhanced phase discrimination.

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3'-Diaminobenzidine&Haematoxylin.

PubMed

Korzynska, Anna; Roszkowiak, Lukasz; Lopez, Carlos; Bosch, Ramon; Witkowski, Lukasz; Lejeune, Marylene

2013-03-25

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the 'brown component' extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without

An adaptive design for updating the threshold value of a continuous biomarker.

PubMed

Spencer, Amy V; Harbron, Chris; Mander, Adrian; Wason, James; Peers, Ian

2016-11-30

Potential predictive biomarkers are often measured on a continuous scale, but in practice, a threshold value to divide the patient population into biomarker 'positive' and 'negative' is desirable. Early phase clinical trials are increasingly using biomarkers for patient selection, but at this stage, it is likely that little will be known about the relationship between the biomarker and the treatment outcome. We describe a single-arm trial design with adaptive enrichment, which can increase power to demonstrate efficacy within a patient subpopulation, the parameters of which are also estimated. Our design enables us to learn about the biomarker and optimally adjust the threshold during the study, using a combination of generalised linear modelling and Bayesian prediction. At the final analysis, a binomial exact test is carried out, allowing the hypothesis that 'no population subset exists in which the novel treatment has a desirable response rate' to be tested. Through extensive simulations, we are able to show increased power over fixed threshold methods in many situations without increasing the type-I error rate. We also show that estimates of the threshold, which defines the population subset, are unbiased and often more precise than those from fixed threshold studies. We provide an example of the method applied (retrospectively) to publically available data from a study of the use of tamoxifen after mastectomy by the German Breast Study Group, where progesterone receptor is the biomarker of interest. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin

PubMed Central

2013-01-01

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the ’brown component’ extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without

Threshold-adaptive canny operator based on cross-zero points

NASA Astrophysics Data System (ADS)

Liu, Boqi; Zhang, Xiuhua; Hong, Hanyu

2018-03-01

Canny edge detection[1] is a technique to extract useful structural information from different vision objects and dramatically reduce the amount of data to be processed. It has been widely applied in various computer vision systems. There are two thresholds have to be settled before the edge is segregated from background. Usually, by the experience of developers, two static values are set as the thresholds[2]. In this paper, a novel automatic thresholding method is proposed. The relation between the thresholds and Cross-zero Points is analyzed, and an interpolation function is deduced to determine the thresholds. Comprehensive experimental results demonstrate the effectiveness of proposed method and advantageous for stable edge detection at changing illumination.

Adaptive threshold control for auto-rate fallback algorithm in IEEE 802.11 multi-rate WLANs

NASA Astrophysics Data System (ADS)

Wu, Qilin; Lu, Yang; Zhu, Xiaolin; Ge, Fangzhen

2012-03-01

The IEEE 802.11 standard supports multiple rates for data transmission in the physical layer. Nowadays, to improve network performance, a rate adaptation scheme called auto-rate fallback (ARF) is widely adopted in practice. However, ARF scheme suffers performance degradation in multiple contending nodes environments. In this article, we propose a novel rate adaptation scheme called ARF with adaptive threshold control. In multiple contending nodes environment, the proposed scheme can effectively mitigate the frame collision effect on rate adaptation decision by adaptively adjusting rate-up and rate-down threshold according to the current collision level. Simulation results show that the proposed scheme can achieve significantly higher throughput than the other existing rate adaptation schemes. Furthermore, the simulation results also demonstrate that the proposed scheme can effectively respond to the varying channel condition.

Lowering threshold energy for femtosecond laser pulse photodisruption through turbid media using adaptive optics

NASA Astrophysics Data System (ADS)

Hansen, A.; Ripken, Tammo; Krueger, Ronald R.; Lubatschowski, Holger

2011-03-01

Focussed femtosecond laser pulses are applied in ophthalmic tissues to create an optical breakdown and therefore a tissue dissection through photodisruption. The threshold irradiance for the optical breakdown depends on the photon density in the focal volume which can be influenced by the pulse energy, the size of the irradiated area (focus), and the irradiation time. For an application in the posterior eye segment the aberrations of the anterior eye elements cause a distortion of the wavefront and therefore an increased focal volume which reduces the photon density and thus raises the required energy for surpassing the threshold irradiance. The influence of adaptive optics on lowering the pulse energy required for photodisruption by refining a distorted focus was investigated. A reduction of the threshold energy can be shown when using adaptive optics. The spatial confinement with adaptive optics furthermore raises the irradiance at constant pulse energy. The lowered threshold energy allows for tissue dissection with reduced peripheral damage. This offers the possibility for moving femtosecond laser surgery from corneal or lental applications in the anterior eye to vitreal or retinal applications in the posterior eye.

Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography.

PubMed

Zaki, Farzana; Wang, Yahui; Su, Hao; Yuan, Xin; Liu, Xuan

2017-05-01

Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to the physical origin of speckle noise in OCT image. Our results demonstrate that NAWT outperforms conventional wavelet thresholding.

Evaluation and comparison of 50 Hz current threshold of electrocutaneous sensations using different methods

PubMed Central

Lindenblatt, G.; Silny, J.

2006-01-01

Leakage currents, tiny currents flowing from an everyday-life appliance through the body to the ground, can cause a non-adequate perception (called electrocutaneous sensation, ECS) or even pain and should be avoided. Safety standards for low-frequency range are based on experimental results of current thresholds of electrocutaneous sensations, which however show a wide range between about 50 μA (rms) and 1000 μA (rms). In order to be able to explain these differences, the perception threshold was measured repeatedly in experiments with test persons under identical experimental setup, but by means of different methods (measuring strategies), namely: direct adjustment, classical threshold as amperage of 50% perception probability, and confidence rating procedure of signal detection theory. The current is injected using a 1 cm2 electrode at the highly touch sensitive part of the index fingertip. These investigations show for the first time that the threshold of electrocutaneous sensations is influenced both by adaptation to the non-adequate stimulus and individual, emotional factors. Therefore, classical methods, on which the majority of the safety investigations are based, cannot be used to determine a leakage current threshold. The confidence rating procedure of the modern signal detection theory yields a value of 179.5 μA (rms) at 50 Hz power supply net frequency as the lower end of the 95% confidence range considering the variance in the investigated group. This value is expected to be free of adaptation influences, and is distinctly lower than the European limits and supports the stricter regulations of Canada and USA. PMID:17111461

Methods for SBS Threshold Reduction

DTIC Science & Technology

1994-01-30

We have investigated methods for reducing the threshold for stimulated Brillouin scattering (SBS) using a frequency-narrowed Cr,Tm,Ho:YAG laser...operating at 2.12 micrometers. The SBS medium was carbon disulfide. Single-focus SBS and threshold reduction by using two foci, a loop, and a ring have

Bayesian methods for estimating GEBVs of threshold traits

PubMed Central

Wang, C-L; Ding, X-D; Wang, J-Y; Liu, J-F; Fu, W-X; Zhang, Z; Yin, Z-J; Zhang, Q

2013-01-01

Estimation of genomic breeding values is the key step in genomic selection (GS). Many methods have been proposed for continuous traits, but methods for threshold traits are still scarce. Here we introduced threshold model to the framework of GS, and specifically, we extended the three Bayesian methods BayesA, BayesB and BayesCπ on the basis of threshold model for estimating genomic breeding values of threshold traits, and the extended methods are correspondingly termed BayesTA, BayesTB and BayesTCπ. Computing procedures of the three BayesT methods using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the benefit of the presented methods in accuracy with the genomic estimated breeding values (GEBVs) for threshold traits. Factors affecting the performance of the three BayesT methods were addressed. As expected, the three BayesT methods generally performed better than the corresponding normal Bayesian methods, in particular when the number of phenotypic categories was small. In the standard scenario (number of categories=2, incidence=30%, number of quantitative trait loci=50, h2=0.3), the accuracies were improved by 30.4%, 2.4%, and 5.7% points, respectively. In most scenarios, BayesTB and BayesTCπ generated similar accuracies and both performed better than BayesTA. In conclusion, our work proved that threshold model fits well for predicting GEBVs of threshold traits, and BayesTCπ is supposed to be the method of choice for GS of threshold traits. PMID:23149458

Optimal thresholds for the estimation of area rain-rate moments by the threshold method

NASA Technical Reports Server (NTRS)

Short, David A.; Shimizu, Kunio; Kedem, Benjamin

1993-01-01

Optimization of the threshold method, achieved by determination of the threshold that maximizes the correlation between an area-average rain-rate moment and the area coverage of rain rates exceeding the threshold, is demonstrated empirically and theoretically. Empirical results for a sequence of GATE radar snapshots show optimal thresholds of 5 and 27 mm/h for the first and second moments, respectively. Theoretical optimization of the threshold method by the maximum-likelihood approach of Kedem and Pavlopoulos (1991) predicts optimal thresholds near 5 and 26 mm/h for lognormally distributed rain rates with GATE-like parameters. The agreement between theory and observations suggests that the optimal threshold can be understood as arising due to sampling variations, from snapshot to snapshot, of a parent rain-rate distribution. Optimal thresholds for gamma and inverse Gaussian distributions are also derived and compared.

Olfactory Detection Thresholds and Adaptation in Adults with Autism Spectrum Condition

ERIC Educational Resources Information Center

Tavassoli, T.; Baron-Cohen, S.

2012-01-01

Sensory issues have been widely reported in Autism Spectrum Conditions (ASC). Since olfaction is one of the least investigated senses in ASC, the current studies explore olfactory detection thresholds and adaptation to olfactory stimuli in adults with ASC. 80 participants took part, 38 (18 females, 20 males) with ASC and 42 control participants…

Methods for automatic trigger threshold adjustment

DOEpatents

Welch, Benjamin J; Partridge, Michael E

2014-03-18

Methods are presented for adjusting trigger threshold values to compensate for drift in the quiescent level of a signal monitored for initiating a data recording event, thereby avoiding false triggering conditions. Initial threshold values are periodically adjusted by re-measuring the quiescent signal level, and adjusting the threshold values by an offset computation based upon the measured quiescent signal level drift. Re-computation of the trigger threshold values can be implemented on time based or counter based criteria. Additionally, a qualification width counter can be utilized to implement a requirement that a trigger threshold criterion be met a given number of times prior to initiating a data recording event, further reducing the possibility of a false triggering situation.

Shape anomaly detection under strong measurement noise: An analytical approach to adaptive thresholding

NASA Astrophysics Data System (ADS)

Krasichkov, Alexander S.; Grigoriev, Eugene B.; Bogachev, Mikhail I.; Nifontov, Eugene M.

2015-10-01

We suggest an analytical approach to the adaptive thresholding in a shape anomaly detection problem. We find an analytical expression for the distribution of the cosine similarity score between a reference shape and an observational shape hindered by strong measurement noise that depends solely on the noise level and is independent of the particular shape analyzed. The analytical treatment is also confirmed by computer simulations and shows nearly perfect agreement. Using this analytical solution, we suggest an improved shape anomaly detection approach based on adaptive thresholding. We validate the noise robustness of our approach using typical shapes of normal and pathological electrocardiogram cycles hindered by additive white noise. We show explicitly that under high noise levels our approach considerably outperforms the conventional tactic that does not take into account variations in the noise level.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

Comparison of image segmentation of lungs using methods: connected threshold, neighborhood connected, and threshold level set segmentation

NASA Astrophysics Data System (ADS)

Amanda, A. R.; Widita, R.

2016-03-01

The aim of this research is to compare some image segmentation methods for lungs based on performance evaluation parameter (Mean Square Error (MSE) and Peak Signal Noise to Ratio (PSNR)). In this study, the methods compared were connected threshold, neighborhood connected, and the threshold level set segmentation on the image of the lungs. These three methods require one important parameter, i.e the threshold. The threshold interval was obtained from the histogram of the original image. The software used to segment the image here was InsightToolkit-4.7.0 (ITK). This research used 5 lung images to be analyzed. Then, the results were compared using the performance evaluation parameter determined by using MATLAB. The segmentation method is said to have a good quality if it has the smallest MSE value and the highest PSNR. The results show that four sample images match the criteria of connected threshold, while one sample refers to the threshold level set segmentation. Therefore, it can be concluded that connected threshold method is better than the other two methods for these cases.

Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

NASA Astrophysics Data System (ADS)

Wang, Xiuzhong; Srinivas, Chukka

2016-03-01

This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

A threshold method for immunological correlates of protection

PubMed Central

2013-01-01

Background Immunological correlates of protection are biological markers such as disease-specific antibodies which correlate with protection against disease and which are measurable with immunological assays. It is common in vaccine research and in setting immunization policy to rely on threshold values for the correlate where the accepted threshold differentiates between individuals who are considered to be protected against disease and those who are susceptible. Examples where thresholds are used include development of a new generation 13-valent pneumococcal conjugate vaccine which was required in clinical trials to meet accepted thresholds for the older 7-valent vaccine, and public health decision making on vaccination policy based on long-term maintenance of protective thresholds for Hepatitis A, rubella, measles, Japanese encephalitis and others. Despite widespread use of such thresholds in vaccine policy and research, few statistical approaches have been formally developed which specifically incorporate a threshold parameter in order to estimate the value of the protective threshold from data. Methods We propose a 3-parameter statistical model called the a:b model which incorporates parameters for a threshold and constant but different infection probabilities below and above the threshold estimated using profile likelihood or least squares methods. Evaluation of the estimated threshold can be performed by a significance test for the existence of a threshold using a modified likelihood ratio test which follows a chi-squared distribution with 3 degrees of freedom, and confidence intervals for the threshold can be obtained by bootstrapping. The model also permits assessment of relative risk of infection in patients achieving the threshold or not. Goodness-of-fit of the a:b model may be assessed using the Hosmer-Lemeshow approach. The model is applied to 15 datasets from published clinical trials on pertussis, respiratory syncytial virus and varicella. Results

Mass Detection in Mammographic Images Using Wavelet Processing and Adaptive Threshold Technique.

PubMed

Vikhe, P S; Thool, V R

2016-04-01

Detection of mass in mammogram for early diagnosis of breast cancer is a significant assignment in the reduction of the mortality rate. However, in some cases, screening of mass is difficult task for radiologist, due to variation in contrast, fuzzy edges and noisy mammograms. Masses and micro-calcifications are the distinctive signs for diagnosis of breast cancer. This paper presents, a method for mass enhancement using piecewise linear operator in combination with wavelet processing from mammographic images. The method includes, artifact suppression and pectoral muscle removal based on morphological operations. Finally, mass segmentation for detection using adaptive threshold technique is carried out to separate the mass from background. The proposed method has been tested on 130 (45 + 85) images with 90.9 and 91 % True Positive Fraction (TPF) at 2.35 and 2.1 average False Positive Per Image(FP/I) from two different databases, namely Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM). The obtained results show that, the proposed technique gives improved diagnosis in the early breast cancer detection.

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction.

PubMed

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-13

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods.

Methods for threshold determination in multiplexed assays

DOEpatents

Tammero, Lance F. Bentley; Dzenitis, John M; Hindson, Benjamin J

2014-06-24

Methods for determination of threshold values of signatures comprised in an assay are described. Each signature enables detection of a target. The methods determine a probability density function of negative samples and a corresponding false positive rate curve. A false positive criterion is established and a threshold for that signature is determined as a point at which the false positive rate curve intersects the false positive criterion. A method for quantitative analysis and interpretation of assay results together with a method for determination of a desired limit of detection of a signature in an assay are also described.

A lane line segmentation algorithm based on adaptive threshold and connected domain theory

NASA Astrophysics Data System (ADS)

Feng, Hui; Xu, Guo-sheng; Han, Yi; Liu, Yang

2018-04-01

Before detecting cracks and repairs on road lanes, it's necessary to eliminate the influence of lane lines on the recognition result in road lane images. Aiming at the problems caused by lane lines, an image segmentation algorithm based on adaptive threshold and connected domain is proposed. First, by analyzing features like grey level distribution and the illumination of the images, the algorithm uses Hough transform to divide the images into different sections and convert them into binary images separately. It then uses the connected domain theory to amend the outcome of segmentation, remove noises and fill the interior zone of lane lines. Experiments have proved that this method could eliminate the influence of illumination and lane line abrasion, removing noises thoroughly while maintaining high segmentation precision.

Passive activity observation (PAO) method to estimate outdoor thermal adaptation in public space: case studies in Australian cities.

PubMed

Sharifi, Ehsan; Boland, John

2018-06-18

Outdoor thermal comfort is influenced by people's climate expectations, perceptions and adaptation capacity. Varied individual response to comfortable or stressful thermal environments results in a deviation between actual outdoor thermal activity choices and those predicted by thermal comfort indices. This paper presents a passive activity observation (PAO) method for estimating contextual limits of outdoor thermal adaptation. The PAO method determines which thermal environment result in statistically meaningful changes may occur in outdoor activity patterns, and it estimates thresholds of outdoor thermal neutrality and limits of thermal adaptation in public space based on activity observation and microclimate field measurement. Applications of the PAO method have been demonstrated in Adelaide, Melbourne and Sydney, where outdoor activities were analysed against outdoor thermal comfort indices between 2013 and 2014. Adjusted apparent temperature (aAT), adaptive predicted mean vote (aPMV), outdoor standard effective temperature (OUT_SET), physiological equivalent temperature (PET) and universal thermal comfort index (UTCI) are calculated from the PAO data. Using the PAO method, the high threshold of outdoor thermal neutrality was observed between 24 °C for optional activities and 34 °C for necessary activities (UTCI scale). Meanwhile, the ultimate limit of thermal adaptation in uncontrolled public spaces is estimated to be between 28 °C for social activities and 48 °C for necessary activities. Normalised results indicate that city-wide high thresholds for outdoor thermal neutrality vary from 25 °C in Melbourne to 26 °C in Sydney and 30 °C in Adelaide. The PAO method is a relatively fast and localised method for measuring limits of outdoor thermal adaptation and effectively informs urban design and policy making in the context of climate change.

Predicting missing values in a home care database using an adaptive uncertainty rule method.

PubMed

Konias, S; Gogou, G; Bamidis, P D; Vlahavas, I; Maglaveras, N

2005-01-01

Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. In this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

A study of the threshold method utilizing raingage data

NASA Technical Reports Server (NTRS)

Short, David A.; Wolff, David B.; Rosenfeld, Daniel; Atlas, David

1993-01-01

The threshold method for estimation of area-average rain rate relies on determination of the fractional area where rain rate exceeds a preset level of intensity. Previous studies have shown that the optimal threshold level depends on the climatological rain-rate distribution (RRD). It has also been noted, however, that the climatological RRD may be composed of an aggregate of distributions, one for each of several distinctly different synoptic conditions, each having its own optimal threshold. In this study, the impact of RRD variations on the threshold method is shown in an analysis of 1-min rainrate data from a network of tipping-bucket gauges in Darwin, Australia. Data are analyzed for two distinct regimes: the premonsoon environment, having isolated intense thunderstorms, and the active monsoon rains, having organized convective cell clusters that generate large areas of stratiform rain. It is found that a threshold of 10 mm/h results in the same threshold coefficient for both regimes, suggesting an alternative definition of optimal threshold as that which is least sensitive to distribution variations. The observed behavior of the threshold coefficient is well simulated by assumption of lognormal distributions with different scale parameters and same shape parameters.

Chaotic Signal Denoising Based on Hierarchical Threshold Synchrosqueezed Wavelet Transform

NASA Astrophysics Data System (ADS)

Wang, Wen-Bo; Jing, Yun-yu; Zhao, Yan-chao; Zhang, Lian-Hua; Wang, Xiang-Li

2017-12-01

In order to overcoming the shortcoming of single threshold synchrosqueezed wavelet transform(SWT) denoising method, an adaptive hierarchical threshold SWT chaotic signal denoising method is proposed. Firstly, a new SWT threshold function is constructed based on Stein unbiased risk estimation, which is two order continuous derivable. Then, by using of the new threshold function, a threshold process based on the minimum mean square error was implemented, and the optimal estimation value of each layer threshold in SWT chaotic denoising is obtained. The experimental results of the simulating chaotic signal and measured sunspot signals show that, the proposed method can filter the noise of chaotic signal well, and the intrinsic chaotic characteristic of the original signal can be recovered very well. Compared with the EEMD denoising method and the single threshold SWT denoising method, the proposed method can obtain better denoising result for the chaotic signal.

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction

PubMed Central

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-01

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods. PMID:29342857

A de-noising algorithm based on wavelet threshold-exponential adaptive window width-fitting for ground electrical source airborne transient electromagnetic signal

NASA Astrophysics Data System (ADS)

Ji, Yanju; Li, Dongsheng; Yu, Mingmei; Wang, Yuan; Wu, Qiong; Lin, Jun

2016-05-01

The ground electrical source airborne transient electromagnetic system (GREATEM) on an unmanned aircraft enjoys considerable prospecting depth, lateral resolution and detection efficiency, etc. In recent years it has become an important technical means of rapid resources exploration. However, GREATEM data are extremely vulnerable to stationary white noise and non-stationary electromagnetic noise (sferics noise, aircraft engine noise and other human electromagnetic noises). These noises will cause degradation of the imaging quality for data interpretation. Based on the characteristics of the GREATEM data and major noises, we propose a de-noising algorithm utilizing wavelet threshold method and exponential adaptive window width-fitting. Firstly, the white noise is filtered in the measured data using the wavelet threshold method. Then, the data are segmented using data window whose step length is even logarithmic intervals. The data polluted by electromagnetic noise are identified within each window based on the discriminating principle of energy detection, and the attenuation characteristics of the data slope are extracted. Eventually, an exponential fitting algorithm is adopted to fit the attenuation curve of each window, and the data polluted by non-stationary electromagnetic noise are replaced with their fitting results. Thus the non-stationary electromagnetic noise can be effectively removed. The proposed algorithm is verified by the synthetic and real GREATEM signals. The results show that in GREATEM signal, stationary white noise and non-stationary electromagnetic noise can be effectively filtered using the wavelet threshold-exponential adaptive window width-fitting algorithm, which enhances the imaging quality.

Hair segmentation using adaptive threshold from edge and branch length measures.

PubMed

Lee, Ian; Du, Xian; Anthony, Brian

2017-10-01

Non-invasive imaging techniques allow the monitoring of skin structure and diagnosis of skin diseases in clinical applications. However, hair in skin images hampers the imaging and classification of the skin structure of interest. Although many hair segmentation methods have been proposed for digital hair removal, a major challenge in hair segmentation remains in detecting hairs that are thin, overlapping, of similar contrast or color to underlying skin, or overlaid on highly-textured skin structure. To solve the problem, we present an automatic hair segmentation method that uses edge density (ED) and mean branch length (MBL) to measure hair. First, hair is detected by the integration of top-hat transform and modified second-order Gaussian filter. Second, we employ a robust adaptive threshold of ED and MBL to generate a hair mask. Third, the hair mask is refined by k-NN classification of hair and skin pixels. The proposed algorithm was tested using two datasets of healthy skin images and lesion images respectively. These datasets were taken from different imaging platforms in various illumination levels and varying skin colors. We compared the hair detection and segmentation results from our algorithm and six other hair segmentation methods of state of the art. Our method exhibits high value of sensitivity: 75% and specificity: 95%, which indicates significantly higher accuracy and better balance between true positive and false positive detection than the other methods. Published by Elsevier Ltd.

Estimation of pulse rate from ambulatory PPG using ensemble empirical mode decomposition and adaptive thresholding.

PubMed

Pittara, Melpo; Theocharides, Theocharis; Orphanidou, Christina

2017-07-01

A new method for deriving pulse rate from PPG obtained from ambulatory patients is presented. The method employs Ensemble Empirical Mode Decomposition to identify the pulsatile component from noise-corrupted PPG, and then uses a set of physiologically-relevant rules followed by adaptive thresholding, in order to estimate the pulse rate in the presence of noise. The method was optimized and validated using 63 hours of data obtained from ambulatory hospital patients. The F1 score obtained with respect to expertly annotated data was 0.857 and the mean absolute errors of estimated pulse rates with respect to heart rates obtained from ECG collected in parallel were 1.72 bpm for "good" quality PPG and 4.49 bpm for "bad" quality PPG. Both errors are within the clinically acceptable margin-of-error for pulse rate/heart rate measurements, showing the promise of the proposed approach for inclusion in next generation wearable sensors.

QUEST - A Bayesian adaptive psychometric method

NASA Technical Reports Server (NTRS)

Watson, A. B.; Pelli, D. G.

1983-01-01

An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.

Adaptive thresholding image series from fluorescence confocal scanning laser microscope using orientation intensity profiles

NASA Astrophysics Data System (ADS)

Feng, Judy J.; Ip, Horace H.; Cheng, Shuk H.

2004-05-01

Many grey-level thresholding methods based on histogram or other statistic information about the interest image such as maximum entropy and so on have been proposed in the past. However, most methods based on statistic analysis of the images concerned little about the characteristics of morphology of interest objects, which sometimes could provide very important indication which can help to find the optimum threshold, especially for those organisms which have special texture morphologies such as vasculature, neuro-network etc. in medical imaging. In this paper, we propose a novel method for thresholding the fluorescent vasculature image series recorded from Confocal Scanning Laser Microscope. After extracting the basic orientation of the slice of vessels inside a sub-region partitioned from the images, we analysis the intensity profiles perpendicular to the vessel orientation to get the reasonable initial threshold for each region. Then the threshold values of those regions near the interest one both in x-y and optical directions have been referenced to get the final result of thresholds of the region, which makes the whole stack of images look more continuous. The resulting images are characterized by suppressing both noise and non-interest tissues conglutinated to vessels, while improving the vessel connectivities and edge definitions. The value of the method for idealized thresholding the fluorescence images of biological objects is demonstrated by a comparison of the results of 3D vascular reconstruction.

Uncertainty Estimates of Psychoacoustic Thresholds Obtained from Group Tests

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Christian, Andrew

2016-01-01

Adaptive psychoacoustic test methods, in which the next signal level depends on the response to the previous signal, are the most efficient for determining psychoacoustic thresholds of individual subjects. In many tests conducted in the NASA psychoacoustic labs, the goal is to determine thresholds representative of the general population. To do this economically, non-adaptive testing methods are used in which three or four subjects are tested at the same time with predetermined signal levels. This approach requires us to identify techniques for assessing the uncertainty in resulting group-average psychoacoustic thresholds. In this presentation we examine the Delta Method of frequentist statistics, the Generalized Linear Model (GLM), the Nonparametric Bootstrap, a frequentist method, and Markov Chain Monte Carlo Posterior Estimation and a Bayesian approach. Each technique is exercised on a manufactured, theoretical dataset and then on datasets from two psychoacoustics facilities at NASA. The Delta Method is the simplest to implement and accurate for the cases studied. The GLM is found to be the least robust, and the Bootstrap takes the longest to calculate. The Bayesian Posterior Estimate is the most versatile technique examined because it allows the inclusion of prior information.

Threshold selection for classification of MR brain images by clustering method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moldovanu, Simona; Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi; Obreja, Cristian

Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzedmore » images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.« less

Threshold selection for classification of MR brain images by clustering method

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

2015-12-01

Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

Point estimation following two-stage adaptive threshold enrichment clinical trials.

PubMed

Kimani, Peter K; Todd, Susan; Renfro, Lindsay A; Stallard, Nigel

2018-05-31

Recently, several study designs incorporating treatment effect assessment in biomarker-based subpopulations have been proposed. Most statistical methodologies for such designs focus on the control of type I error rate and power. In this paper, we have developed point estimators for clinical trials that use the two-stage adaptive enrichment threshold design. The design consists of two stages, where in stage 1, patients are recruited in the full population. Stage 1 outcome data are then used to perform interim analysis to decide whether the trial continues to stage 2 with the full population or a subpopulation. The subpopulation is defined based on one of the candidate threshold values of a numerical predictive biomarker. To estimate treatment effect in the selected subpopulation, we have derived unbiased estimators, shrinkage estimators, and estimators that estimate bias and subtract it from the naive estimate. We have recommended one of the unbiased estimators. However, since none of the estimators dominated in all simulation scenarios based on both bias and mean squared error, an alternative strategy would be to use a hybrid estimator where the estimator used depends on the subpopulation selected. This would require a simulation study of plausible scenarios before the trial. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Lowered threshold energy for femtosecond laser induced optical breakdown in a water based eye model by aberration correction with adaptive optics.

PubMed

Hansen, Anja; Géneaux, Romain; Günther, Axel; Krüger, Alexander; Ripken, Tammo

2013-06-01

In femtosecond laser ophthalmic surgery tissue dissection is achieved by photodisruption based on laser induced optical breakdown. In order to minimize collateral damage to the eye laser surgery systems should be optimized towards the lowest possible energy threshold for photodisruption. However, optical aberrations of the eye and the laser system distort the irradiance distribution from an ideal profile which causes a rise in breakdown threshold energy even if great care is taken to minimize the aberrations of the system during design and alignment. In this study we used a water chamber with an achromatic focusing lens and a scattering sample as eye model and determined breakdown threshold in single pulse plasma transmission loss measurements. Due to aberrations, the precise lower limit for breakdown threshold irradiance in water is still unknown. Here we show that the threshold energy can be substantially reduced when using adaptive optics to improve the irradiance distribution by spatial beam shaping. We found that for initial aberrations with a root-mean-square wave front error of only one third of the wavelength the threshold energy can still be reduced by a factor of three if the aberrations are corrected to the diffraction limit by adaptive optics. The transmitted pulse energy is reduced by 17% at twice the threshold. Furthermore, the gas bubble motions after breakdown for pulse trains at 5 kilohertz repetition rate show a more transverse direction in the corrected case compared to the more spherical distribution without correction. Our results demonstrate how both applied and transmitted pulse energy could be reduced during ophthalmic surgery when correcting for aberrations. As a consequence, the risk of retinal damage by transmitted energy and the extent of collateral damage to the focal volume could be minimized accordingly when using adaptive optics in fs-laser surgery.

Lowered threshold energy for femtosecond laser induced optical breakdown in a water based eye model by aberration correction with adaptive optics

PubMed Central

Hansen, Anja; Géneaux, Romain; Günther, Axel; Krüger, Alexander; Ripken, Tammo

2013-01-01

In femtosecond laser ophthalmic surgery tissue dissection is achieved by photodisruption based on laser induced optical breakdown. In order to minimize collateral damage to the eye laser surgery systems should be optimized towards the lowest possible energy threshold for photodisruption. However, optical aberrations of the eye and the laser system distort the irradiance distribution from an ideal profile which causes a rise in breakdown threshold energy even if great care is taken to minimize the aberrations of the system during design and alignment. In this study we used a water chamber with an achromatic focusing lens and a scattering sample as eye model and determined breakdown threshold in single pulse plasma transmission loss measurements. Due to aberrations, the precise lower limit for breakdown threshold irradiance in water is still unknown. Here we show that the threshold energy can be substantially reduced when using adaptive optics to improve the irradiance distribution by spatial beam shaping. We found that for initial aberrations with a root-mean-square wave front error of only one third of the wavelength the threshold energy can still be reduced by a factor of three if the aberrations are corrected to the diffraction limit by adaptive optics. The transmitted pulse energy is reduced by 17% at twice the threshold. Furthermore, the gas bubble motions after breakdown for pulse trains at 5 kilohertz repetition rate show a more transverse direction in the corrected case compared to the more spherical distribution without correction. Our results demonstrate how both applied and transmitted pulse energy could be reduced during ophthalmic surgery when correcting for aberrations. As a consequence, the risk of retinal damage by transmitted energy and the extent of collateral damage to the focal volume could be minimized accordingly when using adaptive optics in fs-laser surgery. PMID:23761849

Shear wave speed estimation by adaptive random sample consensus method.

PubMed

Lin, Haoming; Wang, Tianfu; Chen, Siping

2014-01-01

This paper describes a new method for shear wave velocity estimation that is capable of extruding outliers automatically without preset threshold. The proposed method is an adaptive random sample consensus (ARANDSAC) and the metric used here is finding the certain percentage of inliers according to the closest distance criterion. To evaluate the method, the simulation and phantom experiment results were compared using linear regression with all points (LRWAP) and radon sum transform (RS) method. The assessment reveals that the relative biases of mean estimation are 20.00%, 4.67% and 5.33% for LRWAP, ARANDSAC and RS respectively for simulation, 23.53%, 4.08% and 1.08% for phantom experiment. The results suggested that the proposed ARANDSAC algorithm is accurate in shear wave speed estimation.

Evaluation of Maryland abutment scour equation through selected threshold velocity methods

USGS Publications Warehouse

Benedict, S.T.

2010-01-01

The U.S. Geological Survey, in cooperation with the Maryland State Highway Administration, used field measurements of scour to evaluate the sensitivity of the Maryland abutment scour equation to the critical (or threshold) velocity variable. Four selected methods for estimating threshold velocity were applied to the Maryland abutment scour equation, and the predicted scour to the field measurements were compared. Results indicated that performance of the Maryland abutment scour equation was sensitive to the threshold velocity with some threshold velocity methods producing better estimates of predicted scour than did others. In addition, results indicated that regional stream characteristics can affect the performance of the Maryland abutment scour equation with moderate-gradient streams performing differently from low-gradient streams. On the basis of the findings of the investigation, guidance for selecting threshold velocity methods for application to the Maryland abutment scour equation are provided, and limitations are noted.

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Network analysis of a financial market based on genuine correlation and threshold method

NASA Astrophysics Data System (ADS)

Namaki, A.; Shirazi, A. H.; Raei, R.; Jafari, G. R.

2011-10-01

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock network. For a better risk management, we clean the correlation matrix by removing the market mode from data and then construct this matrix based on the residuals. We show that this technique has an important effect on correlation coefficient distribution by applying it for Dow Jones Industrial Average (DJIA). To study the topological structure of a network we apply the removing market mode technique and the threshold method to Tehran Stock Exchange (TSE) as an example. We show that this network follows a power-law model in certain intervals. We also show the behavior of clustering coefficients and component numbers of this network for different thresholds. These outputs are useful for both theoretical and practical purposes such as asset allocation and risk management.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

PubMed Central

Hondula, David M.; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-01-01

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634 PMID:28885979

A multigrid method for steady Euler equations on unstructured adaptive grids

NASA Technical Reports Server (NTRS)

Riemslagh, Kris; Dick, Erik

1993-01-01

A flux-difference splitting type algorithm is formulated for the steady Euler equations on unstructured grids. The polynomial flux-difference splitting technique is used. A vertex-centered finite volume method is employed on a triangular mesh. The multigrid method is in defect-correction form. A relaxation procedure with a first order accurate inner iteration and a second-order correction performed only on the finest grid, is used. A multi-stage Jacobi relaxation method is employed as a smoother. Since the grid is unstructured a Jacobi type is chosen. The multi-staging is necessary to provide sufficient smoothing properties. The domain is discretized using a Delaunay triangular mesh generator. Three grids with more or less uniform distribution of nodes but with different resolution are generated by successive refinement of the coarsest grid. Nodes of coarser grids appear in the finer grids. The multigrid method is started on these grids. As soon as the residual drops below a threshold value, an adaptive refinement is started. The solution on the adaptively refined grid is accelerated by a multigrid procedure. The coarser multigrid grids are generated by successive coarsening through point removement. The adaption cycle is repeated a few times. Results are given for the transonic flow over a NACA-0012 airfoil.

Optimum threshold selection method of centroid computation for Gaussian spot

NASA Astrophysics Data System (ADS)

Li, Xuxu; Li, Xinyang; Wang, Caixia

2015-10-01

Centroid computation of Gaussian spot is often conducted to get the exact position of a target or to measure wave-front slopes in the fields of target tracking and wave-front sensing. Center of Gravity (CoG) is the most traditional method of centroid computation, known as its low algorithmic complexity. However both electronic noise from the detector and photonic noise from the environment reduces its accuracy. In order to improve the accuracy, thresholding is unavoidable before centroid computation, and optimum threshold need to be selected. In this paper, the model of Gaussian spot is established to analyze the performance of optimum threshold under different Signal-to-Noise Ratio (SNR) conditions. Besides, two optimum threshold selection methods are introduced: TmCoG (using m % of the maximum intensity of spot as threshold), and TkCoG ( usingμn +κσ n as the threshold), μn and σn are the mean value and deviation of back noise. Firstly, their impact on the detection error under various SNR conditions is simulated respectively to find the way to decide the value of k or m. Then, a comparison between them is made. According to the simulation result, TmCoG is superior over TkCoG for the accuracy of selected threshold, and detection error is also lower.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

PubMed

Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-08-16

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method

PubMed Central

Vega, Tomás; Lozano, Jose Eugenio; Meerhoff, Tamara; Snacken, René; Mott, Joshua; Ortiz de Lejarazu, Raul; Nunes, Baltazar

2012-01-01

Please cite this paper as: Vega et al. (2012) Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza and Other Respiratory Viruses 7(4), 546–558. Background  Timely influenza surveillance is important to monitor influenza epidemics. Objectives  (i) To calculate the epidemic threshold for influenza‐like illness (ILI) and acute respiratory infections (ARI) in 19 countries, as well as the thresholds for different levels of intensity. (ii) To evaluate the performance of these thresholds. Methods  The moving epidemic method (MEM) has been developed to determine the baseline influenza activity and an epidemic threshold. False alerts, detection lags and timeliness of the detection of epidemics were calculated. The performance was evaluated using a cross‐validation procedure. Results  The overall sensitivity of the MEM threshold was 71·8% and the specificity was 95·5%. The median of the timeliness was 1 week (range: 0–4·5). Conclusions  The method produced a robust and specific signal to detect influenza epidemics. The good balance between the sensitivity and specificity of the epidemic threshold to detect seasonal epidemics and avoid false alerts has advantages for public health purposes. This method may serve as standard to define the start of the annual influenza epidemic in countries in Europe. PMID:22897919

Evaluation of different methods for determining growing degree-day thresholds in apricot cultivars

NASA Astrophysics Data System (ADS)

Ruml, Mirjana; Vuković, Ana; Milatović, Dragan

2010-07-01

The aim of this study was to examine different methods for determining growing degree-day (GDD) threshold temperatures for two phenological stages (full bloom and harvest) and select the optimal thresholds for a greater number of apricot ( Prunus armeniaca L.) cultivars grown in the Belgrade region. A 10-year data series were used to conduct the study. Several commonly used methods to determine the threshold temperatures from field observation were evaluated: (1) the least standard deviation in GDD; (2) the least standard deviation in days; (3) the least coefficient of variation in GDD; (4) regression coefficient; (5) the least standard deviation in days with a mean temperature above the threshold; (6) the least coefficient of variation in days with a mean temperature above the threshold; and (7) the smallest root mean square error between the observed and predicted number of days. In addition, two methods for calculating daily GDD, and two methods for calculating daily mean air temperatures were tested to emphasize the differences that can arise by different interpretations of basic GDD equation. The best agreement with observations was attained by method (7). The lower threshold temperature obtained by this method differed among cultivars from -5.6 to -1.7°C for full bloom, and from -0.5 to 6.6°C for harvest. However, the “Null” method (lower threshold set to 0°C) and “Fixed Value” method (lower threshold set to -2°C for full bloom and to 3°C for harvest) gave very good results. The limitations of the widely used method (1) and methods (5) and (6), which generally performed worst, are discussed in the paper.

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Viral Diversity Threshold for Adaptive Immunity in Prokaryotes

PubMed Central

Weinberger, Ariel D.; Wolf, Yuri I.; Lobkovsky, Alexander E.; Gilmore, Michael S.; Koonin, Eugene V.

2012-01-01

ABSTRACT Bacteria and archaea face continual onslaughts of rapidly diversifying viruses and plasmids. Many prokaryotes maintain adaptive immune systems known as clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (Cas). CRISPR-Cas systems are genomic sensors that serially acquire viral and plasmid DNA fragments (spacers) that are utilized to target and cleave matching viral and plasmid DNA in subsequent genomic invasions, offering critical immunological memory. Only 50% of sequenced bacteria possess CRISPR-Cas immunity, in contrast to over 90% of sequenced archaea. To probe why half of bacteria lack CRISPR-Cas immunity, we combined comparative genomics and mathematical modeling. Analysis of hundreds of diverse prokaryotic genomes shows that CRISPR-Cas systems are substantially more prevalent in thermophiles than in mesophiles. With sequenced bacteria disproportionately mesophilic and sequenced archaea mostly thermophilic, the presence of CRISPR-Cas appears to depend more on environmental temperature than on bacterial-archaeal taxonomy. Mutation rates are typically severalfold higher in mesophilic prokaryotes than in thermophilic prokaryotes. To quantitatively test whether accelerated viral mutation leads microbes to lose CRISPR-Cas systems, we developed a stochastic model of virus-CRISPR coevolution. The model competes CRISPR-Cas-positive (CRISPR-Cas+) prokaryotes against CRISPR-Cas-negative (CRISPR-Cas−) prokaryotes, continually weighing the antiviral benefits conferred by CRISPR-Cas immunity against its fitness costs. Tracking this cost-benefit analysis across parameter space reveals viral mutation rate thresholds beyond which CRISPR-Cas cannot provide sufficient immunity and is purged from host populations. These results offer a simple, testable viral diversity hypothesis to explain why mesophilic bacteria disproportionately lack CRISPR-Cas immunity. More generally, fundamental limits on the adaptability of biological

The scotopic threshold response of the dark-adapted electroretinogram of the mouse.

PubMed

Saszik, Shannon M; Robson, John G; Frishman, Laura J

2002-09-15

The most sensitive response in the dark-adapted electroretinogram (ERG), the scotopic threshold response (STR) which originates from the proximal retina, has been identified in several mammals including humans, but previously not in the mouse. The current study established the presence and assessed the nature of the mouse STR. ERGs were recorded from adult wild-type C57/BL6 mice anaesthetized with ketamine (70 mg kg(-1)) and xylazine (7 mg kg(-1)). Recordings were between DTL fibres placed under contact lenses on the two eyes. Monocular test stimuli were brief flashes (lambda(max) 462 nm; -6.1 to +1.8 log scotopic Troland seconds(sc td s)) under fully dark-adapted conditions and in the presence of steady adapting backgrounds (-3.2 to -1.7 log sc td). For the weakest test stimuli, ERGs consisted of a slow negative potential maximal approximately 200 ms after the flash, with a small positive potential preceding it. The negative wave resembled the STR of other species. As intensity was increased, the negative potential saturated but the positive potential (maximal approximately 110 ms) continued to grow as the b-wave. For stimuli that saturated the b-wave, the a-wave emerged. For stimulus strengths up to those at which the a-wave emerged, ERG amplitudes measured at fixed times after the flash (110 and 200 ms) were fitted with a model assuming an initially linear rise of response amplitude with intensity, followed by saturation of five components of declining sensitivity: a negative STR (nSTR), a positive STR (pSTR), a positive scotopic response (pSR), PII (the bipolar cell component) and PIII (the photoreceptor component). The nSTR and pSTR were approximately 3 times more sensitive than the pSR, which was approximately 7 times more sensitive than PII. The sensitive positive components dominated the b-wave up to > 5 % of its saturated amplitude. Pharmacological agents that suppress proximal retinal activity (e.g. GABA) minimized the pSTR, nSTR and pSR, essentially

Adaptive Monte Carlo methods

NASA Astrophysics Data System (ADS)

Fasnacht, Marc

We develop adaptive Monte Carlo methods for the calculation of the free energy as a function of a parameter of interest. The methods presented are particularly well-suited for systems with complex energy landscapes, where standard sampling techniques have difficulties. The Adaptive Histogram Method uses a biasing potential derived from histograms recorded during the simulation to achieve uniform sampling in the parameter of interest. The Adaptive Integration method directly calculates an estimate of the free energy from the average derivative of the Hamiltonian with respect to the parameter of interest and uses it as a biasing potential. We compare both methods to a state of the art method, and demonstrate that they compare favorably for the calculation of potentials of mean force of dense Lennard-Jones fluids. We use the Adaptive Integration Method to calculate accurate potentials of mean force for different types of simple particles in a Lennard-Jones fluid. Our approach allows us to separate the contributions of the solvent to the potential of mean force from the effect of the direct interaction between the particles. With contributions of the solvent determined, we can find the potential of mean force directly for any other direct interaction without additional simulations. We also test the accuracy of the Adaptive Integration Method on a thermodynamic cycle, which allows us to perform a consistency check between potentials of mean force and chemical potentials calculated using the Adaptive Integration Method. The results demonstrate a high degree of consistency of the method.

A Fiber Bragg Grating Interrogation System with Self-Adaption Threshold Peak Detection Algorithm.

PubMed

Zhang, Weifang; Li, Yingwu; Jin, Bo; Ren, Feifei; Wang, Hongxun; Dai, Wei

2018-04-08

A Fiber Bragg Grating (FBG) interrogation system with a self-adaption threshold peak detection algorithm is proposed and experimentally demonstrated in this study. This system is composed of a field programmable gate array (FPGA) and advanced RISC machine (ARM) platform, tunable Fabry-Perot (F-P) filter and optical switch. To improve system resolution, the F-P filter was employed. As this filter is non-linear, this causes the shifting of central wavelengths with the deviation compensated by the parts of the circuit. Time-division multiplexing (TDM) of FBG sensors is achieved by an optical switch, with the system able to realize the combination of 256 FBG sensors. The wavelength scanning speed of 800 Hz can be achieved by a FPGA+ARM platform. In addition, a peak detection algorithm based on a self-adaption threshold is designed and the peak recognition rate is 100%. Experiments with different temperatures were conducted to demonstrate the effectiveness of the system. Four FBG sensors were examined in the thermal chamber without stress. When the temperature changed from 0 °C to 100 °C, the degree of linearity between central wavelengths and temperature was about 0.999 with the temperature sensitivity being 10 pm/°C. The static interrogation precision was able to reach 0.5 pm. Through the comparison of different peak detection algorithms and interrogation approaches, the system was verified to have an optimum comprehensive performance in terms of precision, capacity and speed.

A Fiber Bragg Grating Interrogation System with Self-Adaption Threshold Peak Detection Algorithm

PubMed Central

Zhang, Weifang; Li, Yingwu; Jin, Bo; Ren, Feifei

2018-01-01

A Fiber Bragg Grating (FBG) interrogation system with a self-adaption threshold peak detection algorithm is proposed and experimentally demonstrated in this study. This system is composed of a field programmable gate array (FPGA) and advanced RISC machine (ARM) platform, tunable Fabry–Perot (F–P) filter and optical switch. To improve system resolution, the F–P filter was employed. As this filter is non-linear, this causes the shifting of central wavelengths with the deviation compensated by the parts of the circuit. Time-division multiplexing (TDM) of FBG sensors is achieved by an optical switch, with the system able to realize the combination of 256 FBG sensors. The wavelength scanning speed of 800 Hz can be achieved by a FPGA+ARM platform. In addition, a peak detection algorithm based on a self-adaption threshold is designed and the peak recognition rate is 100%. Experiments with different temperatures were conducted to demonstrate the effectiveness of the system. Four FBG sensors were examined in the thermal chamber without stress. When the temperature changed from 0 °C to 100 °C, the degree of linearity between central wavelengths and temperature was about 0.999 with the temperature sensitivity being 10 pm/°C. The static interrogation precision was able to reach 0.5 pm. Through the comparison of different peak detection algorithms and interrogation approaches, the system was verified to have an optimum comprehensive performance in terms of precision, capacity and speed. PMID:29642507

Adaptive threshold determination for efficient channel sensing in cognitive radio network using mobile sensors

NASA Astrophysics Data System (ADS)

Morshed, M. N.; Khatun, S.; Kamarudin, L. M.; Aljunid, S. A.; Ahmad, R. B.; Zakaria, A.; Fakir, M. M.

2017-03-01

Spectrum saturation problem is a major issue in wireless communication systems all over the world. Huge number of users is joining each day to the existing fixed band frequency but the bandwidth is not increasing. These requirements demand for efficient and intelligent use of spectrum. To solve this issue, the Cognitive Radio (CR) is the best choice. Spectrum sensing of a wireless heterogeneous network is a fundamental issue to detect the presence of primary users' signals in CR networks. In order to protect primary users (PUs) from harmful interference, the spectrum sensing scheme is required to perform well even in low signal-to-noise ratio (SNR) environments. Meanwhile, the sensing period is usually required to be short enough so that secondary (unlicensed) users (SUs) can fully utilize the available spectrum. CR networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary user's licensed frequency bands. In this paper, we have proposed an adaptive threshold detection method to detect presence of PU signal using free space path loss (FSPL) model in 2.4 GHz WLAN network. The model is designed for mobile sensors embedded in smartphones. The mobile sensors acts as SU while the existing WLAN network (channels) works as PU. The theoretical results show that the desired threshold range detection of mobile sensors mainly depends on the noise floor level of the location in consideration.

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

NASA Technical Reports Server (NTRS)

Smith, Paul L.; VonderHaar, Thomas H.

1996-01-01

The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

Is there a minimum intensity threshold for resistance training-induced hypertrophic adaptations?

PubMed

Schoenfeld, Brad J

2013-12-01

In humans, regimented resistance training has been shown to promote substantial increases in skeletal muscle mass. With respect to traditional resistance training methods, the prevailing opinion is that an intensity of greater than ~60 % of 1 repetition maximum (RM) is necessary to elicit significant increases in muscular size. It has been surmised that this is the minimum threshold required to activate the complete spectrum of fiber types, particularly those associated with the largest motor units. There is emerging evidence, however, that low-intensity resistance training performed with blood flow restriction (BFR) can promote marked increases in muscle hypertrophy, in many cases equal to that of traditional high-intensity exercise. The anabolic effects of such occlusion-based training have been attributed to increased levels of metabolic stress that mediate hypertrophy at least in part by enhancing recruitment of high-threshold motor units. Recently, several researchers have put forth the theory that low-intensity exercise (≤50 % 1RM) performed without BFR can promote increases in muscle size equal, or perhaps even superior, to that at higher intensities, provided training is carried out to volitional muscular failure. Proponents of the theory postulate that fatiguing contractions at light loads is simply a milder form of BFR and thus ultimately results in maximal muscle fiber recruitment. Current research indicates that low-load exercise can indeed promote increases in muscle growth in untrained subjects, and that these gains may be functionally, metabolically, and/or aesthetically meaningful. However, whether hypertrophic adaptations can equal that achieved with higher intensity resistance exercise (≤60 % 1RM) remains to be determined. Furthermore, it is not clear as to what, if any, hypertrophic effects are seen with low-intensity exercise in well-trained subjects as experimental studies on the topic in this population are lacking. Practical

A multi-threshold sampling method for TOF-PET signal processing

NASA Astrophysics Data System (ADS)

Kim, H.; Kao, C. M.; Xie, Q.; Chen, C. T.; Zhou, L.; Tang, F.; Frisch, H.; Moses, W. W.; Choong, W. S.

2009-04-01

As an approach to realizing all-digital data acquisition for positron emission tomography (PET), we have previously proposed and studied a multi-threshold sampling method to generate samples of a PET event waveform with respect to a few user-defined amplitudes. In this sampling scheme, one can extract both the energy and timing information for an event. In this paper, we report our prototype implementation of this sampling method and the performance results obtained with this prototype. The prototype consists of two multi-threshold discriminator boards and a time-to-digital converter (TDC) board. Each of the multi-threshold discriminator boards takes one input and provides up to eight threshold levels, which can be defined by users, for sampling the input signal. The TDC board employs the CERN HPTDC chip that determines the digitized times of the leading and falling edges of the discriminator output pulses. We connect our prototype electronics to the outputs of two Hamamatsu R9800 photomultiplier tubes (PMTs) that are individually coupled to a 6.25×6.25×25 mm3 LSO crystal. By analyzing waveform samples generated by using four thresholds, we obtain a coincidence timing resolution of about 340 ps and an ˜18% energy resolution at 511 keV. We are also able to estimate the decay-time constant from the resulting samples and obtain a mean value of 44 ns with an ˜9 ns FWHM. In comparison, using digitized waveforms obtained at a 20 GSps sampling rate for the same LSO/PMT modules we obtain ˜300 ps coincidence timing resolution, ˜14% energy resolution at 511 keV, and ˜5 ns FWHM for the estimated decay-time constant. Details of the results on the timing and energy resolutions by using the multi-threshold method indicate that it is a promising approach for implementing digital PET data acquisition.

Cost-effectiveness thresholds: methods for setting and examples from around the world.

PubMed

Santos, André Soares; Guerra-Junior, Augusto Afonso; Godman, Brian; Morton, Alec; Ruas, Cristina Mariano

2018-06-01

Cost-effectiveness thresholds (CETs) are used to judge if an intervention represents sufficient value for money to merit adoption in healthcare systems. The study was motivated by the Brazilian context of HTA, where meetings are being conducted to decide on the definition of a threshold. Areas covered: An electronic search was conducted on Medline (via PubMed), Lilacs (via BVS) and ScienceDirect followed by a complementary search of references of included studies, Google Scholar and conference abstracts. Cost-effectiveness thresholds are usually calculated through three different approaches: the willingness-to-pay, representative of welfare economics; the precedent method, based on the value of an already funded technology; and the opportunity cost method, which links the threshold to the volume of health displaced. An explicit threshold has never been formally adopted in most places. Some countries have defined thresholds, with some flexibility to consider other factors. An implicit threshold could be determined by research of funded cases. Expert commentary: CETs have had an important role as a 'bridging concept' between the world of academic research and the 'real world' of healthcare prioritization. The definition of a cost-effectiveness threshold is paramount for the construction of a transparent and efficient Health Technology Assessment system.

Thresholds for Coral Bleaching: Are Synergistic Factors and Shifting Thresholds Changing the Landscape for Management? (Invited)

NASA Astrophysics Data System (ADS)

Eakin, C.; Donner, S. D.; Logan, C. A.; Gledhill, D. K.; Liu, G.; Heron, S. F.; Christensen, T.; Rauenzahn, J.; Morgan, J.; Parker, B. A.; Hoegh-Guldberg, O.; Skirving, W. J.; Strong, A. E.

2010-12-01

As carbon dioxide rises in the atmosphere, climate change and ocean acidification are modifying important physical and chemical parameters in the oceans with resulting impacts on coral reef ecosystems. Rising CO2 is warming the world’s oceans and causing corals to bleach, with both alarming frequency and severity. The frequent return of stressful temperatures has already resulted in major damage to many of the world’s coral reefs and is expected to continue in the foreseeable future. Warmer oceans also have contributed to a rise in coral infectious diseases. Both bleaching and infectious disease can result in coral mortality and threaten one of the most diverse ecosystems on Earth and the important ecosystem services they provide. Additionally, ocean acidification from rising CO2 is reducing the availability of carbonate ions needed by corals to build their skeletons and perhaps depressing the threshold for bleaching. While thresholds vary among species and locations, it is clear that corals around the world are already experiencing anomalous temperatures that are too high, too often, and that warming is exceeding the rate at which corals can adapt. This is despite a complex adaptive capacity that involves both the coral host and the zooxanthellae, including changes in the relative abundance of the latter in their coral hosts. The safe upper limit for atmospheric CO2 is probably somewhere below 350ppm, a level we passed decades ago, and for temperature is a sustained global temperature increase of less than 1.5°C above pre-industrial levels. How much can corals acclimate and/or adapt to the unprecedented fast changing environmental conditions? Any change in the threshold for coral bleaching as the result of acclimation and/or adaption may help corals to survive in the future but adaptation to one stress may be maladaptive to another. There also is evidence that ocean acidification and nutrient enrichment modify this threshold. What do shifting thresholds mean

Novel wavelet threshold denoising method in axle press-fit zone ultrasonic detection

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai

2017-02-01

Axles are important part of railway locomotives and vehicles. Periodic ultrasonic inspection of axles can effectively detect and monitor axle fatigue cracks. However, in the axle press-fit zone, the complex interface contact condition reduces the signal-noise ratio (SNR). Therefore, the probability of false positives and false negatives increases. In this work, a novel wavelet threshold function is created to remove noise and suppress press-fit interface echoes in axle ultrasonic defect detection. The novel wavelet threshold function with two variables is designed to ensure the precision of optimum searching process. Based on the positive correlation between the correlation coefficient and SNR and with the experiment phenomenon that the defect and the press-fit interface echo have different axle-circumferential correlation characteristics, a discrete optimum searching process for two undetermined variables in novel wavelet threshold function is conducted. The performance of the proposed method is assessed by comparing it with traditional threshold methods using real data. The statistic results of the amplitude and the peak SNR of defect echoes show that the proposed wavelet threshold denoising method not only maintains the amplitude of defect echoes but also has a higher peak SNR.

Threshold-free method for three-dimensional segmentation of organelles

NASA Astrophysics Data System (ADS)

Chan, Yee-Hung M.; Marshall, Wallace F.

2012-03-01

An ongoing challenge in the field of cell biology is to how to quantify the size and shape of organelles within cells. Automated image analysis methods often utilize thresholding for segmentation, but the calculated surface of objects depends sensitively on the exact threshold value chosen, and this problem is generally worse at the upper and lower zboundaries because of the anisotropy of the point spread function. We present here a threshold-independent method for extracting the three-dimensional surface of vacuoles in budding yeast whose limiting membranes are labeled with a fluorescent fusion protein. These organelles typically exist as a clustered set of 1-10 sphere-like compartments. Vacuole compartments and center points are identified manually within z-stacks taken using a spinning disk confocal microscope. A set of rays is defined originating from each center point and radiating outwards in random directions. Intensity profiles are calculated at coordinates along these rays, and intensity maxima are taken as the points the rays cross the limiting membrane of the vacuole. These points are then fit with a weighted sum of basis functions to define the surface of the vacuole, and then parameters such as volume and surface area are calculated. This method is able to determine the volume and surface area of spherical beads (0.96 to 2 micron diameter) with less than 10% error, and validation using model convolution methods produce similar results. Thus, this method provides an accurate, automated method for measuring the size and morphology of organelles and can be generalized to measure cells and other objects on biologically relevant length-scales.

Inexact adaptive Newton methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bertiger, W.I.; Kelsey, F.J.

1985-02-01

The Inexact Adaptive Newton method (IAN) is a modification of the Adaptive Implicit Method/sup 1/ (AIM) with improved Newton convergence. Both methods simplify the Jacobian at each time step by zeroing coefficients in regions where saturations are changing slowly. The methods differ in how the diagonal block terms are treated. On test problems with up to 3,000 cells, IAN consistently saves approximately 30% of the CPU time when compared to the fully implicit method. AIM shows similar savings on some problems, but takes as much CPU time as fully implicit on other test problems due to poor Newton convergence.

Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding.

PubMed

Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A

2016-08-12

With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

Watershed safety and quality control by safety threshold method

NASA Astrophysics Data System (ADS)

Da-Wei Tsai, David; Mengjung Chou, Caroline; Ramaraj, Rameshprabu; Liu, Wen-Cheng; Honglay Chen, Paris

2014-05-01

Taiwan was warned as one of the most dangerous countries by IPCC and the World Bank. In such an exceptional and perilous island, we would like to launch the strategic research of land-use management on the catastrophe prevention and environmental protection. This study used the watershed management by "Safety Threshold Method" to restore and to prevent the disasters and pollution on island. For the deluge prevention, this study applied the restoration strategy to reduce total runoff which was equilibrium to 59.4% of the infiltration each year. For the sediment management, safety threshold management could reduce the sediment below the equilibrium of the natural sediment cycle. In the water quality issues, the best strategies exhibited the significant total load reductions of 10% in carbon (BOD5), 15% in nitrogen (nitrate) and 9% in phosphorus (TP). We found out the water quality could meet the BOD target by the 50% peak reduction with management. All the simulations demonstrated the safety threshold method was helpful to control the loadings within the safe range of disasters and environmental quality. Moreover, from the historical data of whole island, the past deforestation policy and the mistake economic projects were the prime culprits. Consequently, this study showed a practical method to manage both the disasters and pollution in a watershed scale by the land-use management.

Searching for signposts: Adaptive planning thresholds in long-term water supply projections for the Western U.S.

NASA Astrophysics Data System (ADS)

Robinson, B.; Herman, J. D.

2017-12-01

Long-term water supply planning is challenged by highly uncertain streamflow projections across climate models and emissions scenarios. Recent studies have devised infrastructure and policy responses that can withstand or adapt to an ensemble of scenarios, particularly those outside the envelope of historical variability. An important aspect of this process is whether the proposed thresholds for adaptation (i.e., observations that trigger a response) truly represent a trend toward future change. Here we propose an approach to connect observations of annual mean streamflow with long-term projections by filtering GCM-based streamflow ensembles. Visualizations are developed to investigate whether observed changes in mean annual streamflow can be linked to projected changes in end-of-century mean and variance relative to the full ensemble. A key focus is identifying thresholds that point to significant long-term changes in the distribution of streamflow (+/- 20% or greater) as early as possible. The analysis is performed on 87 sites in the Western United States, using streamflow ensembles through 2100 from a recent study by the U.S. Bureau of Reclamation. Results focus on three primary questions: (1) how many years of observed data are needed to identify the most extreme scenarios, and by what year can they be identified? (2) are these features different between sites? and (3) using this analysis, do observed flows to date at each site point to significant long-term changes? This study addresses the challenge of severe uncertainty in long-term streamflow projections by identifying key thresholds that can be observed to support water supply planning.

Low-Threshold Active Teaching Methods for Mathematic Instruction

ERIC Educational Resources Information Center

Marotta, Sebastian M.; Hargis, Jace

2011-01-01

In this article, we present a large list of low-threshold active teaching methods categorized so the instructor can efficiently access and target the deployment of conceptually based lessons. The categories include teaching strategies for lecture on large and small class sizes; student action individually, in pairs, and groups; games; interaction…

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

Advances in Adaptive Control Methods

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2009-01-01

This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

PubMed Central

Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-01-01

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference. PMID:29186075

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

PubMed

Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-11-29

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

PubMed Central

Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A.

2016-01-01

With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications. PMID:27515908

Psychophysical Measurement of Rod and Cone Thresholds in Stargardt Disease with Full-Field Stimuli

PubMed Central

Collison, Frederick T.; Fishman, Gerald A.; McAnany, J. Jason; Zernant, Jana; Allikmets, Rando

2014-01-01

Purpose To investigate psychophysical thresholds in Stargardt disease with the full-field stimulus test (FST). Methods Visual acuity (VA), spectral-domain optical coherence tomography (SD-OCT), full-field electroretinogram (ERG), and FST measurements were made in one eye of 24 patients with Stargardt disease. Dark-adapted rod FST thresholds were measured with short-wavelength stimuli, and cone FST thresholds were obtained from the cone plateau phase of dark adaptation using long-wavelength stimuli. Correlation coefficients were calculated for FST thresholds versus macular thickness, VA and ERG amplitudes. Results Stargardt patient FST cone thresholds correlated significantly with VA, macular thickness, and ERG cone-response amplitudes (all P<0.01). The patients’ FST rod thresholds correlated with ERG rod-response amplitudes (P<0.01), but not macular thickness (P=0.05). All Stargardt disease patients with flecks confined to the macula and most of the patients with flecks extending outside of the macula had normal FST thresholds. All patients with extramacular atrophic changes had elevated FST cone thresholds and most had elevated FST rod thresholds. Conclusion FST rod and cone threshold elevation in Stargardt disease patients correlated well with measures of structure and function, as well as ophthalmoscopic retinal appearance. FST appears to be a useful tool for assessing rod and cone function in Stargardt disease. PMID:24695063

An adaptive embedded mesh procedure for leading-edge vortex flows

NASA Technical Reports Server (NTRS)

Powell, Kenneth G.; Beer, Michael A.; Law, Glenn W.

1989-01-01

A procedure for solving the conical Euler equations on an adaptively refined mesh is presented, along with a method for determining which cells to refine. The solution procedure is a central-difference cell-vertex scheme. The adaptation procedure is made up of a parameter on which the refinement decision is based, and a method for choosing a threshold value of the parameter. The refinement parameter is a measure of mesh-convergence, constructed by comparison of locally coarse- and fine-grid solutions. The threshold for the refinement parameter is based on the curvature of the curve relating the number of cells flagged for refinement to the value of the refinement threshold. Results for three test cases are presented. The test problem is that of a delta wing at angle of attack in a supersonic free-stream. The resulting vortices and shocks are captured efficiently by the adaptive code.

Constructing financial network based on PMFG and threshold method

NASA Astrophysics Data System (ADS)

Nie, Chun-Xiao; Song, Fu-Tie

2018-04-01

Based on planar maximally filtered graph (PMFG) and threshold method, we introduced a correlation-based network named PMFG-based threshold network (PTN). We studied the community structure of PTN and applied ISOMAP algorithm to represent PTN in low-dimensional Euclidean space. The results show that the community corresponds well to the cluster in the Euclidean space. Further, we studied the dynamics of the community structure and constructed the normalized mutual information (NMI) matrix. Based on the real data in the market, we found that the volatility of the market can lead to dramatic changes in the community structure, and the structure is more stable during the financial crisis.

Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.

PubMed

Jiang, Wen Jun; Wittek, Peter; Zhao, Li; Gao, Shi Chao

2014-01-01

Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. The new feature enables real-time adaptive waveform detection using an algorithm of linear time complexity. It can also recognize notches in the waveform and it is inherently robust to baseline drift. An implementation of the algorithm on Android is available for free download. We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.

Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists.

PubMed

Neal, Craig M; Hunter, Angus M; Brennan, Lorraine; O'Sullivan, Aifric; Hamilton, D Lee; De Vito, Giuseppe; Galloway, Stuart D R

2013-02-15

This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.

An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image

NASA Astrophysics Data System (ADS)

Yu, Zhijie; Yu, Hui; Wang, Chen-sheng

2014-11-01

Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.

Robust Optimal Adaptive Control Method with Large Adaptive Gain

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Twelve automated thresholding methods for segmentation of PET images: a phantom study.

PubMed

Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M

2012-06-21

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical (18)F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools.

Twelve automated thresholding methods for segmentation of PET images: a phantom study

NASA Astrophysics Data System (ADS)

Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M.

2012-06-01

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools.

Variable Threshold Method for Determining the Boundaries of Imaged Subvisible Particles.

PubMed

Cavicchi, Richard E; Collett, Cayla; Telikepalli, Srivalli; Hu, Zhishang; Carrier, Michael; Ripple, Dean C

2017-06-01

An accurate assessment of particle characteristics and concentrations in pharmaceutical products by flow imaging requires accurate particle sizing and morphological analysis. Analysis of images begins with the definition of particle boundaries. Commonly a single threshold defines the level for a pixel in the image to be included in the detection of particles, but depending on the threshold level, this results in either missing translucent particles or oversizing of less transparent particles due to the halos and gradients in intensity near the particle boundaries. We have developed an imaging analysis algorithm that sets the threshold for a particle based on the maximum gray value of the particle. We show that this results in tighter boundaries for particles with high contrast, while conserving the number of highly translucent particles detected. The method is implemented as a plugin for FIJI, an open-source image analysis software. The method is tested for calibration beads in water and glycerol/water solutions, a suspension of microfabricated rods, and stir-stressed aggregates made from IgG. The result is that appropriate thresholds are automatically set for solutions with a range of particle properties, and that improved boundaries will allow for more accurate sizing results and potentially improved particle classification studies. Published by Elsevier Inc.

Stable Extraction of Threshold Voltage Using Transconductance Change Method for CMOS Modeling, Simulation and Characterization

NASA Astrophysics Data System (ADS)

Choi, Woo Young; Woo, Dong-Soo; Choi, Byung Yong; Lee, Jong Duk; Park, Byung-Gook

2004-04-01

We proposed a stable extraction algorithm for threshold voltage using transconductance change method by optimizing node interval. With the algorithm, noise-free gm2 (=dgm/dVGS) profiles can be extracted within one-percent error, which leads to more physically-meaningful threshold voltage calculation by the transconductance change method. The extracted threshold voltage predicts the gate-to-source voltage at which the surface potential is within kT/q of φs=2φf+VSB. Our algorithm makes the transconductance change method more practical by overcoming noise problem. This threshold voltage extraction algorithm yields the threshold roll-off behavior of nanoscale metal oxide semiconductor field effect transistor (MOSFETs) accurately and makes it possible to calculate the surface potential φs at any other point on the drain-to-source current (IDS) versus gate-to-source voltage (VGS) curve. It will provide us with a useful analysis tool in the field of device modeling, simulation and characterization.

DARK ADAPTATION IN DINEUTES

PubMed Central

Clark, Leonard B.

1938-01-01

The level of dark adaptation of the whirligig beetle can be measured in terms of the threshold intensity calling forth a response. The course of dark adaptation was determined at levels of light adaptation of 6.5, 91.6, and 6100 foot-candles. All data can be fitted by the same curve. This indicates that dark adaptation follows parts of the same course irrespective of the level of light adaptation. The intensity of the adapting light determines the level at which dark adaptation will begin. The relation between log aI 0 (instantaneous threshold) and log of adapting light intensity is linear over the range studied. PMID:19873056

Verification of the tumor volume delineation method using a fixed threshold of peak standardized uptake value.

PubMed

Koyama, Kazuya; Mitsumoto, Takuya; Shiraishi, Takahiro; Tsuda, Keisuke; Nishiyama, Atsushi; Inoue, Kazumasa; Yoshikawa, Kyosan; Hatano, Kazuo; Kubota, Kazuo; Fukushi, Masahiro

2017-09-01

We aimed to determine the difference in tumor volume associated with the reconstruction model in positron-emission tomography (PET). To reduce the influence of the reconstruction model, we suggested a method to measure the tumor volume using the relative threshold method with a fixed threshold based on peak standardized uptake value (SUV peak ). The efficacy of our method was verified using 18 F-2-fluoro-2-deoxy-D-glucose PET/computed tomography images of 20 patients with lung cancer. The tumor volume was determined using the relative threshold method with a fixed threshold based on the SUV peak . The PET data were reconstructed using the ordered-subset expectation maximization (OSEM) model, the OSEM + time-of-flight (TOF) model, and the OSEM + TOF + point-spread function (PSF) model. The volume differences associated with the reconstruction algorithm (%VD) were compared. For comparison, the tumor volume was measured using the relative threshold method based on the maximum SUV (SUV max ). For the OSEM and TOF models, the mean %VD values were -0.06 ± 8.07 and -2.04 ± 4.23% for the fixed 40% threshold according to the SUV max and the SUV peak, respectively. The effect of our method in this case seemed to be minor. For the OSEM and PSF models, the mean %VD values were -20.41 ± 14.47 and -13.87 ± 6.59% for the fixed 40% threshold according to the SUV max and SUV peak , respectively. Our new method enabled the measurement of tumor volume with a fixed threshold and reduced the influence of the changes in tumor volume associated with the reconstruction model.

Objectivity and validity of EMG method in estimating anaerobic threshold.

PubMed

Kang, S-K; Kim, J; Kwon, M; Eom, H

2014-08-01

The purposes of this study were to verify and compare the performances of anaerobic threshold (AT) point estimates among different filtering intervals (9, 15, 20, 25, 30 s) and to investigate the interrelationships of AT point estimates obtained by ventilatory threshold (VT) and muscle fatigue thresholds using electromyographic (EMG) activity during incremental exercise on a cycle ergometer. 69 untrained male university students, yet pursuing regular exercise voluntarily participated in this study. The incremental exercise protocol was applied with a consistent stepwise increase in power output of 20 watts per minute until exhaustion. AT point was also estimated in the same manner using V-slope program with gas exchange parameters. In general, the estimated values of AT point-time computed by EMG method were more consistent across 5 filtering intervals and demonstrated higher correlations among themselves when compared with those values obtained by VT method. The results found in the present study suggest that the EMG signals could be used as an alternative or a new option in estimating AT point. Also the proposed computing procedure implemented in Matlab for the analysis of EMG signals appeared to be valid and reliable as it produced nearly identical values and high correlations with VT estimates. © Georg Thieme Verlag KG Stuttgart · New York.

Torque-onset determination: Unintended consequences of the threshold method.

PubMed

Dotan, Raffy; Jenkins, Glenn; O'Brien, Thomas D; Hansen, Steve; Falk, Bareket

2016-12-01

Compared with visual torque-onset-detection (TOD), threshold-based TOD produces onset bias, which increases with lower torques or rates of torque development (RTD). To compare the effects of differential TOD-bias on common contractile parameters in two torque-disparate groups. Fifteen boys and 12 men performed maximal, explosive, isometric knee-extensions. Torque and EMG were recorded for each contraction. Best contractions were selected by peak torque (MVC) and peak RTD. Visual-TOD-based torque-time traces, electromechanical delays (EMD), and times to peak RTD (tRTD) were compared with corresponding data derived from fixed 4-Nm- and relative 5%MVC-thresholds. The 5%MVC TOD-biases were similar for boys and men, but the corresponding 4-Nm-based biases were markedly different (40.3±14.1 vs. 18.4±7.1ms, respectively; p<0.001). Boys-men EMD differences were most affected, increasing from 5.0ms (visual) to 26.9ms (4Nm; p<0.01). Men's visually-based torque kinetics tended to be faster than the boys' (NS), but the 4-Nm-based kinetics erroneously depicted the boys as being much faster to any given %MVC (p<0.001). When comparing contractile properties of dissimilar groups, e.g., children vs. adults, threshold-based TOD methods can misrepresent reality and lead to erroneous conclusions. Relative-thresholds (e.g., 5% MVC) still introduce error, but group-comparisons are not confounded. Copyright © 2016 Elsevier Ltd. All rights reserved.

THRESHOLD LOGIC.

DTIC Science & Technology

synthesis procedures; a ’best’ method is definitely established. (2) ’Symmetry Types for Threshold Logic’ is a tutorial expositon including a careful...development of the Goto-Takahasi self-dual type ideas. (3) ’Best Threshold Gate Decisions’ reports a comparison, on the 2470 7-argument threshold ...interpretation is shown best. (4) ’ Threshold Gate Networks’ reviews the previously discussed 2-algorithm in geometric terms, describes our FORTRAN

The Limits to Adaptation; A Systems Approach

EPA Science Inventory

The Limits to Adaptation: A Systems Approach. The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering...

Reliability and validity of a brief method to assess nociceptive flexion reflex (NFR) threshold.

PubMed

Rhudy, Jamie L; France, Christopher R

2011-07-01

The nociceptive flexion reflex (NFR) is a physiological tool to study spinal nociception. However, NFR assessment can take several minutes and expose participants to repeated suprathreshold stimulations. The 4 studies reported here assessed the reliability and validity of a brief method to assess NFR threshold that uses a single ascending series of stimulations (Peak 1 NFR), by comparing it to a well-validated method that uses 3 ascending/descending staircases of stimulations (Staircase NFR). Correlations between the NFR definitions were high, were on par with test-retest correlations of Staircase NFR, and were not affected by participant sex or chronic pain status. Results also indicated the test-retest reliabilities for the 2 definitions were similar. Using larger stimulus increments (4 mAs) to assess Peak 1 NFR tended to result in higher NFR threshold estimates than using the Staircase NFR definition, whereas smaller stimulus increments (2 mAs) tended to result in lower NFR threshold estimates than the Staircase NFR definition. Neither NFR definition was correlated with anxiety, pain catastrophizing, or anxiety sensitivity. In sum, a single ascending series of electrical stimulations results in a reliable and valid estimate of NFR threshold. However, caution may be warranted when comparing NFR thresholds across studies that differ in the ascending stimulus increments. This brief method to assess NFR threshold is reliable and valid; therefore, it should be useful to clinical pain researchers interested in quickly assessing inter- and intra-individual differences in spinal nociceptive processes. Copyright © 2011 American Pain Society. Published by Elsevier Inc. All rights reserved.

Threshold Values for Identification of Contamination Predicted by Reduced-Order Models

DOE PAGES

Last, George V.; Murray, Christopher J.; Bott, Yi-Ju; ...

2014-12-31

The U.S. Department of Energy’s (DOE’s) National Risk Assessment Partnership (NRAP) Project is developing reduced-order models to evaluate potential impacts on underground sources of drinking water (USDWs) if CO2 or brine leaks from deep CO2 storage reservoirs. Threshold values, below which there would be no predicted impacts, were determined for portions of two aquifer systems. These threshold values were calculated using an interwell approach for determining background groundwater concentrations that is an adaptation of methods described in the U.S. Environmental Protection Agency’s Unified Guidance for Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities.

Prefixed-threshold real-time selection method in free-space quantum key distribution

NASA Astrophysics Data System (ADS)

Wang, Wenyuan; Xu, Feihu; Lo, Hoi-Kwong

2018-03-01

Free-space quantum key distribution allows two parties to share a random key with unconditional security, between ground stations, between mobile platforms, and even in satellite-ground quantum communications. Atmospheric turbulence causes fluctuations in transmittance, which further affect the quantum bit error rate and the secure key rate. Previous postselection methods to combat atmospheric turbulence require a threshold value determined after all quantum transmission. In contrast, here we propose a method where we predetermine the optimal threshold value even before quantum transmission. Therefore, the receiver can discard useless data immediately, thus greatly reducing data storage requirements and computing resources. Furthermore, our method can be applied to a variety of protocols, including, for example, not only single-photon BB84 but also asymptotic and finite-size decoy-state BB84, which can greatly increase its practicality.

Assessing Adaptive Instructional Design Tools and Methods in ADAPT[IT].

ERIC Educational Resources Information Center

Eseryel, Deniz; Spector, J. Michael

ADAPT[IT] (Advanced Design Approach for Personalized Training - Interactive Tools) is a European project within the Information Society Technologies program that is providing design methods and tools to guide a training designer according to the latest cognitive science and standardization principles. ADAPT[IT] addresses users in two significantly…

Definition of temperature thresholds: the example of the French heat wave warning system.

PubMed

Pascal, Mathilde; Wagner, Vérène; Le Tertre, Alain; Laaidi, Karine; Honoré, Cyrille; Bénichou, Françoise; Beaudeau, Pascal

2013-01-01

Heat-related deaths should be somewhat preventable. In France, some prevention measures are activated when minimum and maximum temperatures averaged over three days reach city-specific thresholds. The current thresholds were computed based on a descriptive analysis of past heat waves and on local expert judgement. We tested whether a different method would confirm these thresholds. The study was set in the six cities of Paris, Lyon, Marseille, Nantes, Strasbourg and Limoges between 1973 and 2003. For each city, we estimated the excess in mortality associated with different temperature thresholds, using a generalised additive model, controlling for long-time trends, seasons and days of the week. These models were used to compute the mortality predicted by different percentiles of temperatures. The thresholds were chosen as the percentiles associated with a significant excess mortality. In all cities, there was a good correlation between current thresholds and the thresholds derived from the models, with 0°C to 3°C differences for averaged maximum temperatures. Both set of thresholds were able to anticipate the main periods of excess mortality during the summers of 1973 to 2003. A simple method relying on descriptive analysis and expert judgement is sufficient to define protective temperature thresholds and to prevent heat wave mortality. As temperatures are increasing along with the climate change and adaptation is ongoing, more research is required to understand if and when thresholds should be modified.

The absolute threshold of cone vision

PubMed Central

Koeing, Darran; Hofer, Heidi

2013-01-01

We report measurements of the absolute threshold of cone vision, which has been previously underestimated due to sub-optimal conditions or overly strict subjective response criteria. We avoided these limitations by using optimized stimuli and experimental conditions while having subjects respond within a rating scale framework. Small (1′ fwhm), brief (34 msec), monochromatic (550 nm) stimuli were foveally presented at multiple intensities in dark-adapted retina for 5 subjects. For comparison, 4 subjects underwent similar testing with rod-optimized stimuli. Cone absolute threshold, that is, the minimum light energy for which subjects were just able to detect a visual stimulus with any response criterion, was 203 ± 38 photons at the cornea, ∼0.47 log units lower than previously reported. Two-alternative forced-choice measurements in a subset of subjects yielded consistent results. Cone thresholds were less responsive to criterion changes than rod thresholds, suggesting a limit to the stimulus information recoverable from the cone mosaic in addition to the limit imposed by Poisson noise. Results were consistent with expectations for detection in the face of stimulus uncertainty. We discuss implications of these findings for modeling the first stages of human cone vision and interpreting psychophysical data acquired with adaptive optics at the spatial scale of the receptor mosaic. PMID:21270115

A de-noising method using the improved wavelet threshold function based on noise variance estimation

NASA Astrophysics Data System (ADS)

Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

2018-01-01

The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation

PubMed Central

Zhang, Jie; Fan, Shangang; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki

2017-01-01

Both L1/2 and L2/3 are two typical non-convex regularizations of Lp (0thresholding algorithm and then proposes a sparse adaptive iterative-weighted Lp thresholding algorithm (SAITA). Moreover, a simple yet effective regularization parameter is proposed to weight each sub-dictionary-based Lp regularizer. Simulation results have shown that the proposed SAITA not only performs better than the corresponding L1 algorithms but can also obtain a better recovery performance and achieve faster convergence than the conventional single-dictionary sparse transform-based Lp case. Moreover, we conduct some applications about sparse image recovery and obtain good results by comparison with relative work. PMID:29244777

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation.

PubMed

Li, Yunyi; Zhang, Jie; Fan, Shangang; Yang, Jie; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki; Gui, Guan

2017-12-15

Both L 1/2 and L 2/3 are two typical non-convex regularizations of L p (0thresholding algorithm and then proposes a sparse adaptive iterative-weighted L p thresholding algorithm (SAITA). Moreover, a simple yet effective regularization parameter is proposed to weight each sub-dictionary-based L p regularizer. Simulation results have shown that the proposed SAITA not only performs better than the corresponding L₁ algorithms but can also obtain a better recovery performance and achieve faster convergence than the conventional single-dictionary sparse transform-based L p case. Moreover, we conduct some applications about sparse image recovery and obtain good results by comparison with relative work.

Incorporating adaptive responses into future projections of coral bleaching.

PubMed

Logan, Cheryl A; Dunne, John P; Eakin, C Mark; Donner, Simon D

2014-01-01

Climate warming threatens to increase mass coral bleaching events, and several studies have projected the demise of tropical coral reefs this century. However, recent evidence indicates corals may be able to respond to thermal stress though adaptive processes (e.g., genetic adaptation, acclimatization, and symbiont shuffling). How these mechanisms might influence warming-induced bleaching remains largely unknown. This study compared how different adaptive processes could affect coral bleaching projections. We used the latest bias-corrected global sea surface temperature (SST) output from the NOAA/GFDL Earth System Model 2 (ESM2M) for the preindustrial period through 2100 to project coral bleaching trajectories. Initial results showed that, in the absence of adaptive processes, application of a preindustrial climatology to the NOAA Coral Reef Watch bleaching prediction method overpredicts the present-day bleaching frequency. This suggests that corals may have already responded adaptively to some warming over the industrial period. We then modified the prediction method so that the bleaching threshold either permanently increased in response to thermal history (e.g., simulating directional genetic selection) or temporarily increased for 2-10 years in response to a bleaching event (e.g., simulating symbiont shuffling). A bleaching threshold that changes relative to the preceding 60 years of thermal history reduced the frequency of mass bleaching events by 20-80% compared with the 'no adaptive response' prediction model by 2100, depending on the emissions scenario. When both types of adaptive responses were applied, up to 14% more reef cells avoided high-frequency bleaching by 2100. However, temporary increases in bleaching thresholds alone only delayed the occurrence of high-frequency bleaching by ca. 10 years in all but the lowest emissions scenario. Future research should test the rate and limit of different adaptive responses for coral species across latitudes and

Accelerated Adaptive Integration Method

PubMed Central

2015-01-01

Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors. PMID:24780083

Vibratory Adaptation of Cutaneous Mechanoreceptive Afferents

PubMed Central

Bensmaïa, S. J.; Leung, Y. Y.; Hsiao, S. S.; Johnson, K. O.

2007-01-01

The objective of this study was to investigate the effects of extended suprathreshold vibratory stimulation on the sensitivity of slowly adapting type 1 (SA1), rapidly adapting (RA), and Pacinian (PC) afferents. To that end, an algorithm was developed to track afferent absolute (I0) and entrainment (I1) thresholds as they change over time. We recorded afferent responses to periliminal vibratory test stimuli, which were interleaved with intense vibratory conditioning stimuli during the adaptation period of each experimental run. From these measurements, the algorithm allowed us to infer changes in the afferents’ sensitivity. We investigated the stimulus parameters that affect adaptation by assessing the degree to which adaptation depends on the amplitude and frequency of the adapting stimulus. For all three afferent types, I0 and I1 increased with increasing adaptation frequency and amplitude. The degree of adaptation seems to be independent of the firing rate evoked in the afferent by the conditioning stimulus. In the analysis, we distinguished between additive adaptation (in which I0 and I1 shift equally) and multiplicative effects (in which the ratio I1/I0 remains constant). RA threshold shifts are almost perfectly additive. SA1 threshold shifts are close to additive and far from multiplicative (I1 threshold shifts are twice the shifts). PC shifts are more difficult to classify. We used an I0 integrate-and-fire model to study the possible neural mechanisms. A change in transducer gain predicts a multiplicative change in I0 and I1 and is thus ruled out as a mechanism underlying SA1 and RA adaptation. A change in the resting action potential threshold predicts equal, additive change in I0 and I1 and thus accounts well for RA adaptation. A change in the degree of refractoriness during the relative refractory period predicts an additional change in I1 such as that observed for SA1 fibers. We infer that adaptation is caused by an increase in spiking thresholds

Adaptive threshold hunting for the effects of transcranial direct current stimulation on primary motor cortex inhibition.

PubMed

Mooney, Ronan A; Cirillo, John; Byblow, Winston D

2018-06-01

Primary motor cortex excitability can be modulated by anodal and cathodal transcranial direct current stimulation (tDCS). These neuromodulatory effects may, in part, be dependent on modulation within gamma-aminobutyric acid (GABA)-mediated inhibitory networks. GABAergic function can be quantified non-invasively using adaptive threshold hunting paired-pulse transcranial magnetic stimulation (TMS). The previous studies have used TMS with posterior-anterior (PA) induced current to assess tDCS effects on inhibition. However, TMS with anterior-posterior (AP) induced current in the brain provides a more robust measure of GABA-mediated inhibition. The aim of the present study was to assess the modulation of corticomotor excitability and inhibition after anodal and cathodal tDCS using TMS with PA- and AP-induced current. In 16 young adults (26 ± 1 years), we investigated the response to anodal, cathodal, and sham tDCS in a repeated-measures double-blinded crossover design. Adaptive threshold hunting paired-pulse TMS with PA- and AP-induced current was used to examine separate interneuronal populations within M1 and their influence on corticomotor excitability and short- and long-interval inhibition (SICI and LICI) for up to 60 min after tDCS. Unexpectedly, cathodal tDCS increased corticomotor excitability assessed with AP (P = 0.047) but not PA stimulation (P = 0.74). SICI AP was reduced after anodal tDCS compared with sham (P = 0.040). Pearson's correlations indicated that SICI AP and LICI AP modulation was associated with corticomotor excitability after anodal (P = 0.027) and cathodal tDCS (P = 0.042). The after-effects of tDCS on corticomotor excitability may depend on the direction of the TMS-induced current used to make assessments, and on modulation within GABA-mediated inhibitory circuits.

Thresholds for the perception of whole-body linear sinusoidal motion in the horizontal plane

NASA Technical Reports Server (NTRS)

Mah, Robert W.; Young, Laurence R.; Steele, Charles R.; Schubert, Earl D.

1989-01-01

An improved linear sled has been developed to provide precise motion stimuli without generating perceptible extraneous motion cues (a noiseless environment). A modified adaptive forced-choice method was employed to determine perceptual thresholds to whole-body linear sinusoidal motion in 25 subjects. Thresholds for the detection of movement in the horizontal plane were found to be lower than those reported previously. At frequencies of 0.2 to 0.5 Hz, thresholds were shown to be independent of frequency, while at frequencies of 1.0 to 3.0 Hz, thresholds showed a decreasing sensitivity with increasing frequency, indicating that the perceptual process is not sensitive to the rate change of acceleration of the motion stimulus. The results suggest that the perception of motion behaves as an integrating accelerometer with a bandwidth of at least 3 Hz.

Photoacoustic signals denoising of the glucose aqueous solutions using an improved wavelet threshold method

NASA Astrophysics Data System (ADS)

Ren, Zhong; Liu, Guodong; Xiong, Zhihua

2016-10-01

The photoacoustic signals denoising of glucose is one of most important steps in the quality identification of the fruit because the real-time photoacoustic singals of glucose are easily interfered by all kinds of noises. To remove the noises and some useless information, an improved wavelet threshld function were proposed. Compared with the traditional wavelet hard and soft threshold functions, the improved wavelet threshold function can overcome the pseudo-oscillation effect of the denoised photoacoustic signals due to the continuity of the improved wavelet threshold function, and the error between the denoised signals and the original signals can be decreased. To validate the feasibility of the improved wavelet threshold function denoising, the denoising simulation experiments based on MATLAB programmimg were performed. In the simulation experiments, the standard test signal was used, and three different denoising methods were used and compared with the improved wavelet threshold function. The signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) values were used to evaluate the performance of the improved wavelet threshold function denoising. The experimental results demonstrate that the SNR value of the improved wavelet threshold function is largest and the RMSE value is lest, which fully verifies that the improved wavelet threshold function denoising is feasible. Finally, the improved wavelet threshold function denoising was used to remove the noises of the photoacoustic signals of the glucose solutions. The denoising effect is also very good. Therefore, the improved wavelet threshold function denoising proposed by this paper, has a potential value in the field of denoising for the photoacoustic singals.

The Limits to Adaptation: A Systems Approach

EPA Science Inventory

The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering parameters), resource constraints (expressed th...

Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

NASA Astrophysics Data System (ADS)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.

Adaptive Finite Element Methods for Continuum Damage Modeling

NASA Technical Reports Server (NTRS)

Min, J. B.; Tworzydlo, W. W.; Xiques, K. E.

1995-01-01

The paper presents an application of adaptive finite element methods to the modeling of low-cycle continuum damage and life prediction of high-temperature components. The major objective is to provide automated and accurate modeling of damaged zones through adaptive mesh refinement and adaptive time-stepping methods. The damage modeling methodology is implemented in an usual way by embedding damage evolution in the transient nonlinear solution of elasto-viscoplastic deformation problems. This nonlinear boundary-value problem is discretized by adaptive finite element methods. The automated h-adaptive mesh refinements are driven by error indicators, based on selected principal variables in the problem (stresses, non-elastic strains, damage, etc.). In the time domain, adaptive time-stepping is used, combined with a predictor-corrector time marching algorithm. The time selection is controlled by required time accuracy. In order to take into account strong temperature dependency of material parameters, the nonlinear structural solution a coupled with thermal analyses (one-way coupling). Several test examples illustrate the importance and benefits of adaptive mesh refinements in accurate prediction of damage levels and failure time.

Impairment of retinal increment thresholds in Huntington's disease.

PubMed

Paulus, W; Schwarz, G; Werner, A; Lange, H; Bayer, A; Hofschuster, M; Müller, N; Zrenner, E

1993-10-01

We have investigated detection thresholds for a foveal blue test light using a Maxwellian view system in 61 normal subjects, 19 patients with Huntington's chorea, 14 patients with Tourette's syndrome, and 20 patients with schizophrenia. Ten measurements were made: The blue test light (1 degree diameter, 500 msec duration) was presented either superimposed on a yellow adaptation field (5 degree diameter) or 500 msec after switching off this field (transient tritanopia effect). In both cases five different background intensities were presented. The only abnormality found was in patients with Huntington's chorea. During adaptation these patients' thresholds are significantly higher than normal (p < 0.005). No change was found in the transient tritanopia effect. Huntington's disease causes degeneration of several different transmitter systems in the brain. Increment threshold testing allows for noninvasive investigation of patients and confirms the involvement of the retina in the degenerative process in Huntington's chorea.

Variable-Threshold Threshold Elements,

DTIC Science & Technology

A threshold element is a mathematical model of certain types of logic gates and of a biological neuron. Much work has been done on the subject of... threshold elements with fixed thresholds; this study concerns itself with elements in which the threshold may be varied, variable- threshold threshold ...elements. Physical realizations include resistor-transistor elements, in which the threshold is simply a voltage. Variation of the threshold causes the

Thermal bistability-based method for real-time optimization of ultralow-threshold whispering gallery mode microlasers.

PubMed

Lin, Guoping; Candela, Y; Tillement, O; Cai, Zhiping; Lefèvre-Seguin, V; Hare, J

2012-12-15

A method based on thermal bistability for ultralow-threshold microlaser optimization is demonstrated. When sweeping the pump laser frequency across a pump resonance, the dynamic thermal bistability slows down the power variation. The resulting line shape modification enables a real-time monitoring of the laser characteristic. We demonstrate this method for a functionalized microsphere exhibiting a submicrowatt laser threshold. This approach is confirmed by comparing the results with a step-by-step recording in quasi-static thermal conditions.

Ventilatory thresholds determined from HRV: comparison of 2 methods in obese adolescents.

PubMed

Quinart, S; Mourot, L; Nègre, V; Simon-Rigaud, M-L; Nicolet-Guénat, M; Bertrand, A-M; Meneveau, N; Mougin, F

2014-03-01

The development of personalised training programmes is crucial in the management of obesity. We evaluated the ability of 2 heart rate variability analyses to determine ventilatory thresholds (VT) in obese adolescents. 20 adolescents (mean age 14.3±1.6 years and body mass index z-score 4.2±0.1) performed an incremental test to exhaustion before and after a 9-month multidisciplinary management programme. The first (VT1) and second (VT2) ventilatory thresholds were identified by the reference method (gas exchanges). We recorded RR intervals to estimate VT1 and VT2 from heart rate variability using time-domain analysis and time-varying spectral-domain analysis. The coefficient correlations between thresholds were higher with spectral-domain analysis compared to time-domain analysis: Heart rate at VT1: r=0.91 vs. =0.66 and VT2: r=0.91 vs. =0.66; power at VT1: r=0.91 vs. =0.74 and VT2: r=0.93 vs. =0.78; spectral-domain vs. time-domain analysis respectively). No systematic bias in heart rate at VT1 and VT2 with standard deviations <6 bpm were found, confirming that spectral-domain analysis could replace the reference method for the detection of ventilatory thresholds. Furthermore, this technique is sensitive to rehabilitation and re-training, which underlines its utility in clinical practice. This inexpensive and non-invasive tool is promising for prescribing physical activity programs in obese adolescents. © Georg Thieme Verlag KG Stuttgart · New York.

Modeling Adaptive Educational Methods with IMS Learning Design

ERIC Educational Resources Information Center

Specht, Marcus; Burgos, Daniel

2007-01-01

The paper describes a classification system for adaptive methods developed in the area of adaptive educational hypermedia based on four dimensions: What components of the educational system are adapted? To what features of the user and the current context does the system adapt? Why does the system adapt? How does the system get the necessary…

High-resolution audiometry: an automated method for hearing threshold acquisition with quality control.

PubMed

Bian, Lin

2012-01-01

In clinical practice, hearing thresholds are measured at only five to six frequencies at octave intervals. Thus, the audiometric configuration cannot closely reflect the actual status of the auditory structures. In addition, differential diagnosis requires quantitative comparison of behavioral thresholds with physiological measures, such as otoacoustic emissions (OAEs) that are usually measured in higher resolution. The purpose of this research was to develop a method to improve the frequency resolution of the audiogram. A repeated-measure design was used in the study to evaluate the reliability of the threshold measurements. A total of 16 participants with clinically normal hearing and mild hearing loss were recruited from a population of university students. No intervention was involved in the study. Custom developed system and software were used for threshold acquisition with quality control (QC). With real-ear calibration and monitoring of test signals, the system provided accurate and individualized measure of hearing thresholds that were determined by an analysis based on signal detection theory (SDT). The reliability of the threshold measure was assessed by correlation and differences between the repeated measures. The audiometric configurations were diverse and unique to each individual ear. The accuracy, within-subject reliability, and between-test repeatability are relatively high. With QC, the high-resolution audiograms can be reliably and accurately measured. Hearing thresholds measured as ear canal sound pressures with higher frequency resolution can provide more customized hearing-aid fitting. The test system may be integrated with other physiological measures, such as OAEs, into a comprehensive evaluative tool. American Academy of Audiology.

A complementary graphical method for reducing and analyzing large data sets. Case studies demonstrating thresholds setting and selection.

PubMed

Jing, X; Cimino, J J

2014-01-01

Graphical displays can make data more understandable; however, large graphs can challenge human comprehension. We have previously described a filtering method to provide high-level summary views of large data sets. In this paper we demonstrate our method for setting and selecting thresholds to limit graph size while retaining important information by applying it to large single and paired data sets, taken from patient and bibliographic databases. Four case studies are used to illustrate our method. The data are either patient discharge diagnoses (coded using the International Classification of Diseases, Clinical Modifications [ICD9-CM]) or Medline citations (coded using the Medical Subject Headings [MeSH]). We use combinations of different thresholds to obtain filtered graphs for detailed analysis. The thresholds setting and selection, such as thresholds for node counts, class counts, ratio values, p values (for diff data sets), and percentiles of selected class count thresholds, are demonstrated with details in case studies. The main steps include: data preparation, data manipulation, computation, and threshold selection and visualization. We also describe the data models for different types of thresholds and the considerations for thresholds selection. The filtered graphs are 1%-3% of the size of the original graphs. For our case studies, the graphs provide 1) the most heavily used ICD9-CM codes, 2) the codes with most patients in a research hospital in 2011, 3) a profile of publications on "heavily represented topics" in MEDLINE in 2011, and 4) validated knowledge about adverse effects of the medication of rosiglitazone and new interesting areas in the ICD9-CM hierarchy associated with patients taking the medication of pioglitazone. Our filtering method reduces large graphs to a manageable size by removing relatively unimportant nodes. The graphical method provides summary views based on computation of usage frequency and semantic context of hierarchical

Laying the Groundwork for NCLEX Success: An Exploration of Adaptive Quizzing as an Examination Preparation Method.

PubMed

Cox-Davenport, Rebecca A; Phelan, Julia C

2015-05-01

First-time NCLEX-RN pass rates are an important indicator of nursing school success and quality. Nursing schools use different methods to anticipate NCLEX outcomes and help prevent student failure and possible threat to accreditation. This study evaluated the impact of a shift in NCLEX preparation policy at a BSN program in the southeast United States. The policy shifted from the use of predictor score thresholds to determine graduation eligibility to a more proactive remediation strategy involving adaptive quizzing. A descriptive correlational design evaluated the impact of an adaptive quizzing system designed to give students ongoing active practice and feedback and explored the relationship between predictor examinations and NCLEX success. Data from student usage of the system as well as scores on predictor tests were collected for three student cohorts. Results revealed a positive correlation between adaptive quizzing system usage and content mastery. Two of the 69 students in the sample did not pass the NCLEX. With so few students failing the NCLEX, predictability of any course variables could not be determined. The power of predictor examinations to predict NCLEX failure could also not be supported. The most consistent factor among students, however, was their content mastery level within the adaptive quizzing system. Implications of these findings are discussed.

The method of constant stimuli is inefficient

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Fitzhugh, Andrew

1990-01-01

Simpson (1988) has argued that the method of constant stimuli is as efficient as adaptive methods of threshold estimation and has supported this claim with simulations. It is shown that Simpson's simulations are not a reasonable model of the experimental process and that more plausible simulations confirm that adaptive methods are much more efficient that the method of constant stimuli.

Adaptive 4d Psi-Based Change Detection

NASA Astrophysics Data System (ADS)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

Large Covariance Estimation by Thresholding Principal Orthogonal Complements.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2013-09-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.

Adaptive mesh strategies for the spectral element method

NASA Technical Reports Server (NTRS)

Mavriplis, Catherine

1992-01-01

An adaptive spectral method was developed for the efficient solution of time dependent partial differential equations. Adaptive mesh strategies that include resolution refinement and coarsening by three different methods are illustrated on solutions to the 1-D viscous Burger equation and the 2-D Navier-Stokes equations for driven flow in a cavity. Sharp gradients, singularities, and regions of poor resolution are resolved optimally as they develop in time using error estimators which indicate the choice of refinement to be used. The adaptive formulation presents significant increases in efficiency, flexibility, and general capabilities for high order spectral methods.

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames

Can adaptive threshold-based metabolic tumor volume (MTV) and lean body mass corrected standard uptake value (SUL) predict prognosis in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy?

PubMed

Akagunduz, Ozlem Ozkaya; Savas, Recep; Yalman, Deniz; Kocacelebi, Kenan; Esassolak, Mustafa

2015-11-01

To evaluate the predictive value of adaptive threshold-based metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax) and maximum lean body mass corrected SUV (SULmax) measured on pretreatment positron emission tomography and computed tomography (PET/CT) imaging in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy. Pretreatment PET/CT of the 62 patients with locally advanced head and neck cancer who were treated consecutively between May 2010 and February 2013 were reviewed retrospectively. The maximum FDG uptake of the primary tumor was defined according to SUVmax and SULmax. Multiple threshold levels between 60% and 10% of the SUVmax and SULmax were tested with intervals of 5% to 10% in order to define the most suitable threshold value for the metabolic activity of each patient's tumor (adaptive threshold). MTV was calculated according to this value. We evaluated the relationship of mean values of MTV, SUVmax and SULmax with treatment response, local recurrence, distant metastasis and disease-related death. Receiver-operating characteristic (ROC) curve analysis was done to obtain optimal predictive cut-off values for MTV and SULmax which were found to have a predictive value. Local recurrence-free (LRFS), disease-free (DFS) and overall survival (OS) were examined according to these cut-offs. Forty six patients had complete response, 15 had partial response, and 1 had stable disease 6 weeks after the completion of treatment. Median follow-up of the entire cohort was 18 months. Of 46 complete responders 10 had local recurrence, and of 16 partial or no responders 10 had local progression. Eighteen patients died. Adaptive threshold-based MTV had significant predictive value for treatment response (p=0.011), local recurrence/progression (p=0.050), and disease-related death (p=0.024). SULmax had a predictive value for local recurrence/progression (p=0.030). ROC curves analysis revealed a cut-off value of 14.00 mL for

Methods of scaling threshold color difference using printed samples

NASA Astrophysics Data System (ADS)

Huang, Min; Cui, Guihua; Liu, Haoxue; Luo, M. Ronnier

2012-01-01

A series of printed samples on substrate of semi-gloss paper and with the magnitude of threshold color difference were prepared for scaling the visual color difference and to evaluate the performance of different method. The probabilities of perceptibly was used to normalized to Z-score and different color differences were scaled to the Z-score. The visual color difference was got, and checked with the STRESS factor. The results indicated that only the scales have been changed but the relative scales between pairs in the data are preserved.

Track and vertex reconstruction: From classical to adaptive methods

NASA Astrophysics Data System (ADS)

Strandlie, Are; Frühwirth, Rudolf

2010-04-01

This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.

Differentially Private Histogram Publication For Dynamic Datasets: An Adaptive Sampling Approach

PubMed Central

Li, Haoran; Jiang, Xiaoqian; Xiong, Li; Liu, Jinfei

2016-01-01

Differential privacy has recently become a de facto standard for private statistical data release. Many algorithms have been proposed to generate differentially private histograms or synthetic data. However, most of them focus on “one-time” release of a static dataset and do not adequately address the increasing need of releasing series of dynamic datasets in real time. A straightforward application of existing histogram methods on each snapshot of such dynamic datasets will incur high accumulated error due to the composibility of differential privacy and correlations or overlapping users between the snapshots. In this paper, we address the problem of releasing series of dynamic datasets in real time with differential privacy, using a novel adaptive distance-based sampling approach. Our first method, DSFT, uses a fixed distance threshold and releases a differentially private histogram only when the current snapshot is sufficiently different from the previous one, i.e., with a distance greater than a predefined threshold. Our second method, DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by a feedback control mechanism to capture the data dynamics. Extensive experiments on real and synthetic datasets demonstrate that our approach achieves better utility than baseline methods and existing state-of-the-art methods. PMID:26973795

Critical review and hydrologic application of threshold detection methods for the generalized Pareto (GP) distribution

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto

2016-04-01

Estimation of extreme rainfall from data constitutes one of the most important issues in statistical hydrology, as it is associated with the design of hydraulic structures and flood water management. To that extent, based on asymptotic arguments from Extreme Excess (EE) theory, several studies have focused on developing new, or improving existing methods to fit a generalized Pareto (GP) distribution model to rainfall excesses above a properly selected threshold u. The latter is generally determined using various approaches, such as non-parametric methods that are intended to locate the changing point between extreme and non-extreme regions of the data, graphical methods where one studies the dependence of GP distribution parameters (or related metrics) on the threshold level u, and Goodness of Fit (GoF) metrics that, for a certain level of significance, locate the lowest threshold u that a GP distribution model is applicable. In this work, we review representative methods for GP threshold detection, discuss fundamental differences in their theoretical bases, and apply them to 1714 daily rainfall records from the NOAA-NCDC open-access database, with more than 110 years of data. We find that non-parametric methods that are intended to locate the changing point between extreme and non-extreme regions of the data are generally not reliable, while methods that are based on asymptotic properties of the upper distribution tail lead to unrealistically high threshold and shape parameter estimates. The latter is justified by theoretical arguments, and it is especially the case in rainfall applications, where the shape parameter of the GP distribution is low; i.e. on the order of 0.1 ÷ 0.2. Better performance is demonstrated by graphical methods and GoF metrics that rely on pre-asymptotic properties of the GP distribution. For daily rainfall, we find that GP threshold estimates range between 2÷12 mm/d with a mean value of 6.5 mm/d, while the existence of quantization in the

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

PubMed Central

Yang, Yingbao; Li, Xiaolong; Pan, Xin; Zhang, Yong; Cao, Chen

2017-01-01

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. PMID:28368301

Adaptive [theta]-methods for pricing American options

NASA Astrophysics Data System (ADS)

Khaliq, Abdul Q. M.; Voss, David A.; Kazmi, Kamran

2008-12-01

We develop adaptive [theta]-methods for solving the Black-Scholes PDE for American options. By adding a small, continuous term, the Black-Scholes PDE becomes an advection-diffusion-reaction equation on a fixed spatial domain. Standard implementation of [theta]-methods would require a Newton-type iterative procedure at each time step thereby increasing the computational complexity of the methods. Our linearly implicit approach avoids such complications. We establish a general framework under which [theta]-methods satisfy a discrete version of the positivity constraint characteristic of American options, and numerically demonstrate the sensitivity of the constraint. The positivity results are established for the single-asset and independent two-asset models. In addition, we have incorporated and analyzed an adaptive time-step control strategy to increase the computational efficiency. Numerical experiments are presented for one- and two-asset American options, using adaptive exponential splitting for two-asset problems. The approach is compared with an iterative solution of the two-asset problem in terms of computational efficiency.

Evidence Accumulator or Decision Threshold – Which Cortical Mechanism are We Observing?

PubMed Central

Simen, Patrick

2012-01-01

Most psychological models of perceptual decision making are of the accumulation-to-threshold variety. The neural basis of accumulation in parietal and prefrontal cortex is therefore a topic of great interest in neuroscience. In contrast, threshold mechanisms have received less attention, and their neural basis has usually been sought in subcortical structures. Here I analyze a model of a decision threshold that can be implemented in the same cortical areas as evidence accumulators, and whose behavior bears on two open questions in decision neuroscience: (1) When ramping activity is observed in a brain region during decision making, does it reflect evidence accumulation? (2) Are changes in speed-accuracy tradeoffs and response biases more likely to be achieved by changes in thresholds, or in accumulation rates and starting points? The analysis suggests that task-modulated ramping activity, by itself, is weak evidence that a brain area mediates evidence accumulation as opposed to threshold readout; and that signs of modulated accumulation are as likely to indicate threshold adaptation as adaptation of starting points and accumulation rates. These conclusions imply that how thresholds are modeled can dramatically impact accumulator-based interpretations of this data. PMID:22737136

Methods used in adaptation of health-related guidelines: A systematic survey.

PubMed

Abdul-Khalek, Rima A; Darzi, Andrea J; Godah, Mohammad W; Kilzar, Lama; Lakis, Chantal; Agarwal, Arnav; Abou-Jaoude, Elias; Meerpohl, Joerg J; Wiercioch, Wojtek; Santesso, Nancy; Brax, Hneine; Schünemann, Holger; Akl, Elie A

2017-12-01

Adaptation refers to the systematic approach for considering the endorsement or modification of recommendations produced in one setting for application in another as an alternative to de novo development. To describe and assess the methods used for adapting health-related guidelines published in peer-reviewed journals, and to assess the quality of the resulting adapted guidelines. We searched Medline and Embase up to June 2015. We assessed the method of adaptation, and the quality of included guidelines. Seventy-two papers were eligible. Most adapted guidelines and their source guidelines were published by professional societies (71% and 68% respectively), and in high-income countries (83% and 85% respectively). Of the 57 adapted guidelines that reported any detail about adaptation method, 34 (60%) did not use a published adaptation method. The number (and percentage) of adapted guidelines fulfilling each of the ADAPTE steps ranged between 2 (4%) and 57 (100%). The quality of adapted guidelines was highest for the "scope and purpose" domain and lowest for the "editorial independence" domain (respective mean percentages of the maximum possible scores were 93% and 43%). The mean score for "rigor of development" was 57%. Most adapted guidelines published in peer-reviewed journals do not report using a published adaptation method, and their adaptation quality was variable.

Reduced rank regression via adaptive nuclear norm penalization

PubMed Central

Chen, Kun; Dong, Hongbo; Chan, Kung-Sik

2014-01-01

Summary We propose an adaptive nuclear norm penalization approach for low-rank matrix approximation, and use it to develop a new reduced rank estimation method for high-dimensional multivariate regression. The adaptive nuclear norm is defined as the weighted sum of the singular values of the matrix, and it is generally non-convex under the natural restriction that the weight decreases with the singular value. However, we show that the proposed non-convex penalized regression method has a global optimal solution obtained from an adaptively soft-thresholded singular value decomposition. The method is computationally efficient, and the resulting solution path is continuous. The rank consistency of and prediction/estimation performance bounds for the estimator are established for a high-dimensional asymptotic regime. Simulation studies and an application in genetics demonstrate its efficacy. PMID:25045172

Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images.

PubMed

Basset, Antoine; Boulanger, Jérôme; Salamero, Jean; Bouthemy, Patrick; Kervrann, Charles

2015-11-01

Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) automatically selects the optimal scale corresponding to the most frequent spot size in the image. Four criteria are proposed and compared to determine the optimal scale in a scale-space framework. Then, the segmentation stage amounts to thresholding the LoG of the intensity image. In contrast to other methods, the threshold is locally adapted given a probability of false alarm (PFA) specified by the user for the whole set of images to be processed. The local threshold is automatically derived from the PFA value and local image statistics estimated in a window whose size is not a critical parameter. We also propose a new data set for benchmarking, consisting of six collections of one hundred images each, which exploits backgrounds extracted from real microscopy images. We have carried out an extensive comparative evaluation on several data sets with ground-truth, which demonstrates that ATLAS outperforms existing methods. ATLAS does not need any fine parameter tuning and requires very low computation time. Convincing results are also reported on real total internal reflection fluorescence microscopy images.

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

Goldsmith, Steven Y.

2004-06-22

An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

NASA Technical Reports Server (NTRS)

Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong; Farfan-Ramos, Luis; Simon, Donald L.

2010-01-01

A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

A critique of the use of indicator-species scores for identifying thresholds in species responses

USGS Publications Warehouse

Cuffney, Thomas F.; Qian, Song S.

2013-01-01

Identification of ecological thresholds is important both for theoretical and applied ecology. Recently, Baker and King (2010, King and Baker 2010) proposed a method, threshold indicator analysis (TITAN), to calculate species and community thresholds based on indicator species scores adapted from Dufrêne and Legendre (1997). We tested the ability of TITAN to detect thresholds using models with (broken-stick, disjointed broken-stick, dose-response, step-function, Gaussian) and without (linear) definitive thresholds. TITAN accurately and consistently detected thresholds in step-function models, but not in models characterized by abrupt changes in response slopes or response direction. Threshold detection in TITAN was very sensitive to the distribution of 0 values, which caused TITAN to identify thresholds associated with relatively small differences in the distribution of 0 values while ignoring thresholds associated with large changes in abundance. Threshold identification and tests of statistical significance were based on the same data permutations resulting in inflated estimates of statistical significance. Application of bootstrapping to the split-point problem that underlies TITAN led to underestimates of the confidence intervals of thresholds. Bias in the derivation of the z-scores used to identify TITAN thresholds and skewedness in the distribution of data along the gradient produced TITAN thresholds that were much more similar than the actual thresholds. This tendency may account for the synchronicity of thresholds reported in TITAN analyses. The thresholds identified by TITAN represented disparate characteristics of species responses that, when coupled with the inability of TITAN to identify thresholds accurately and consistently, does not support the aggregation of individual species thresholds into a community threshold.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Threshold magnitudes for a multichannel correlation detector in background seismicity

DOE PAGES

Carmichael, Joshua D.; Hartse, Hans

2016-04-01

Colocated explosive sources often produce correlated seismic waveforms. Multichannel correlation detectors identify these signals by scanning template waveforms recorded from known reference events against "target" data to find similar waveforms. This screening problem is challenged at thresholds required to monitor smaller explosions, often because non-target signals falsely trigger such detectors. Therefore, it is generally unclear what thresholds will reliably identify a target explosion while screening non-target background seismicity. Here, we estimate threshold magnitudes for hypothetical explosions located at the North Korean nuclear test site over six months of 2010, by processing International Monitoring System (IMS) array data with a multichannelmore » waveform correlation detector. Our method (1) accounts for low amplitude background seismicity that falsely triggers correlation detectors but is unidentifiable with conventional power beams, (2) adapts to diurnally variable noise levels and (3) uses source-receiver reciprocity concepts to estimate thresholds for explosions spatially separated from the template source. Furthermore, we find that underground explosions with body wave magnitudes m b = 1.66 are detectable at the IMS array USRK with probability 0.99, when using template waveforms consisting only of P -waves, without false alarms. We conservatively find that these thresholds also increase by up to a magnitude unit for sources located 4 km or more from the Feb.12, 2013 announced nuclear test.« less

Comparison of in-air evoked potential and underwater behavioral hearing thresholds in four bottlenose dolphins (Tursiops truncatus).

PubMed

Finneran, James J; Houser, Dorian S

2006-05-01

Traditional behavioral techniques for hearing assessment in marine mammals are limited by the time and access required to train subjects. Electrophysiological methods, where passive electrodes are used to measure auditory evoked potentials (AEPs), are attractive alternatives to behavioral techniques; however, there have been few attempts to compare AEP and behavioral results for the same subject. In this study, behavioral and AEP hearing thresholds were compared in four bottlenose dolphins. AEP thresholds were measured in-air using a piezoelectric sound projector embedded in a suction cup to deliver amplitude modulated tones to the dolphin through the lower jaw. Evoked potentials were recorded noninvasively using surface electrodes. Adaptive procedures allowed AEP hearing thresholds to be estimated from 10 to 150 kHz in a single ear in about 45 min. Behavioral thresholds were measured in a quiet pool and in San Diego Bay. AEP and behavioral threshold estimates agreed closely as to the upper cutoff frequency beyond which thresholds increased sharply. AEP thresholds were strongly correlated with pool behavioral thresholds across the range of hearing; differences between AEP and pool behavioral thresholds increased with threshold magnitude and ranged from 0 to + 18 dB.

Peaks Over Threshold (POT): A methodology for automatic threshold estimation using goodness of fit p-value

NASA Astrophysics Data System (ADS)

Solari, Sebastián.; Egüen, Marta; Polo, María. José; Losada, Miguel A.

2017-04-01

Threshold estimation in the Peaks Over Threshold (POT) method and the impact of the estimation method on the calculation of high return period quantiles and their uncertainty (or confidence intervals) are issues that are still unresolved. In the past, methods based on goodness of fit tests and EDF-statistics have yielded satisfactory results, but their use has not yet been systematized. This paper proposes a methodology for automatic threshold estimation, based on the Anderson-Darling EDF-statistic and goodness of fit test. When combined with bootstrapping techniques, this methodology can be used to quantify both the uncertainty of threshold estimation and its impact on the uncertainty of high return period quantiles. This methodology was applied to several simulated series and to four precipitation/river flow data series. The results obtained confirmed its robustness. For the measured series, the estimated thresholds corresponded to those obtained by nonautomatic methods. Moreover, even though the uncertainty of the threshold estimation was high, this did not have a significant effect on the width of the confidence intervals of high return period quantiles.

A Method For Assessing Economic Thresholds of Hardwood Competition

Treesearch

Steven A. Knowe

2002-01-01

A procedure was developed for computing economic thresholds for hardwood competition in pine plantations. The economic threshold represents the break-even level of competition above which hardwood control is a financially attractive treatment. Sensitivity analyses were conducted to examine the relative importance of biological and economic factors in determining...

Interocular transfer of spatial adaptation is weak at low spatial frequencies.

PubMed

Baker, Daniel H; Meese, Tim S

2012-06-15

Adapting one eye to a high contrast grating reduces sensitivity to similar target gratings shown to the same eye, and also to those shown to the opposite eye. According to the textbook account, interocular transfer (IOT) of adaptation is around 60% of the within-eye effect. However, most previous studies on this were limited to using high spatial frequencies, sustained presentation, and criterion-dependent methods for assessing threshold. Here, we measure IOT across a wide range of spatiotemporal frequencies, using a criterion-free 2AFC method. We find little or no IOT at low spatial frequencies, consistent with other recent observations. At higher spatial frequencies, IOT was present, but weaker than previously reported (around 35%, on average, at 8c/deg). Across all conditions, monocular adaptation raised thresholds by around a factor of 2, and observers showed normal binocular summation, demonstrating that they were not binocularly compromised. These findings prompt a reassessment of our understanding of the binocular architecture implied by interocular adaptation. In particular, the output of monocular channels may be available to perceptual decision making at low spatial frequencies. Copyright © 2012 Elsevier Ltd. All rights reserved.

An objective method for measuring face detection thresholds using the sweep steady-state visual evoked response

PubMed Central

Ales, Justin M.; Farzin, Faraz; Rossion, Bruno; Norcia, Anthony M.

2012-01-01

We introduce a sensitive method for measuring face detection thresholds rapidly, objectively, and independently of low-level visual cues. The method is based on the swept parameter steady-state visual evoked potential (ssVEP), in which a stimulus is presented at a specific temporal frequency while parametrically varying (“sweeping”) the detectability of the stimulus. Here, the visibility of a face image was increased by progressive derandomization of the phase spectra of the image in a series of equally spaced steps. Alternations between face and fully randomized images at a constant rate (3/s) elicit a robust first harmonic response at 3 Hz specific to the structure of the face. High-density EEG was recorded from 10 human adult participants, who were asked to respond with a button-press as soon as they detected a face. The majority of participants produced an evoked response at the first harmonic (3 Hz) that emerged abruptly between 30% and 35% phase-coherence of the face, which was most prominent on right occipito-temporal sites. Thresholds for face detection were estimated reliably in single participants from 15 trials, or on each of the 15 individual face trials. The ssVEP-derived thresholds correlated with the concurrently measured perceptual face detection thresholds. This first application of the sweep VEP approach to high-level vision provides a sensitive and objective method that could be used to measure and compare visual perception thresholds for various object shapes and levels of categorization in different human populations, including infants and individuals with developmental delay. PMID:23024355

Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis.

PubMed Central

Sieracki, M E; Reichenbach, S E; Webb, K L

1989-01-01

The accurate measurement of bacterial and protistan cell biomass is necessary for understanding their population and trophic dynamics in nature. Direct measurement of fluorescently stained cells is often the method of choice. The tedium of making such measurements visually on the large numbers of cells required has prompted the use of automatic image analysis for this purpose. Accurate measurements by image analysis require an accurate, reliable method of segmenting the image, that is, distinguishing the brightly fluorescing cells from a dark background. This is commonly done by visually choosing a threshold intensity value which most closely coincides with the outline of the cells as perceived by the operator. Ideally, an automated method based on the cell image characteristics should be used. Since the optical nature of edges in images of light-emitting, microscopic fluorescent objects is different from that of images generated by transmitted or reflected light, it seemed that automatic segmentation of such images may require special considerations. We tested nine automated threshold selection methods using standard fluorescent microspheres ranging in size and fluorescence intensity and fluorochrome-stained samples of cells from cultures of cyanobacteria, flagellates, and ciliates. The methods included several variations based on the maximum intensity gradient of the sphere profile (first derivative), the minimum in the second derivative of the sphere profile, the minimum of the image histogram, and the midpoint intensity. Our results indicated that thresholds determined visually and by first-derivative methods tended to overestimate the threshold, causing an underestimation of microsphere size. The method based on the minimum of the second derivative of the profile yielded the most accurate area estimates for spheres of different sizes and brightnesses and for four of the five cell types tested. A simple model of the optical properties of fluorescing objects and

Adaptive envelope protection methods for aircraft

NASA Astrophysics Data System (ADS)

Unnikrishnan, Suraj

Carefree handling refers to the ability of a pilot to operate an aircraft without the need to continuously monitor aircraft operating limits. At the heart of all carefree handling or maneuvering systems, also referred to as envelope protection systems, are algorithms and methods for predicting future limit violations. Recently, envelope protection methods that have gained more acceptance, translate limit proximity information to its equivalent in the control channel. Envelope protection algorithms either use very small prediction horizon or are static methods with no capability to adapt to changes in system configurations. Adaptive approaches maximizing prediction horizon such as dynamic trim, are only applicable to steady-state-response critical limit parameters. In this thesis, a new adaptive envelope protection method is developed that is applicable to steady-state and transient response critical limit parameters. The approach is based upon devising the most aggressive optimal control profile to the limit boundary and using it to compute control limits. Pilot-in-the-loop evaluations of the proposed approach are conducted at the Georgia Tech Carefree Maneuver lab for transient longitudinal hub moment limit protection. Carefree maneuvering is the dual of carefree handling in the realm of autonomous Uninhabited Aerial Vehicles (UAVs). Designing a flight control system to fully and effectively utilize the operational flight envelope is very difficult. With the increasing role and demands for extreme maneuverability there is a need for developing envelope protection methods for autonomous UAVs. In this thesis, a full-authority automatic envelope protection method is proposed for limit protection in UAVs. The approach uses adaptive estimate of limit parameter dynamics and finite-time horizon predictions to detect impending limit boundary violations. Limit violations are prevented by treating the limit boundary as an obstacle and by correcting nominal control

Adaptive Set-Based Methods for Association Testing.

PubMed

Su, Yu-Chen; Gauderman, William James; Berhane, Kiros; Lewinger, Juan Pablo

2016-02-01

With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test. © 2015 WILEY PERIODICALS, INC.

Sub-Volumetric Classification and Visualization of Emphysema Using a Multi-Threshold Method and Neural Network

NASA Astrophysics Data System (ADS)

Tan, Kok Liang; Tanaka, Toshiyuki; Nakamura, Hidetoshi; Shirahata, Toru; Sugiura, Hiroaki

Chronic Obstructive Pulmonary Disease is a disease in which the airways and tiny air sacs (alveoli) inside the lung are partially obstructed or destroyed. Emphysema is what occurs as more and more of the walls between air sacs get destroyed. The goal of this paper is to produce a more practical emphysema-quantification algorithm that has higher correlation with the parameters of pulmonary function tests compared to classical methods. The use of the threshold range from approximately -900 Hounsfield Unit to -990 Hounsfield Unit for extracting emphysema from CT has been reported in many papers. From our experiments, we realize that a threshold which is optimal for a particular CT data set might not be optimal for other CT data sets due to the subtle radiographic variations in the CT images. Consequently, we propose a multi-threshold method that utilizes ten thresholds between and including -900 Hounsfield Unit and -990 Hounsfield Unit for identifying the different potential emphysematous regions in the lung. Subsequently, we divide the lung into eight sub-volumes. From each sub-volume, we calculate the ratio of the voxels with the intensity below a certain threshold. The respective ratios of the voxels below the ten thresholds are employed as the features for classifying the sub-volumes into four emphysema severity classes. Neural network is used as the classifier. The neural network is trained using 80 training sub-volumes. The performance of the classifier is assessed by classifying 248 test sub-volumes of the lung obtained from 31 subjects. Actual diagnoses of the sub-volumes are hand-annotated and consensus-classified by radiologists. The four-class classification accuracy of the proposed method is 89.82%. The sub-volumetric classification results produced in this study encompass not only the information of emphysema severity but also the distribution of emphysema severity from the top to the bottom of the lung. We hypothesize that besides emphysema severity, the

Large Covariance Estimation by Thresholding Principal Orthogonal Complements

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088

Fitting psychometric functions using a fixed-slope parameter: an advanced alternative for estimating odor thresholds with data generated by ASTM E679.

PubMed

Peng, Mei; Jaeger, Sara R; Hautus, Michael J

2014-03-01

Psychometric functions are predominately used for estimating detection thresholds in vision and audition. However, the requirement of large data quantities for fitting psychometric functions (>30 replications) reduces their suitability in olfactory studies because olfactory response data are often limited (<4 replications) due to the susceptibility of human olfactory receptors to fatigue and adaptation. This article introduces a new method for fitting individual-judge psychometric functions to olfactory data obtained using the current standard protocol-American Society for Testing and Materials (ASTM) E679. The slope parameter of the individual-judge psychometric function is fixed to be the same as that of the group function; the same-shaped symmetrical sigmoid function is fitted only using the intercept. This study evaluated the proposed method by comparing it with 2 available methods. Comparison to conventional psychometric functions (fitted slope and intercept) indicated that the assumption of a fixed slope did not compromise precision of the threshold estimates. No systematic difference was obtained between the proposed method and the ASTM method in terms of group threshold estimates or threshold distributions, but there were changes in the rank, by threshold, of judges in the group. Overall, the fixed-slope psychometric function is recommended for obtaining relatively reliable individual threshold estimates when the quantity of data is limited.

An integrative perspective of the anaerobic threshold.

PubMed

Sales, Marcelo Magalhães; Sousa, Caio Victor; da Silva Aguiar, Samuel; Knechtle, Beat; Nikolaidis, Pantelis Theodoros; Alves, Polissandro Mortoza; Simões, Herbert Gustavo

2017-12-14

The concept of anaerobic threshold (AT) was introduced during the nineteen sixties. Since then, several methods to identify the anaerobic threshold (AT) have been studied and suggested as novel 'thresholds' based upon the variable used for its detection (i.e. lactate threshold, ventilatory threshold, glucose threshold). These different techniques have brought some confusion about how we should name this parameter, for instance, anaerobic threshold or the physiological measure used (i.e. lactate, ventilation). On the other hand, the modernization of scientific methods and apparatus to detect AT, as well as the body of literature formed in the past decades, could provide a more cohesive understanding over the AT and the multiple physiological systems involved. Thus, the purpose of this review was to provide an integrative perspective of the methods to determine AT. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of Sensibility Threshold for Interocclusal Thickness of Patients Wearing Complete Dentures

PubMed Central

Shala, Kujtim Sh.; Ahmedi, Enis F.; Tmava-Dragusha, Arlinda

2017-01-01

Objective The aim of this study was to evaluate sensibility threshold for interocclusal thickness in experienced and nonexperienced denture wearers after the insertion of new complete dentures. Materials and Methods A total of 88 patients with complete dentures have participated in this study. The research was divided into two experimental groups, compared with the previous experience prosthetic dental treatment. The sensibility threshold for interocclusal thickness was measured with metal foil with 8 μm thickness and width of 8 mm, placed between the upper and lower incisor region. Statistical analysis was performed using standard software package BMDP (biomedical statistical package). Results Results suggest that time of measurement affects the average values of the sensibility threshold for interocclusal thickness (F = 242.68, p = 0.0000). Gender appeared to be a significant factor when it interacted with time measurement resulting in differences in sensibility threshold for interocclusal thickness (gender: F = 9.84, p = 0.018; F = 4.83, p = 0.0003). Conclusion The sensibility threshold for interocclusal thickness was the most important functional adaptation in patient with complete dentures. A unique trait of this indicator is the progressive reduction of initial values and a tendency to reestablish the stationary state in the fifteenth week after dentures is taken off. PMID:28702055

Orion MPCV Touchdown Detection Threshold Development and Testing

NASA Technical Reports Server (NTRS)

Daum, Jared; Gay, Robert

2013-01-01

A robust method of detecting Orion Multi-Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post-landing segment of the Flight Software (FSW). An in-depth trade study was completed to determine optimal characteristics of the touchdown detection method resulting in an algorithm monitoring filtered, lever-arm corrected, 200 Hz Inertial Measurement Unit (IMU) vehicle acceleration magnitude data against a tunable threshold using persistence counter logic. Following the design of the algorithm, high fidelity environment and vehicle simulations, coupled with the actual vehicle FSW, were used to tune the acceleration threshold and persistence counter value to result in adequate performance in detecting touchdown and sufficient safety margin against early detection while descending under parachutes. An analytical approach including Kriging and adaptive sampling allowed for a sufficient number of finite element analysis (FEA) impact simulations to be completed using minimal computation time. The combination of a persistence counter of 10 and an acceleration threshold of approximately 57.3 ft/s2 resulted in an impact performance factor of safety (FOS) of 1.0 and a safety FOS of approximately 2.6 for touchdown declaration. An RCS termination acceleration threshold of approximately 53.1 ft/s(exp)2 with a persistence counter of 10 resulted in an increased impact performance FOS of 1.2 at the expense of a lowered under-parachutes safety factor of 2.2. The resulting tuned algorithm was then tested on data from eight Capsule Parachute Assembly System (CPAS) flight tests, showing an experimental minimum safety FOS of 6.1. The formulated touchdown detection algorithm will be flown on the Orion MPCV FSW during the Exploration Flight Test 1

An Ultra-Low Power Turning Angle Based Biomedical Signal Compression Engine with Adaptive Threshold Tuning.

PubMed

Zhou, Jun; Wang, Chao

2017-08-06

Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems. This paper presents an ultra-low power biomedical signal compression engine for healthcare data sensing and analytics in the era of big data and sensor intelligence. It extracts the feature points of the biomedical signal by window-based turning angle detection. The proposed approach has low complexity and thus low power consumption while achieving a large compression ratio (CR) and good quality of reconstructed signal. Near-threshold design technique is adopted to further reduce the power consumption on the circuit level. Besides, the angle threshold for compression can be adaptively tuned according to the error between the original signal and reconstructed signal to address the variation of signal characteristics from person to person or from channel to channel to meet the required signal quality with optimal CR. For demonstration, the proposed biomedical compression engine has been used and evaluated for ECG compression. It achieves an average (CR) of 71.08% and percentage root-mean-square difference (PRD) of 5.87% while consuming only 39 nW. Compared to several state-of-the-art ECG compression engines, the proposed design has significantly lower power consumption while achieving similar CRD and PRD, making it suitable for long-term wearable miniaturized sensor systems to sense and collect healthcare data for remote data analytics.

An automatic segmentation method of a parameter-adaptive PCNN for medical images.

PubMed

Lian, Jing; Shi, Bin; Li, Mingcong; Nan, Ziwei; Ma, Yide

2017-09-01

Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision. The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter [Formula: see text] for different kinds of images. Secondly, we acquire the parameter [Formula: see text] according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset [Formula: see text] to improve initial segmentation precision. Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726. The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.

Continuous Seismic Threshold Monitoring

DTIC Science & Technology

1992-05-31

Continuous threshold monitoring is a technique for using a seismic network to monitor a geographical area continuously in time. The method provides...area. Two approaches are presented. Site-specific monitoring: By focusing a seismic network on a specific target site, continuous threshold monitoring...recorded events at the site. We define the threshold trace for the network as the continuous time trace of computed upper magnitude limits of seismic

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

Quantifying ecological thresholds from response surfaces

Treesearch

Heather E. Lintz; Bruce McCune; Andrew N. Gray; Katherine A. McCulloh

2011-01-01

Ecological thresholds are abrupt changes of ecological state. While an ecological threshold is a widely accepted concept, most empirical methods detect them in time or across geographic space. Although useful, these approaches do not quantify the direct drivers of threshold response. Causal understanding of thresholds detected empirically requires their investigation...

The Random-Threshold Generalized Unfolding Model and Its Application of Computerized Adaptive Testing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien

2013-01-01

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

Automated tumour boundary delineation on 18F-FDG PET images using active contour coupled with shifted-optimal thresholding method

NASA Astrophysics Data System (ADS)

Khamwan, Kitiwat; Krisanachinda, Anchali; Pluempitiwiriyawej, Charnchai

2012-10-01

This study presents an automatic method to trace the boundary of the tumour in positron emission tomography (PET) images. It has been discovered that Otsu's threshold value is biased when the within-class variances between the object and the background are significantly different. To solve the problem, a double-stage threshold search that minimizes the energy between the first Otsu's threshold and the maximum intensity value is introduced. Such shifted-optimal thresholding is embedded into a region-based active contour so that both algorithms are performed consecutively. The efficiency of the method is validated using six sphere inserts (0.52-26.53 cc volume) of the IEC/2001 torso phantom. Both spheres and phantom were filled with 18F solution with four source-to-background ratio (SBR) measurements of PET images. The results illustrate that the tumour volumes segmented by combined algorithm are of higher accuracy than the traditional active contour. The method had been clinically implemented in ten oesophageal cancer patients. The results are evaluated and compared with the manual tracing by an experienced radiation oncologist. The advantage of the algorithm is the reduced erroneous delineation that improves the precision and accuracy of PET tumour contouring. Moreover, the combined method is robust, independent of the SBR threshold-volume curves, and it does not require prior lesion size measurement.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.; Marino, J. T., Jr.

1974-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.

1975-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Comparison of Threshold Detection Methods for the Generalized Pareto Distribution (GPD): Application to the NOAA-NCDC Daily Rainfall Dataset

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Mamalakis, Antonis; Langousis, Andreas

2015-04-01

One of the most crucial issues in statistical hydrology is the estimation of extreme rainfall from data. To that extent, based on asymptotic arguments from Extreme Excess (EE) theory, several studies have focused on developing new, or improving existing methods to fit a Generalized Pareto Distribution (GPD) model to rainfall excesses above a properly selected threshold u. The latter is generally determined using various approaches that can be grouped into three basic classes: a) non-parametric methods that locate the changing point between extreme and non-extreme regions of the data, b) graphical methods where one studies the dependence of the GPD parameters (or related metrics) to the threshold level u, and c) Goodness of Fit (GoF) metrics that, for a certain level of significance, locate the lowest threshold u that a GPD model is applicable. In this work, we review representative methods for GPD threshold detection, discuss fundamental differences in their theoretical bases, and apply them to daily rainfall records from the NOAA-NCDC open-access database (http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/). We find that non-parametric methods that locate the changing point between extreme and non-extreme regions of the data are generally not reliable, while graphical methods and GoF metrics that rely on limiting arguments for the upper distribution tail lead to unrealistically high thresholds u. The latter is expected, since one checks the validity of the limiting arguments rather than the applicability of a GPD distribution model. Better performance is demonstrated by graphical methods and GoF metrics that rely on GPD properties. Finally, we discuss the effects of data quantization (common in hydrologic applications) on the estimated thresholds. Acknowledgments: The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General

Absolute auditory threshold: testing the absolute.

PubMed

Heil, Peter; Matysiak, Artur

2017-11-02

The mechanisms underlying the detection of sounds in quiet, one of the simplest tasks for auditory systems, are debated. Several models proposed to explain the threshold for sounds in quiet and its dependence on sound parameters include a minimum sound intensity ('hard threshold'), below which sound has no effect on the ear. Also, many models are based on the assumption that threshold is mediated by integration of a neural response proportional to sound intensity. Here, we test these ideas. Using an adaptive forced choice procedure, we obtained thresholds of 95 normal-hearing human ears for 18 tones (3.125 kHz carrier) in quiet, each with a different temporal amplitude envelope. Grand-mean thresholds and standard deviations were well described by a probabilistic model according to which sensory events are generated by a Poisson point process with a low rate in the absence, and higher, time-varying rates in the presence, of stimulation. The subject actively evaluates the process and bases the decision on the number of events observed. The sound-driven rate of events is proportional to the temporal amplitude envelope of the bandpass-filtered sound raised to an exponent. We find no evidence for a hard threshold: When the model is extended to include such a threshold, the fit does not improve. Furthermore, we find an exponent of 3, consistent with our previous studies and further challenging models that are based on the assumption of the integration of a neural response that, at threshold sound levels, is directly proportional to sound amplitude or intensity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula.

PubMed

Mera, David; Cotos, José M; Varela-Pet, José; Garcia-Pineda, Oscar

2012-10-01

Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean's surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time. Copyright © 2012 Elsevier Ltd. All rights reserved.

Adaptive reconnection-based arbitrary Lagrangian Eulerian method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bo, Wurigen; Shashkov, Mikhail

We present a new adaptive Arbitrary Lagrangian Eulerian (ALE) method. This method is based on the reconnection-based ALE (ReALE) methodology of Refs. [35], [34] and [6]. The main elements in a standard ReALE method are: an explicit Lagrangian phase on an arbitrary polygonal (in 2D) mesh in which the solution and positions of grid nodes are updated; a rezoning phase in which a new grid is defined by changing the connectivity (using Voronoi tessellation) but not the number of cells; and a remapping phase in which the Lagrangian solution is transferred onto the new grid. Furthermore, in the standard ReALEmore » method, the rezoned mesh is smoothed by using one or several steps toward centroidal Voronoi tessellation, but it is not adapted to the solution in any way.« less

Adaptive reconnection-based arbitrary Lagrangian Eulerian method

DOE PAGES

Bo, Wurigen; Shashkov, Mikhail

2015-07-21

We present a new adaptive Arbitrary Lagrangian Eulerian (ALE) method. This method is based on the reconnection-based ALE (ReALE) methodology of Refs. [35], [34] and [6]. The main elements in a standard ReALE method are: an explicit Lagrangian phase on an arbitrary polygonal (in 2D) mesh in which the solution and positions of grid nodes are updated; a rezoning phase in which a new grid is defined by changing the connectivity (using Voronoi tessellation) but not the number of cells; and a remapping phase in which the Lagrangian solution is transferred onto the new grid. Furthermore, in the standard ReALEmore » method, the rezoned mesh is smoothed by using one or several steps toward centroidal Voronoi tessellation, but it is not adapted to the solution in any way.« less

An n -material thresholding method for improving integerness of solutions in topology optimization

DOE PAGES

Watts, Seth; Tortorelli, Daniel A.

2016-04-10

It is common in solving topology optimization problems to replace an integer-valued characteristic function design field with the material volume fraction field, a real-valued approximation of the design field that permits "fictitious" mixtures of materials during intermediate iterations in the optimization process. This is reasonable so long as one can interpolate properties for such materials and so long as the final design is integer valued. For this purpose, we present a method for smoothly thresholding the volume fractions of an arbitrary number of material phases which specify the design. This method is trivial for two-material design problems, for example, themore » canonical topology design problem of specifying the presence or absence of a single material within a domain, but it becomes more complex when three or more materials are used, as often occurs in material design problems. We take advantage of the similarity in properties between the volume fractions and the barycentric coordinates on a simplex to derive a thresholding, method which is applicable to an arbitrary number of materials. As we show in a sensitivity analysis, this method has smooth derivatives, allowing it to be used in gradient-based optimization algorithms. Finally, we present results, which show synergistic effects when used with Solid Isotropic Material with Penalty and Rational Approximation of Material Properties material interpolation functions, popular methods of ensuring integerness of solutions.« less

Automatic luminous reflections detector using global threshold with increased luminosity contrast in images

NASA Astrophysics Data System (ADS)

Silva, Ricardo Petri; Naozuka, Gustavo Taiji; Mastelini, Saulo Martiello; Felinto, Alan Salvany

2018-01-01

The incidence of luminous reflections (LR) in captured images can interfere with the color of the affected regions. These regions tend to oversaturate, becoming whitish and, consequently, losing the original color information of the scene. Decision processes that employ images acquired from digital cameras can be impaired by the LR incidence. Such applications include real-time video surgeries, facial, and ocular recognition. This work proposes an algorithm called contrast enhancement of potential LR regions, which is a preprocessing to increase the contrast of potential LR regions, in order to improve the performance of automatic LR detectors. In addition, three automatic detectors were compared with and without the employment of our preprocessing method. The first one is a technique already consolidated in the literature called the Chang-Tseng threshold. We propose two automatic detectors called adapted histogram peak and global threshold. We employed four performance metrics to evaluate the detectors, namely, accuracy, precision, exactitude, and root mean square error. The exactitude metric is developed by this work. Thus, a manually defined reference model was created. The global threshold detector combined with our preprocessing method presented the best results, with an average exactitude rate of 82.47%.

Sign language spotting with a threshold model based on conditional random fields.

PubMed

Yang, Hee-Deok; Sclaroff, Stan; Lee, Seong-Whan

2009-07-01

Sign language spotting is the task of detecting and recognizing signs in a signed utterance, in a set vocabulary. The difficulty of sign language spotting is that instances of signs vary in both motion and appearance. Moreover, signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and nonsign patterns (which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing threshold models in a conditional random field (CRF) model is proposed which performs an adaptive threshold for distinguishing between signs in a vocabulary and nonsign patterns. A short-sign detector, a hand appearance-based sign verification method, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experiments demonstrate that our system can spot signs from continuous data with an 87.0 percent spotting rate and can recognize signs from isolated data with a 93.5 percent recognition rate versus 73.5 percent and 85.4 percent, respectively, for CRFs without a threshold model, short-sign detection, subsign reasoning, and hand appearance-based sign verification. Our system can also achieve a 15.0 percent sign error rate (SER) from continuous data and a 6.4 percent SER from isolated data versus 76.2 percent and 14.5 percent, respectively, for conventional CRFs.

Wavelet-based Adaptive Mesh Refinement Method for Global Atmospheric Chemical Transport Modeling

NASA Astrophysics Data System (ADS)

Rastigejev, Y.

2011-12-01

Numerical modeling of global atmospheric chemical transport presents enormous computational difficulties, associated with simulating a wide range of time and spatial scales. The described difficulties are exacerbated by the fact that hundreds of chemical species and thousands of chemical reactions typically are used for chemical kinetic mechanism description. These computational requirements very often forces researches to use relatively crude quasi-uniform numerical grids with inadequate spatial resolution that introduces significant numerical diffusion into the system. It was shown that this spurious diffusion significantly distorts the pollutant mixing and transport dynamics for typically used grid resolution. The described numerical difficulties have to be systematically addressed considering that the demand for fast, high-resolution chemical transport models will be exacerbated over the next decade by the need to interpret satellite observations of tropospheric ozone and related species. In this study we offer dynamically adaptive multilevel Wavelet-based Adaptive Mesh Refinement (WAMR) method for numerical modeling of atmospheric chemical evolution equations. The adaptive mesh refinement is performed by adding and removing finer levels of resolution in the locations of fine scale development and in the locations of smooth solution behavior accordingly. The algorithm is based on the mathematically well established wavelet theory. This allows us to provide error estimates of the solution that are used in conjunction with an appropriate threshold criteria to adapt the non-uniform grid. Other essential features of the numerical algorithm include: an efficient wavelet spatial discretization that allows to minimize the number of degrees of freedom for a prescribed accuracy, a fast algorithm for computing wavelet amplitudes, and efficient and accurate derivative approximations on an irregular grid. The method has been tested for a variety of benchmark problems

Wavelet methods in multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Helin, T.; Yudytskiy, M.

2013-08-01

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory.

A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data.

PubMed

Collell, Guillem; Prelec, Drazen; Patil, Kaustubh R

2018-01-31

Class imbalance presents a major hurdle in the application of classification methods. A commonly taken approach is to learn ensembles of classifiers using rebalanced data. Examples include bootstrap averaging (bagging) combined with either undersampling or oversampling of the minority class examples. However, rebalancing methods entail asymmetric changes to the examples of different classes, which in turn can introduce their own biases. Furthermore, these methods often require specifying the performance measure of interest a priori, i.e., before learning. An alternative is to employ the threshold moving technique, which applies a threshold to the continuous output of a model, offering the possibility to adapt to a performance measure a posteriori , i.e., a plug-in method. Surprisingly, little attention has been paid to this combination of a bagging ensemble and threshold-moving. In this paper, we study this combination and demonstrate its competitiveness. Contrary to the other resampling methods, we preserve the natural class distribution of the data resulting in well-calibrated posterior probabilities. Additionally, we extend the proposed method to handle multiclass data. We validated our method on binary and multiclass benchmark data sets by using both, decision trees and neural networks as base classifiers. We perform analyses that provide insights into the proposed method.

Solution-adaptive finite element method in computational fracture mechanics

NASA Technical Reports Server (NTRS)

Min, J. B.; Bass, J. M.; Spradley, L. W.

1993-01-01

Some recent results obtained using solution-adaptive finite element method in linear elastic two-dimensional fracture mechanics problems are presented. The focus is on the basic issue of adaptive finite element method for validating the applications of new methodology to fracture mechanics problems by computing demonstration problems and comparing the stress intensity factors to analytical results.

An Ultra-Low Power Turning Angle Based Biomedical Signal Compression Engine with Adaptive Threshold Tuning

PubMed Central

Zhou, Jun; Wang, Chao

2017-01-01

Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems. This paper presents an ultra-low power biomedical signal compression engine for healthcare data sensing and analytics in the era of big data and sensor intelligence. It extracts the feature points of the biomedical signal by window-based turning angle detection. The proposed approach has low complexity and thus low power consumption while achieving a large compression ratio (CR) and good quality of reconstructed signal. Near-threshold design technique is adopted to further reduce the power consumption on the circuit level. Besides, the angle threshold for compression can be adaptively tuned according to the error between the original signal and reconstructed signal to address the variation of signal characteristics from person to person or from channel to channel to meet the required signal quality with optimal CR. For demonstration, the proposed biomedical compression engine has been used and evaluated for ECG compression. It achieves an average (CR) of 71.08% and percentage root-mean-square difference (PRD) of 5.87% while consuming only 39 nW. Compared to several state-of-the-art ECG compression engines, the proposed design has significantly lower power consumption while achieving similar CRD and PRD, making it suitable for long-term wearable miniaturized sensor systems to sense and collect healthcare data for remote data analytics. PMID:28783079

Degraded Chinese rubbing images thresholding based on local first-order statistics

NASA Astrophysics Data System (ADS)

Wang, Fang; Hou, Ling-Ying; Huang, Han

2017-06-01

It is a necessary step for Chinese character segmentation from degraded document images in Optical Character Recognizer (OCR); however, it is challenging due to various kinds of noising in such an image. In this paper, we present three local first-order statistics method that had been adaptive thresholding for segmenting text and non-text of Chinese rubbing image. Both visual inspection and numerically investigate for the segmentation results of rubbing image had been obtained. In experiments, it obtained better results than classical techniques in the binarization of real Chinese rubbing image and PHIBD 2012 datasets.

Adaptive Set-Based Methods for Association Testing

PubMed Central

Su, Yu-Chen; Gauderman, W. James; Kiros, Berhane; Lewinger, Juan Pablo

2017-01-01

With a typical sample size of a few thousand subjects, a single genomewide association study (GWAS) using traditional one-SNP-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. While self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly ‘adapt’ to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a LASSO based test. PMID:26707371

Cultural adaptation and translation of measures: an integrated method.

PubMed

Sidani, Souraya; Guruge, Sepali; Miranda, Joyal; Ford-Gilboe, Marilyn; Varcoe, Colleen

2010-04-01

Differences in the conceptualization and operationalization of health-related concepts may exist across cultures. Such differences underscore the importance of examining conceptual equivalence when adapting and translating instruments. In this article, we describe an integrated method for exploring conceptual equivalence within the process of adapting and translating measures. The integrated method involves five phases including selection of instruments for cultural adaptation and translation; assessment of conceptual equivalence, leading to the generation of a set of items deemed to be culturally and linguistically appropriate to assess the concept of interest in the target community; forward translation; back translation (optional); and pre-testing of the set of items. Strengths and limitations of the proposed integrated method are discussed. (c) 2010 Wiley Periodicals, Inc.

Correlations among within-channel and between-channel auditory gap-detection thresholds in normal listeners.

PubMed

Phillips, Dennis P; Smith, Jennifer C

2004-01-01

We obtained data on within-channel and between-channel auditory temporal gap-detection acuity in the normal population. Ninety-five normal listeners were tested for gap-detection thresholds, for conditions in which the gap was bounded by spectrally identical, and by spectrally different, acoustic markers. Separate thresholds were obtained with the use of an adaptive tracking method, for gaps delimited by narrowband noise bursts centred on 1.0 kHz, noise bursts centred on 4.0 kHz, and for gaps bounded by a leading marker of 4.0 kHz noise and a trailing marker of 1.0 kHz noise. Gap thresholds were lowest for silent periods bounded by identical markers--'within-channel' stimuli. Gap thresholds were significantly longer for the between-channel stimulus--silent periods bounded by unidentical markers (p < 0.0001). Thresholds for the two within-channel tasks were highly correlated (R = 0.76). Thresholds for the between-channel stimulus were weakly correlated with thresholds for the within-channel stimuli (1.0 kHz, R = 0.39; and 4.0 kHz, R = 0.46). The relatively poor predictability of between-channel thresholds from the within-channel thresholds is new evidence on the separability of the mechanisms that mediate performance of the two tasks. The data confirm that the acuity difference for the tasks, which has previously been demonstrated in only small numbers of highly trained listeners, extends to a population of untrained listeners. The acuity of the between-channel mechanism may be relevant to the formation of voice-onset time-category boundaries in speech perception.

A simple method to estimate threshold friction velocity of wind erosion in the field

USDA-ARS?s Scientific Manuscript database

Nearly all wind erosion models require the specification of threshold friction velocity (TFV). Yet determining TFV of wind erosion in field conditions is difficult as it depends on both soil characteristics and distribution of vegetation or other roughness elements. While several reliable methods ha...

Impact of Fast Sodium Channel Inactivation on Spike Threshold Dynamics and Synaptic Integration

PubMed Central

Platkiewicz, Jonathan; Brette, Romain

2011-01-01

Neurons spike when their membrane potential exceeds a threshold value. In central neurons, the spike threshold is not constant but depends on the stimulation. Thus, input-output properties of neurons depend both on the effect of presynaptic spikes on the membrane potential and on the dynamics of the spike threshold. Among the possible mechanisms that may modulate the threshold, one strong candidate is Na channel inactivation, because it specifically impacts spike initiation without affecting the membrane potential. We collected voltage-clamp data from the literature and we found, based on a theoretical criterion, that the properties of Na inactivation could indeed cause substantial threshold variability by itself. By analyzing simple neuron models with fast Na inactivation (one channel subtype), we found that the spike threshold is correlated with the mean membrane potential and negatively correlated with the preceding depolarization slope, consistent with experiments. We then analyzed the impact of threshold dynamics on synaptic integration. The difference between the postsynaptic potential (PSP) and the dynamic threshold in response to a presynaptic spike defines an effective PSP. When the neuron is sufficiently depolarized, this effective PSP is briefer than the PSP. This mechanism regulates the temporal window of synaptic integration in an adaptive way. Finally, we discuss the role of other potential mechanisms. Distal spike initiation, channel noise and Na activation dynamics cannot account for the observed negative slope-threshold relationship, while adaptive conductances (e.g. K+) and Na inactivation can. We conclude that Na inactivation is a metabolically efficient mechanism to control the temporal resolution of synaptic integration. PMID:21573200

Stochastic analysis of epidemics on adaptive time varying networks

NASA Astrophysics Data System (ADS)

Kotnis, Bhushan; Kuri, Joy

2013-06-01

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Dynamic-thresholding level set: a novel computer-aided volumetry method for liver tumors in hepatic CT images

NASA Astrophysics Data System (ADS)

Cai, Wenli; Yoshida, Hiroyuki; Harris, Gordon J.

2007-03-01

Measurement of the volume of focal liver tumors, called liver tumor volumetry, is indispensable for assessing the growth of tumors and for monitoring the response of tumors to oncology treatments. Traditional edge models, such as the maximum gradient and zero-crossing methods, often fail to detect the accurate boundary of a fuzzy object such as a liver tumor. As a result, the computerized volumetry based on these edge models tends to differ from manual segmentation results performed by physicians. In this study, we developed a novel computerized volumetry method for fuzzy objects, called dynamic-thresholding level set (DT level set). An optimal threshold value computed from a histogram tends to shift, relative to the theoretical threshold value obtained from a normal distribution model, toward a smaller region in the histogram. We thus designed a mobile shell structure, called a propagating shell, which is a thick region encompassing the level set front. The optimal threshold calculated from the histogram of the shell drives the level set front toward the boundary of a liver tumor. When the volume ratio between the object and the background in the shell approaches one, the optimal threshold value best fits the theoretical threshold value and the shell stops propagating. Application of the DT level set to 26 hepatic CT cases with 63 biopsy-confirmed hepatocellular carcinomas (HCCs) and metastases showed that the computer measured volumes were highly correlated with those of tumors measured manually by physicians. Our preliminary results showed that DT level set was effective and accurate in estimating the volumes of liver tumors detected in hepatic CT images.

Numerical simulation on the adaptation of forms in trabecular bone to mechanical disuse and basic multi-cellular unit activation threshold at menopause

NASA Astrophysics Data System (ADS)

Gong, He; Fan, Yubo; Zhang, Ming

2008-04-01

The objective of this paper is to identify the effects of mechanical disuse and basic multi-cellular unit (BMU) activation threshold on the form of trabecular bone during menopause. A bone adaptation model with mechanical- biological factors at BMU level was integrated with finite element analysis to simulate the changes of trabecular bone structure during menopause. Mechanical disuse and changes in the BMU activation threshold were applied to the model for the period from 4 years before to 4 years after menopause. The changes in bone volume fraction, trabecular thickness and fractal dimension of the trabecular structures were used to quantify the changes of trabecular bone in three different cases associated with mechanical disuse and BMU activation threshold. It was found that the changes in the simulated bone volume fraction were highly correlated and consistent with clinical data, and that the trabecular thickness reduced significantly during menopause and was highly linearly correlated with the bone volume fraction, and that the change trend of fractal dimension of the simulated trabecular structure was in correspondence with clinical observations. The numerical simulation in this paper may help to better understand the relationship between the bone morphology and the mechanical, as well as biological environment; and can provide a quantitative computational model and methodology for the numerical simulation of the bone structural morphological changes caused by the mechanical environment, and/or the biological environment.

Disturbances of rod threshold forced by briefly exposed luminous lines, edges, disks and annuli

PubMed Central

Hallett, P. E.

1971-01-01

1. When the dark-adapted eye is exposed to a brief duration (2 msec) luminous line the resulting threshold disturbance is much sharper (decay constant of ca. 10 min arc) than would be expected in a system which is known to integrate the effects of light quanta over a distance of 1 deg or so. 2. When the forcing input is a pair of brief duration parallel luminous lines the threshold disturbance falls off sharply at the outsides of the pattern but on the inside a considerable spread of threshold-raising effects may occur unless the lines are sufficiently far apart. 3. The threshold disturbance due to a briefly exposed edge shows an overshoot reminiscent of `lateral inhibition'. 4. If the threshold is measured at the centre of a black disk presented in a briefly lit surround then (a) the dependence of threshold on time interval between test and surround suggests that the threshold elevation is due to a non-optical effect which is not `metacontrast'; (b) the dependence of threshold on black disk diameter is consistent with the notion that the spatial threshold disturbance is progressively sharpened as the separation of luminous edges increases. 5. If the threshold is measured at the centre of briefly exposed luminous disks of various diameters one obtains the same evidence for an `antagonistic centre-surround' system as that produced by other workers (e.g. Westheimer, 1965) for the steadily light-adapted eye. 6. The previous paper (Hallett, 1971) showed that brief illumination of the otherwise dark-adapted eye can rapidly and substantially change the extent of spatial integration. The present paper shows that brief illumination leads to substantial `inhibitory' effects. 7. Earlier approaches are reviewed: (a) the linear system signal/noise theory of the time course of threshold disturbances (Hallett, 1969b) is illustrated by the case of a small subtense flash superimposed on a large oscillatory background; (b) the spatial weighting functions of some other authors are

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Moving and adaptive grid methods for compressible flows

NASA Technical Reports Server (NTRS)

Trepanier, Jean-Yves; Camarero, Ricardo

1995-01-01

This paper describes adaptive grid methods developed specifically for compressible flow computations. The basic flow solver is a finite-volume implementation of Roe's flux difference splitting scheme or arbitrarily moving unstructured triangular meshes. The grid adaptation is performed according to geometric and flow requirements. Some results are included to illustrate the potential of the methodology.

Adaptive Discontinuous Galerkin Methods in Multiwavelets Bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Archibald, Richard K; Fann, George I; Shelton Jr, William Allison

2011-01-01

We use a multiwavelet basis with the Discontinuous Galerkin (DG) method to produce a multi-scale DG method. We apply this Multiwavelet DG method to convection and convection-diffusion problems in multiple dimensions. Merging the DG method with multiwavelets allows the adaptivity in the DG method to be resolved through manipulation of multiwavelet coefficients rather than grid manipulation. Additionally, the Multiwavelet DG method is tested on non-linear equations in one dimension and on the cubed sphere.

Comparing Anisotropic Output-Based Grid Adaptation Methods by Decomposition

NASA Technical Reports Server (NTRS)

Park, Michael A.; Loseille, Adrien; Krakos, Joshua A.; Michal, Todd

2015-01-01

Anisotropic grid adaptation is examined by decomposing the steps of flow solution, ad- joint solution, error estimation, metric construction, and simplex grid adaptation. Multiple implementations of each of these steps are evaluated by comparison to each other and expected analytic results when available. For example, grids are adapted to analytic metric fields and grid measures are computed to illustrate the properties of multiple independent implementations of grid adaptation mechanics. Different implementations of each step in the adaptation process can be evaluated in a system where the other components of the adaptive cycle are fixed. Detailed examination of these properties allows comparison of different methods to identify the current state of the art and where further development should be targeted.

Adaptive semantic tag mining from heterogeneous clinical research texts.

PubMed

Hao, T; Weng, C

2015-01-01

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

Threshold-Voltage-Shift Compensation and Suppression Method Using Hydrogenated Amorphous Silicon Thin-Film Transistors for Large Active Matrix Organic Light-Emitting Diode Displays

NASA Astrophysics Data System (ADS)

Oh, Kyonghwan; Kwon, Oh-Kyong

2012-03-01

A threshold-voltage-shift compensation and suppression method for active matrix organic light-emitting diode (AMOLED) displays fabricated using a hydrogenated amorphous silicon thin-film transistor (TFT) backplane is proposed. The proposed method compensates for the threshold voltage variation of TFTs due to different threshold voltage shifts during emission time and extends the lifetime of the AMOLED panel. Measurement results show that the error range of emission current is from -1.1 to +1.7% when the threshold voltage of TFTs varies from 1.2 to 3.0 V.

Anaerobic Threshold and Salivary α-amylase during Incremental Exercise.

PubMed

Akizuki, Kazunori; Yazaki, Syouichirou; Echizenya, Yuki; Ohashi, Yukari

2014-07-01

[Purpose] The purpose of this study was to clarify the validity of salivary α-amylase as a method of quickly estimating anaerobic threshold and to establish the relationship between salivary α-amylase and double-product breakpoint in order to create a way to adjust exercise intensity to a safe and effective range. [Subjects and Methods] Eleven healthy young adults performed an incremental exercise test using a cycle ergometer. During the incremental exercise test, oxygen consumption, carbon dioxide production, and ventilatory equivalent were measured using a breath-by-breath gas analyzer. Systolic blood pressure and heart rate were measured to calculate the double product, from which double-product breakpoint was determined. Salivary α-amylase was measured to calculate the salivary threshold. [Results] One-way ANOVA revealed no significant differences among workloads at the anaerobic threshold, double-product breakpoint, and salivary threshold. Significant correlations were found between anaerobic threshold and salivary threshold and between anaerobic threshold and double-product breakpoint. [Conclusion] As a method for estimating anaerobic threshold, salivary threshold was as good as or better than determination of double-product breakpoint because the correlation between anaerobic threshold and salivary threshold was higher than the correlation between anaerobic threshold and double-product breakpoint. Therefore, salivary threshold is a useful index of anaerobic threshold during an incremental workload.

Policy Tree Optimization for Adaptive Management of Water Resources Systems

NASA Astrophysics Data System (ADS)

Herman, J. D.; Giuliani, M.

2016-12-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points", which are threshold values of indicator variables that signal a change in policy. However, there remains a need for a general method to optimize the choice of indicators and their threshold values in a way that is easily interpretable for decision makers. Here we propose a conceptual framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. We demonstrate the approach using Folsom Reservoir, California as a case study, in which operating policies must balance the risk of both floods and droughts. Given a set of feature variables, such as reservoir level, inflow observations and forecasts, and time of year, the resulting policy defines the conditions under which flood control and water supply hedging operations should be triggered. Importantly, the tree-based rule sets are easy to interpret for decision making, and can be compared to historical operating policies to understand the adaptations needed under possible climate change scenarios. Several remaining challenges are discussed, including the empirical convergence properties of the method, and extensions to irreversible decisions such as infrastructure. Policy tree optimization, and corresponding open-source software, provide a generalizable, interpretable approach to designing adaptive policies under uncertainty for water resources systems.

Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

NASA Technical Reports Server (NTRS)

Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

1979-01-01

The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

Relationships Between Vestibular Measures as Potential Predictors for Spaceflight Sensorimotor Adaptation

NASA Technical Reports Server (NTRS)

Clark, T. K.; Peters, B.; Gadd, N. E.; De Dios, Y. E.; Wood, S.; Bloomberg, J. J.; Mulavara, A. P.

2016-01-01

Introduction: During space exploration missions astronauts are exposed to a series of novel sensorimotor environments, requiring sensorimotor adaptation. Until adaptation is complete, sensorimotor decrements occur, affecting critical tasks such as piloted landing or docking. Of particularly interest are locomotion tasks such as emergency vehicle egress or extra-vehicular activity. While nearly all astronauts eventually adapt sufficiently, it appears there are substantial individual differences in how quickly and effectively this adaptation occurs. These individual differences in capacity for sensorimotor adaptation are poorly understood. Broadly, we aim to identify measures that may serve as pre-flight predictors of and individual's adaptation capacity to spaceflight-induced sensorimotor changes. As a first step, since spaceflight is thought to involve a reinterpretation of graviceptor cues (e.g. otolith cues from the vestibular system) we investigate the relationships between various measures of vestibular function in humans. Methods: In a set of 15 ground-based control subjects, we quantified individual differences in vestibular function using three measures: 1) ocular vestibular evoked myogenic potential (oVEMP), 2) computerized dynamic posturography and 3) vestibular perceptual thresholds. oVEMP responses are elicited using a mechanical stimuli approach. Computerized dynamic posturography was used to quantify Sensory Organization Tests (SOTs), including SOT5M which involved performing pitching head movements while balancing on a sway-reference support surface with eyes closed. We implemented a vestibular perceptual threshold task using the tilt capabilities of the Tilt-Translation Sled (TTS) at JSC. On each trial, the subject was passively roll-tilted left ear down or right ear down in the dark and verbally provided a forced-choice response regarding which direction they felt tilted. The motion profile was a single-cycle sinusoid of angular acceleration with a

A Continuous Threshold Expectile Model.

PubMed

Zhang, Feipeng; Li, Qunhua

2017-12-01

Expectile regression is a useful tool for exploring the relation between the response and the explanatory variables beyond the conditional mean. A continuous threshold expectile regression is developed for modeling data in which the effect of a covariate on the response variable is linear but varies below and above an unknown threshold in a continuous way. The estimators for the threshold and the regression coefficients are obtained using a grid search approach. The asymptotic properties for all the estimators are derived, and the estimator for the threshold is shown to achieve root-n consistency. A weighted CUSUM type test statistic is proposed for the existence of a threshold at a given expectile, and its asymptotic properties are derived under both the null and the local alternative models. This test only requires fitting the model under the null hypothesis in the absence of a threshold, thus it is computationally more efficient than the likelihood-ratio type tests. Simulation studies show that the proposed estimators and test have desirable finite sample performance in both homoscedastic and heteroscedastic cases. The application of the proposed method on a Dutch growth data and a baseball pitcher salary data reveals interesting insights. The proposed method is implemented in the R package cthreshER .

Epidemic spreading on preferred degree adaptive networks.

PubMed

Jolad, Shivakumar; Liu, Wenjia; Schmittmann, B; Zia, R K P

2012-01-01

We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree κ. Using very simple rules for forming such preferred degree networks, we find some unusual statistical properties not found in familiar Erdös-Rényi or scale free networks. By letting κ depend on the fraction of infected individuals, we model the behavioral changes in response to how the extent of the epidemic is perceived. In our models, the behavioral adaptations can be either 'blind' or 'selective'--depending on whether a node adapts by cutting or adding links to randomly chosen partners or selectively, based on the state of the partner. For a frozen preferred network, we find that the infection threshold follows the heterogeneous mean field result λ(c)/μ = <κ>/<κ2> and the phase diagram matches the predictions of the annealed adjacency matrix (AAM) approach. With 'blind' adaptations, although the epidemic threshold remains unchanged, the infection level is substantially affected, depending on the details of the adaptation. The 'selective' adaptive SIS models are most interesting. Both the threshold and the level of infection changes, controlled not only by how the adaptations are implemented but also how often the nodes cut/add links (compared to the time scales of the epidemic spreading). A simple mean field theory is presented for the selective adaptations which capture the qualitative and some of the quantitative features of the infection phase diagram.

CHOW PARAMETERS IN THRESHOLD LOGIC,

DTIC Science & Technology

respect to threshold functions, they provide the optimal test-synthesis method for completely specified 7-argument (or less) functions, reflect the...signs and relative magnitudes of realizing weights and threshold , and can be used themselves as approximating weights. Results are reproved in a

Cell assembly sequences arising from spike threshold adaptation keep track of time in the hippocampus

PubMed Central

Itskov, Vladimir; Curto, Carina; Pastalkova, Eva; Buzsáki, György

2011-01-01

Hippocampal neurons can display reliable and long-lasting sequences of transient firing patterns, even in the absence of changing external stimuli. We suggest that time-keeping is an important function of these sequences, and propose a network mechanism for their generation. We show that sequences of neuronal assemblies recorded from rat hippocampal CA1 pyramidal cells can reliably predict elapsed time (15-20 sec) during wheel running with a precision of 0.5sec. In addition, we demonstrate the generation of multiple reliable, long-lasting sequences in a recurrent network model. These sequences are generated in the presence of noisy, unstructured inputs to the network, mimicking stationary sensory input. Identical initial conditions generate similar sequences, whereas different initial conditions give rise to distinct sequences. The key ingredients responsible for sequence generation in the model are threshold-adaptation and a Mexican-hat-like pattern of connectivity among pyramidal cells. This pattern may arise from recurrent systems such as the hippocampal CA3 region or the entorhinal cortex. We hypothesize that mechanisms that evolved for spatial navigation also support tracking of elapsed time in behaviorally relevant contexts. PMID:21414904

Speech perception at positive signal-to-noise ratios using adaptive adjustment of time compression.

PubMed

Schlueter, Anne; Brand, Thomas; Lemke, Ulrike; Nitzschner, Stefan; Kollmeier, Birger; Holube, Inga

2015-11-01

Positive signal-to-noise ratios (SNRs) characterize listening situations most relevant for hearing-impaired listeners in daily life and should therefore be considered when evaluating hearing aid algorithms. For this, a speech-in-noise test was developed and evaluated, in which the background noise is presented at fixed positive SNRs and the speech rate (i.e., the time compression of the speech material) is adaptively adjusted. In total, 29 younger and 12 older normal-hearing, as well as 24 older hearing-impaired listeners took part in repeated measurements. Younger normal-hearing and older hearing-impaired listeners conducted one of two adaptive methods which differed in adaptive procedure and step size. Analysis of the measurements with regard to list length and estimation strategy for thresholds resulted in a practical method measuring the time compression for 50% recognition. This method uses time-compression adjustment and step sizes according to Versfeld and Dreschler [(2002). J. Acoust. Soc. Am. 111, 401-408], with sentence scoring, lists of 30 sentences, and a maximum likelihood method for threshold estimation. Evaluation of the procedure showed that older participants obtained higher test-retest reliability compared to younger participants. Depending on the group of listeners, one or two lists are required for training prior to data collection.

Fast adaptive composite grid methods on distributed parallel architectures

NASA Technical Reports Server (NTRS)

Lemke, Max; Quinlan, Daniel

1992-01-01

The fast adaptive composite (FAC) grid method is compared with the adaptive composite method (AFAC) under variety of conditions including vectorization and parallelization. Results are given for distributed memory multiprocessor architectures (SUPRENUM, Intel iPSC/2 and iPSC/860). It is shown that the good performance of AFAC and its superiority over FAC in a parallel environment is a property of the algorithm and not dependent on peculiarities of any machine.

Efficient method for calculations of ro-vibrational states in triatomic molecules near dissociation threshold: Application to ozone

NASA Astrophysics Data System (ADS)

Teplukhin, Alexander; Babikov, Dmitri

2016-09-01

A method for calculations of rotational-vibrational states of triatomic molecules up to dissociation threshold (and scattering resonances above it) is devised, that combines hyper-spherical coordinates, sequential diagonalization-truncation procedure, optimized grid DVR, and complex absorbing potential. Efficiency and accuracy of the method and new code are tested by computing the spectrum of ozone up to dissociation threshold, using two different potential energy surfaces. In both cases good agreement with results of previous studies is obtained for the lower energy states localized in the deep (˜10 000 cm-1) covalent well. Upper part of the bound state spectrum, within 600 cm-1 below dissociation threshold, is also computed and is analyzed in detail. It is found that long progressions of symmetric-stretching and bending states (up to 8 and 11 quanta, respectively) survive up to dissociation threshold and even above it, whereas excitations of the asymmetric-stretching overtones couple to the local vibration modes, making assignments difficult. Within 140 cm-1 below dissociation threshold, large-amplitude vibrational states of a floppy complex O⋯O2 are formed over the shallow van der Waals plateau. These are assigned using two local modes: the rocking-motion and the dissociative-motion progressions, up to 6 quanta in each, both with frequency ˜20 cm-1. Many of these plateau states are mixed with states of the covalent well. Interestingly, excitation of the rocking-motion helps keeping these states localized within the plateau region, by raising the effective barrier.

Development of a Method to Determine the Audiogram of the Guinea Pig for Threshold Shift Studies,

DTIC Science & Technology

1984-01-01

AD-A139 717 DEVELOPENI OF A MEHO 10O DEUUUINE tHE AU0IOOGAB Of II THE GUINEA PIG FP0.6 I ARM AEOICAL RESEARCH LAO FORT RUICKER AL. C COMPEIIAIOAE It...tS4 USAARL REPORT NO. 84 - 4 RESU DEVELOPMENT OF A METHOD TO DETERMINE THE AUDIOGRAM OF THE GUINEA PIG FOR THRESHOLD SHIFT STUDIES By Carlos Comperatore...Determine the Audiogram of the Guinea Pig for Threshold Shift Studies G. PERFORMING ORo. REPORT MummaR 7. AUTHOR(e) S. CONTRACT OR GRANT NUMSERa) Carlos

Thresholds for conservation and management: structured decision making as a conceptual framework

USGS Publications Warehouse

Nichols, James D.; Eaton, Mitchell J.; Martin, Julien; Edited by Guntenspergen, Glenn R.

2014-01-01

changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

PubMed Central

Nilsson, Björn; Håkansson, Petra; Johansson, Mikael; Nelander, Sven; Fioretos, Thoas

2007-01-01

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach. PMID:17488501

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

PubMed

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

PubMed Central

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

2016-01-01

Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

Adaptive Nodal Transport Methods for Reactor Transient Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas Downar; E. Lewis

2005-08-31

Develop methods for adaptively treating the angular, spatial, and time dependence of the neutron flux in reactor transient analysis. These methods were demonstrated in the DOE transport nodal code VARIANT and the US NRC spatial kinetics code, PARCS.

Adaptive methods, rolling contact, and nonclassical friction laws

NASA Technical Reports Server (NTRS)

Oden, J. T.

1989-01-01

Results and methods on three different areas of contemporary research are outlined. These include adaptive methods, the rolling contact problem for finite deformation of a hyperelastic or viscoelastic cylinder, and non-classical friction laws for modeling dynamic friction phenomena.

The Formative Method for Adapting Psychotherapy (FMAP): A community-based developmental approach to culturally adapting therapy

PubMed Central

Hwang, Wei-Chin

2010-01-01

How do we culturally adapt psychotherapy for ethnic minorities? Although there has been growing interest in doing so, few therapy adaptation frameworks have been developed. The majority of these frameworks take a top-down theoretical approach to adapting psychotherapy. The purpose of this paper is to introduce a community-based developmental approach to modifying psychotherapy for ethnic minorities. The Formative Method for Adapting Psychotherapy (FMAP) is a bottom-up approach that involves collaborating with consumers to generate and support ideas for therapy adaptation. It involves 5-phases that target developing, testing, and reformulating therapy modifications. These phases include: (a) generating knowledge and collaborating with stakeholders (b) integrating generated information with theory and empirical and clinical knowledge, (c) reviewing the initial culturally adapted clinical intervention with stakeholders and revising the culturally adapted intervention, (d) testing the culturally adapted intervention, and (e) finalizing the culturally adapted intervention. Application of the FMAP is illustrated using examples from a study adapting psychotherapy for Chinese Americans, but can also be readily applied to modify therapy for other ethnic groups. PMID:20625458

Stability and error estimation for Component Adaptive Grid methods

NASA Technical Reports Server (NTRS)

Oliger, Joseph; Zhu, Xiaolei

1994-01-01

Component adaptive grid (CAG) methods for solving hyperbolic partial differential equations (PDE's) are discussed in this paper. Applying recent stability results for a class of numerical methods on uniform grids. The convergence of these methods for linear problems on component adaptive grids is established here. Furthermore, the computational error can be estimated on CAG's using the stability results. Using these estimates, the error can be controlled on CAG's. Thus, the solution can be computed efficiently on CAG's within a given error tolerance. Computational results for time dependent linear problems in one and two space dimensions are presented.

Resilience thinking: integrating resilience, adaptability and transformability

Treesearch

Carl Folke; Stephen R. Carpenter; Brian Walker; Marten Scheffer; Terry Chapin; Johan Rockstrom

2010-01-01

Resilience thinking addresses the dynamics and development of complex social-ecological systems (SES). Three aspects are central: resilience, adaptability and transformability. These aspects interrelate across multiple scales. Resilience in this context is the capacity of a SES to continually change and adapt yet remain within critical thresholds. Adaptability is part...

Application of a Threshold Method to the TRMM Radar for the Estimation of Space-Time Rain Rate Statistics

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Jones, Jeffrey A.

1997-01-01

One of the TRMM radar products of interest is the monthly-averaged rain rates over 5 x 5 degree cells. Clearly, the most directly way of calculating these and similar statistics is to compute them from the individual estimates made over the instantaneous field of view of the Instrument (4.3 km horizontal resolution). An alternative approach is the use of a threshold method. It has been established that over sufficiently large regions the fractional area above a rain rate threshold and the area-average rain rate are well correlated for particular choices of the threshold [e.g., Kedem et al., 19901]. A straightforward application of this method to the TRMM data would consist of the conversion of the individual reflectivity factors to rain rates followed by a calculation of the fraction of these that exceed a particular threshold. Previous results indicate that for thresholds near or at 5 mm/h, the correlation between this fractional area and the area-average rain rate is high. There are several drawbacks to this approach, however. At the TRMM radar frequency of 13.8 GHz the signal suffers attenuation so that the negative bias of the high resolution rain rate estimates will increase as the path attenuation increases. To establish a quantitative relationship between fractional area and area-average rain rate, an independent means of calculating the area-average rain rate is needed such as an array of rain gauges. This type of calibration procedure, however, is difficult for a spaceborne radar such as TRMM. To estimate a statistic other than the mean of the distribution requires, in general, a different choice of threshold and a different set of tuning parameters.

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method.

PubMed

Drevinskas, Tomas; Telksnys, Laimutis; Maruška, Audrius; Gorbatsova, Jelena; Kaljurand, Mihkel

2018-06-05

In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

NASA Astrophysics Data System (ADS)

Li, Qingyong; Huang, Yaping; Liang, Zhengping; Luo, Siwei

Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

A high-throughput method to measure NaCl and acid taste thresholds in mice.

PubMed

Ishiwatari, Yutaka; Bachmanov, Alexander A

2009-05-01

To develop a technique suitable for measuring NaCl taste thresholds in genetic studies, we conducted a series of experiments with outbred CD-1 mice using conditioned taste aversion (CTA) and two-bottle preference tests. In Experiment 1, we compared conditioning procedures involving either oral self-administration of LiCl or pairing NaCl intake with LiCl injections and found that thresholds were the lowest after LiCl self-administration. In Experiment 2, we compared different procedures (30-min and 48-h tests) for testing conditioned mice and found that the 48-h test is more sensitive. In Experiment 3, we examined the effects of varying strength of conditioned (NaCl or LiCl taste intensity) and unconditioned (LiCl toxicity) stimuli and concluded that 75-150 mM LiCl or its mixtures with NaCl are the optimal stimuli for conditioning by oral self-administration. In Experiment 4, we examined whether this technique is applicable for measuring taste thresholds for other taste stimuli. Results of these experiments show that conditioning by oral self-administration of LiCl solutions or its mixtures with other taste stimuli followed by 48-h two-bottle tests of concentration series of a conditioned stimulus is an efficient and sensitive method to measure taste thresholds. Thresholds measured with this technique were 2 mM for NaCl and 1 mM for citric acid. This approach is suitable for simultaneous testing of large numbers of animals, which is required for genetic studies. These data demonstrate that mice, like several other species, generalize CTA from LiCl to NaCl, suggesting that they perceive taste of NaCl and LiCl as qualitatively similar, and they also can generalize CTA of a binary mixture of taste stimuli to mixture components.

Effects of tubing length and coupling method on hearing threshold and real-ear to coupler difference measures.

PubMed

Gustafson, Samantha; Pittman, Andrea; Fanning, Robert

2013-06-01

This tutorial demonstrates the effects of tubing length and coupling type (i.e., foam tip or personal earmold) on hearing threshold and real-ear-to-coupler difference (RECD) measures. Hearing thresholds from 0.25 kHz through 8 kHz are reported at various tubing lengths for 28 normal-hearing adults between the ages of 22 and 31 years. RECD values are reported for 14 of the adults. All measures were made with an insert earphone coupled to a standard foam tip and with an insert earphone coupled to each participant's personal earmold. Threshold and RECD measures obtained with a personal earmold were significantly different from those obtained with a foam tip on repeated measures analyses of variance. One-sample t tests showed these differences to vary systematically with increasing tubing length, with the largest average differences (7-8 dB) occurring at 4 kHz. This systematic examination demonstrates the equal and opposite effects of tubing length on threshold and acoustic measures. Specifically, as tubing length increased, sound pressure level in the ear canal decreased, affecting both hearing thresholds and the real-ear portion of the RECDs. This demonstration shows that when the same coupling method is used to obtain the hearing thresholds and RECD, equal and accurate estimates of real-ear sound pressure level are obtained.

Three-dimensional self-adaptive grid method for complex flows

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Deiwert, George S.

1988-01-01

A self-adaptive grid procedure for efficient computation of three-dimensional complex flow fields is described. The method is based on variational principles to minimize the energy of a spring system analogy which redistributes the grid points. Grid control parameters are determined by specifying maximum and minimum grid spacing. Multidirectional adaptation is achieved by splitting the procedure into a sequence of successive applications of a unidirectional adaptation. One-sided, two-directional constraints for orthogonality and smoothness are used to enhance the efficiency of the method. Feasibility of the scheme is demonstrated by application to a multinozzle, afterbody, plume flow field. Application of the algorithm for initial grid generation is illustrated by constructing a three-dimensional grid about a bump-like geometry.

Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.

2008-01-01

This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.

Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

PubMed Central

Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

2012-01-01

Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

Free energy calculations: an efficient adaptive biasing potential method.

PubMed

Dickson, Bradley M; Legoll, Frédéric; Lelièvre, Tony; Stoltz, Gabriel; Fleurat-Lessard, Paul

2010-05-06

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is computed directly from the population along the coordinates of the free energy. Because of the mollifier, the bias potential is "nonlocal", and its gradient admits a simple analytic expression. A single observation of the reaction coordinate can thus be used to update the approximate free energy at every point within a neighborhood of the observation. This greatly reduces the equilibration time of the adaptive bias potential. This approximation introduces two parameters: strength of mollification and the zero of energy of the bias potential. While we observe that the approximate free energy is a very good estimate of the actual free energy for a large range of mollification strength, we demonstrate that the errors associated with the mollification may be removed via deconvolution. The zero of energy of the bias potential, which is easy to choose, influences the speed of convergence but not the limiting accuracy. This method is simple to apply to free energy or mean force computation in multiple dimensions and does not involve second derivatives of the reaction coordinates, matrix manipulations nor on-the-fly adaptation of parameters. For the alanine dipeptide test case, the new method is found to gain as much as a factor of 10 in efficiency as compared to two basic implementations of the adaptive biasing force methods, and it is shown to be as efficient as well-tempered metadynamics with the postprocess deconvolution giving a clear advantage to the mollified density of states method.

Noninvasive method to estimate anaerobic threshold in individuals with type 2 diabetes.

PubMed

Sales, Marcelo M; Campbell, Carmen Sílvia G; Morais, Pâmella K; Ernesto, Carlos; Soares-Caldeira, Lúcio F; Russo, Paulo; Motta, Daisy F; Moreira, Sérgio R; Nakamura, Fábio Y; Simões, Herbert G

2011-01-12

While several studies have identified the anaerobic threshold (AT) through the responses of blood lactate, ventilation and blood glucose others have suggested the response of the heart rate variability (HRV) as a method to identify the AT in young healthy individuals. However, the validity of HRV in estimating the lactate threshold (LT) and ventilatory threshold (VT) for individuals with type 2 diabetes (T2D) has not been investigated yet. To analyze the possibility of identifying the heart rate variability threshold (HRVT) by considering the responses of parasympathetic indicators during incremental exercise test in type 2 diabetics subjects (T2D) and non diabetics individuals (ND). Nine T2D (55.6 ± 5.7 years, 83.4 ± 26.6 kg, 30.9 ± 5.2 kg.m2(-1)) and ten ND (50.8 ± 5.1 years, 76.2 ± 14.3 kg, 26.5 ± 3.8 kg.m2(-1)) underwent to an incremental exercise test (IT) on a cycle ergometer. Heart rate (HR), rate of perceived exertion (RPE), blood lactate and expired gas concentrations were measured at the end of each stage. HRVT was identified through the responses of root mean square successive difference between adjacent R-R intervals (RMSSD) and standard deviation of instantaneous beat-to-beat R-R interval variability (SD1) by considering the last 60 s of each incremental stage, and were known as HRVT by RMSSD and SD1 (HRVT-RMSSD and HRVT-SD1), respectively. No differences were observed within groups for the exercise intensities corresponding to LT, VT, HRVT-RMSSD and HHVT-SD1. Furthermore, a strong relationship were verified among the studied parameters both for T2D (r = 0.68 to 0.87) and ND (r = 0.91 to 0.98) and the Bland & Altman technique confirmed the agreement among them. The HRVT identification by the proposed autonomic indicators (SD1 and RMSSD) were demonstrated to be valid to estimate the LT and VT for both T2D and ND.

Is ``No-Threshold'' a ``Non-Concept''?

NASA Astrophysics Data System (ADS)

Schaeffer, David J.

1981-11-01

A controversy prominent in scientific literature that has carried over to newspapers, magazines, and popular books is having serious social and political expressions today: “Is there, or is there not, a threshold below which exposure to a carcinogen will not induce cancer?” The distinction between establishing the existence of this threshold (which is a theoretical question) and its value (which is an experimental one) gets lost in the scientific arguments. Establishing the existence of this threshold has now become a philosophical question (and an emotional one). In this paper I qualitatively outline theoretical reasons why a threshold must exist, discuss experiments which measure thresholds on two chemicals, and describe and apply a statistical method for estimating the threshold value from exposure-response data.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

PubMed

Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

2016-02-01

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

Molecular Signaling Network Motifs Provide a Mechanistic Basis for Cellular Threshold Responses

PubMed Central

Bhattacharya, Sudin; Conolly, Rory B.; Clewell, Harvey J.; Kaminski, Norbert E.; Andersen, Melvin E.

2014-01-01

Background: Increasingly, there is a move toward using in vitro toxicity testing to assess human health risk due to chemical exposure. As with in vivo toxicity testing, an important question for in vitro results is whether there are thresholds for adverse cellular responses. Empirical evaluations may show consistency with thresholds, but the main evidence has to come from mechanistic considerations. Objectives: Cellular response behaviors depend on the molecular pathway and circuitry in the cell and the manner in which chemicals perturb these circuits. Understanding circuit structures that are inherently capable of resisting small perturbations and producing threshold responses is an important step towards mechanistically interpreting in vitro testing data. Methods: Here we have examined dose–response characteristics for several biochemical network motifs. These network motifs are basic building blocks of molecular circuits underpinning a variety of cellular functions, including adaptation, homeostasis, proliferation, differentiation, and apoptosis. For each motif, we present biological examples and models to illustrate how thresholds arise from specific network structures. Discussion and Conclusion: Integral feedback, feedforward, and transcritical bifurcation motifs can generate thresholds. Other motifs (e.g., proportional feedback and ultrasensitivity)produce responses where the slope in the low-dose region is small and stays close to the baseline. Feedforward control may lead to nonmonotonic or hormetic responses. We conclude that network motifs provide a basis for understanding thresholds for cellular responses. Computational pathway modeling of these motifs and their combinations occurring in molecular signaling networks will be a key element in new risk assessment approaches based on in vitro cellular assays. Citation: Zhang Q, Bhattacharya S, Conolly RB, Clewell HJ III, Kaminski NE, Andersen ME. 2014. Molecular signaling network motifs provide a

3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels

NASA Astrophysics Data System (ADS)

Huang, Shan; Liu, Xiabi; Han, Guanghui; Zhao, Xinming; Zhao, Yanfeng; Zhou, Chunwu

2018-02-01

The earlier detection of ground glass opacity (GGO) is of great importance since GGOs are more likely to be malignant than solid nodules. However, the detection of GGO is a difficult task in lung cancer screening. This paper proposes a novel GGO candidate extraction method, which performs multilevel thresholding on supervoxels in 3D lung CT images. Firstly, we segment the lung parenchyma based on Otsu algorithm. Secondly, the voxels which are adjacent in 3D discrete space and sharing similar grayscale are clustered into supervoxels. This procedure is used to enhance GGOs and reduce computational complexity. Thirdly, Hessian matrix is used to emphasize focal GGO candidates. Lastly, an improved adaptive multilevel thresholding method is applied on segmented clusters to extract GGO candidates. The proposed method was evaluated on a set of 19 lung CT scans containing 166 GGO lesions from the Lung CT Imaging Signs (LISS) database. The experimental results show that our proposed GGO candidate extraction method is effective, with a sensitivity of 100% and 26.3 of false positives per scan (665 GGO candidates, 499 non-GGO regions and 166 GGO regions). It can handle both focal GGOs and diffuse GGOs.

Locally adaptive parallel temperature accelerated dynamics method

NASA Astrophysics Data System (ADS)

Shim, Yunsic; Amar, Jacques G.

2010-03-01

The recently-developed temperature-accelerated dynamics (TAD) method [M. Sørensen and A.F. Voter, J. Chem. Phys. 112, 9599 (2000)] along with the more recently developed parallel TAD (parTAD) method [Y. Shim et al, Phys. Rev. B 76, 205439 (2007)] allow one to carry out non-equilibrium simulations over extended time and length scales. The basic idea behind TAD is to speed up transitions by carrying out a high-temperature MD simulation and then use the resulting information to obtain event times at the desired low temperature. In a typical implementation, a fixed high temperature Thigh is used. However, in general one expects that for each configuration there exists an optimal value of Thigh which depends on the particular transition pathways and activation energies for that configuration. Here we present a locally adaptive high-temperature TAD method in which instead of using a fixed Thigh the high temperature is dynamically adjusted in order to maximize simulation efficiency. Preliminary results of the performance obtained from parTAD simulations of Cu/Cu(100) growth using the locally adaptive Thigh method will also be presented.

A self-adaptive-grid method with application to airfoil flow

NASA Technical Reports Server (NTRS)

Nakahashi, K.; Deiwert, G. S.

1985-01-01

A self-adaptive-grid method is described that is suitable for multidimensional steady and unsteady computations. Based on variational principles, a spring analogy is used to redistribute grid points in an optimal sense to reduce the overall solution error. User-specified parameters, denoting both maximum and minimum permissible grid spacings, are used to define the all-important constants, thereby minimizing the empiricism and making the method self-adaptive. Operator splitting and one-sided controls for orthogonality and smoothness are used to make the method practical, robust, and efficient. Examples are included for both steady and unsteady viscous flow computations about airfoils in two dimensions, as well as for a steady inviscid flow computation and a one-dimensional case. These examples illustrate the precise control the user has with the self-adaptive method and demonstrate a significant improvement in accuracy and quality of the solutions.

Speckle reduction in optical coherence tomography by adaptive total variation method

NASA Astrophysics Data System (ADS)

Wu, Tong; Shi, Yaoyao; Liu, Youwen; He, Chongjun

2015-12-01

An adaptive total variation method based on the combination of speckle statistics and total variation restoration is proposed and developed for reducing speckle noise in optical coherence tomography (OCT) images. The statistical distribution of the speckle noise in OCT image is investigated and measured. With the measured parameters such as the mean value and variance of the speckle noise, the OCT image is restored by the adaptive total variation restoration method. The adaptive total variation restoration algorithm was applied to the OCT images of a volunteer's hand skin, which showed effective speckle noise reduction and image quality improvement. For image quality comparison, the commonly used median filtering method was also applied to the same images to reduce the speckle noise. The measured results demonstrate the superior performance of the adaptive total variation restoration method in terms of image signal-to-noise ratio, equivalent number of looks, contrast-to-noise ratio, and mean square error.

Is the sky the limit? On the expansion threshold of a species' range.

PubMed

Polechová, Jitka

2018-06-15

More than 100 years after Grigg's influential analysis of species' borders, the causes of limits to species' ranges still represent a puzzle that has never been understood with clarity. The topic has become especially important recently as many scientists have become interested in the potential for species' ranges to shift in response to climate change-and yet nearly all of those studies fail to recognise or incorporate evolutionary genetics in a way that relates to theoretical developments. I show that range margins can be understood based on just two measurable parameters: (i) the fitness cost of dispersal-a measure of environmental heterogeneity-and (ii) the strength of genetic drift, which reduces genetic diversity. Together, these two parameters define an 'expansion threshold': adaptation fails when genetic drift reduces genetic diversity below that required for adaptation to a heterogeneous environment. When the key parameters drop below this expansion threshold locally, a sharp range margin forms. When they drop below this threshold throughout the species' range, adaptation collapses everywhere, resulting in either extinction or formation of a fragmented metapopulation. Because the effects of dispersal differ fundamentally with dimension, the second parameter-the strength of genetic drift-is qualitatively different compared to a linear habitat. In two-dimensional habitats, genetic drift becomes effectively independent of selection. It decreases with 'neighbourhood size'-the number of individuals accessible by dispersal within one generation. Moreover, in contrast to earlier predictions, which neglected evolution of genetic variance and/or stochasticity in two dimensions, dispersal into small marginal populations aids adaptation. This is because the reduction of both genetic and demographic stochasticity has a stronger effect than the cost of dispersal through increased maladaptation. The expansion threshold thus provides a novel, theoretically justified, and

Thermal sensation and climate: a comparison of UTCI and PET thresholds in different climates.

PubMed

Pantavou, Katerina; Lykoudis, Spyridon; Nikolopoulou, Marialena; Tsiros, Ioannis X

2018-06-07

The influence of physiological acclimatization and psychological adaptation on thermal perception is well documented and has revealed the importance of thermal experience and expectation in the evaluation of environmental stimuli. Seasonal patterns of thermal perception have been studied, and calibrated thermal indices' scales have been proposed to obtain meaningful interpretations of thermal sensation indices in different climate regions. The current work attempts to quantify the contribution of climate to the long-term thermal adaptation by examining the relationship between climate normal annual air temperature (1971-2000) and such climate-calibrated thermal indices' assessment scales. The thermal sensation ranges of two thermal indices, the Universal Thermal Climate Index (UTCI) and the Physiological Equivalent Temperature Index (PET), were calibrated for three warm temperate climate contexts (Cfa, Cfb, Csa), against the subjective evaluation of the thermal environment indicated by interviewees during field surveys conducted at seven European cities: Athens (GR), Thessaloniki (GR), Milan (IT), Fribourg (CH), Kassel (DE), Cambridge (UK), and Sheffield (UK), under the same research protocol. Then, calibrated scales for other climate contexts were added from the literature, and the relationship between the respective scales' thresholds and climate normal annual air temperature was examined. To maintain the maximum possible comparability, three methods were applied for the calibration, namely linear, ordinal, and probit regression. The results indicated that the calibrated UTCI and PET thresholds increase with the climate normal annual air temperature of the survey city. To investigate further climates, we also included in the analysis results of previous studies presenting only thresholds for neutral thermal sensation. The average increase of the respective thresholds in the case of neutral thermal sensation was about 0.6 °C for each 1 °C increase of the

Thermal sensation and climate: a comparison of UTCI and PET thresholds in different climates

NASA Astrophysics Data System (ADS)

Pantavou, Katerina; Lykoudis, Spyridon; Nikolopoulou, Marialena; Tsiros, Ioannis X.

2018-06-01

The influence of physiological acclimatization and psychological adaptation on thermal perception is well documented and has revealed the importance of thermal experience and expectation in the evaluation of environmental stimuli. Seasonal patterns of thermal perception have been studied, and calibrated thermal indices' scales have been proposed to obtain meaningful interpretations of thermal sensation indices in different climate regions. The current work attempts to quantify the contribution of climate to the long-term thermal adaptation by examining the relationship between climate normal annual air temperature (1971-2000) and such climate-calibrated thermal indices' assessment scales. The thermal sensation ranges of two thermal indices, the Universal Thermal Climate Index (UTCI) and the Physiological Equivalent Temperature Index (PET), were calibrated for three warm temperate climate contexts (Cfa, Cfb, Csa), against the subjective evaluation of the thermal environment indicated by interviewees during field surveys conducted at seven European cities: Athens (GR), Thessaloniki (GR), Milan (IT), Fribourg (CH), Kassel (DE), Cambridge (UK), and Sheffield (UK), under the same research protocol. Then, calibrated scales for other climate contexts were added from the literature, and the relationship between the respective scales' thresholds and climate normal annual air temperature was examined. To maintain the maximum possible comparability, three methods were applied for the calibration, namely linear, ordinal, and probit regression. The results indicated that the calibrated UTCI and PET thresholds increase with the climate normal annual air temperature of the survey city. To investigate further climates, we also included in the analysis results of previous studies presenting only thresholds for neutral thermal sensation. The average increase of the respective thresholds in the case of neutral thermal sensation was about 0.6 °C for each 1 °C increase of the normal

Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2001-01-01

A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

ICASE/LaRC Workshop on Adaptive Grid Methods

NASA Technical Reports Server (NTRS)

South, Jerry C., Jr. (Editor); Thomas, James L. (Editor); Vanrosendale, John (Editor)

1995-01-01

Solution-adaptive grid techniques are essential to the attainment of practical, user friendly, computational fluid dynamics (CFD) applications. In this three-day workshop, experts gathered together to describe state-of-the-art methods in solution-adaptive grid refinement, analysis, and implementation; to assess the current practice; and to discuss future needs and directions for research. This was accomplished through a series of invited and contributed papers. The workshop focused on a set of two-dimensional test cases designed by the organizers to aid in assessing the current state of development of adaptive grid technology. In addition, a panel of experts from universities, industry, and government research laboratories discussed their views of needs and future directions in this field.

Experimental and Finite Element Modeling of Near-Threshold Fatigue Crack Growth for the K-Decreasing Test Method

NASA Technical Reports Server (NTRS)

Smith, Stephen W.; Seshadri, Banavara R.; Newman, John A.

2015-01-01

The experimental methods to determine near-threshold fatigue crack growth rate data are prescribed in ASTM standard E647. To produce near-threshold data at a constant stress ratio (R), the applied stress-intensity factor (K) is decreased as the crack grows based on a specified K-gradient. Consequently, as the fatigue crack growth rate threshold is approached and the crack tip opening displacement decreases, remote crack wake contact may occur due to the plastically deformed crack wake surfaces and shield the growing crack tip resulting in a reduced crack tip driving force and non-representative crack growth rate data. If such data are used to life a component, the evaluation could yield highly non-conservative predictions. Although this anomalous behavior has been shown to be affected by K-gradient, starting K level, residual stresses, environmental assisted cracking, specimen geometry, and material type, the specifications within the standard to avoid this effect are limited to a maximum fatigue crack growth rate and a suggestion for the K-gradient value. This paper provides parallel experimental and computational simulations for the K-decreasing method for two materials (an aluminum alloy, AA 2024-T3 and a titanium alloy, Ti 6-2-2-2-2) to aid in establishing clear understanding of appropriate testing requirements. These simulations investigate the effect of K-gradient, the maximum value of stress-intensity factor applied, and material type. A material independent term is developed to guide in the selection of appropriate test conditions for most engineering alloys. With the use of such a term, near-threshold fatigue crack growth rate tests can be performed at accelerated rates, near-threshold data can be acquired in days instead of weeks without having to establish testing criteria through trial and error, and these data can be acquired for most engineering materials, even those that are produced in relatively small product forms.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method

Excitable Neurons, Firing Threshold Manifolds and Canards

PubMed Central

2013-01-01

We investigate firing threshold manifolds in a mathematical model of an excitable neuron. The model analyzed investigates the phenomenon of post-inhibitory rebound spiking due to propofol anesthesia and is adapted from McCarthy et al. (SIAM J. Appl. Dyn. Syst. 11(4):1674–1697, [2012]). Propofol modulates the decay time-scale of an inhibitory GABAa synaptic current. Interestingly, this system gives rise to rebound spiking within a specific range of propofol doses. Using techniques from geometric singular perturbation theory, we identify geometric structures, known as canards of folded saddle-type, which form the firing threshold manifolds. We find that the position and orientation of the canard separatrix is propofol dependent. Thus, the speeds of relevant slow synaptic processes are encoded within this geometric structure. We show that this behavior cannot be understood using a static, inhibitory current step protocol, which can provide a single threshold for rebound spiking but cannot explain the observed cessation of spiking for higher propofol doses. We then compare the analyses of dynamic and static synaptic inhibition, showing how the firing threshold manifolds of each relate, and why a current step approach is unable to fully capture the behavior of this model. PMID:23945278

I. RENAL THRESHOLDS FOR HEMOGLOBIN IN DOGS

PubMed Central

Lichty, John A.; Havill, William H.; Whipple, George H.

1932-01-01

We use the term "renal threshold for hemoglobin" to indicate the smallest amount of hemoglobin which given intravenously will effect the appearance of recognizable hemoglobin in the urine. The initial renal threshold level for dog hemoglobin is established by the methods employed at an average value of 155 mg. hemoglobin per kilo body weight with maximal values of 210 and minimal of 124. Repeated daily injections of hemoglobin will depress this initial renal threshold level on the average 46 per cent with maximal values of 110 and minimal values of 60 mg. hemoglobin per kilo body weight. This minimal or depression threshold is relatively constant if the injections are continued. Rest periods without injections cause a return of the renal threshold for hemoglobin toward the initial threshold levels—recovery threshold level. Injections of hemoglobin below the initial threshold level but above the minimal or depression threshold will eventually reduce the renal threshold for hemoglobin to its depression threshold level. We believe the depression threshold or minimal renal threshold level due to repeated hemoglobin injections is a little above the glomerular threshold which we assume is the base line threshold for hemoglobin. Our reasons for this belief in the glomerular threshold are given above and in the other papers of this series. PMID:19870016

DYNAMIC PATTERN RECOGNITION BY MEANS OF THRESHOLD NETS,

DTIC Science & Technology

A method is expounded for the recognition of visual patterns. A circuit diagram of a device is described which is based on a multilayer threshold ...structure synthesized in accordance with the proposed method. Coded signals received each time an image is displayed are transmitted to the threshold ...circuit which distinguishes the signs, and from there to the layers of threshold resolving elements. The image at each layer is made to correspond

Parallel adaptive wavelet collocation method for PDEs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nejadmalayeri, Alireza, E-mail: Alireza.Nejadmalayeri@gmail.com; Vezolainen, Alexei, E-mail: Alexei.Vezolainen@Colorado.edu; Brown-Dymkoski, Eric, E-mail: Eric.Browndymkoski@Colorado.edu

2015-10-01

A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allowsmore » fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.« less

[Target volume segmentation of PET images by an iterative method based on threshold value].

PubMed

Castro, P; Huerga, C; Glaría, L A; Plaza, R; Rodado, S; Marín, M D; Mañas, A; Serrada, A; Núñez, L

2014-01-01

An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition. Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients. The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml. The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images. Copyright © 2013 Elsevier España, S.L.U. and SEMNIM. All rights reserved.

Methods for prismatic/tetrahedral grid generation and adaptation

NASA Technical Reports Server (NTRS)

Kallinderis, Y.

1995-01-01

The present work involves generation of hybrid prismatic/tetrahedral grids for complex 3-D geometries including multi-body domains. The prisms cover the region close to each body's surface, while tetrahedra are created elsewhere. Two developments are presented for hybrid grid generation around complex 3-D geometries. The first is a new octree/advancing front type of method for generation of the tetrahedra of the hybrid mesh. The main feature of the present advancing front tetrahedra generator that is different from previous such methods is that it does not require the creation of a background mesh by the user for the determination of the grid-spacing and stretching parameters. These are determined via an automatically generated octree. The second development is a method for treating the narrow gaps in between different bodies in a multiply-connected domain. This method is applied to a two-element wing case. A High Speed Civil Transport (HSCT) type of aircraft geometry is considered. The generated hybrid grid required only 170 K tetrahedra instead of an estimated two million had a tetrahedral mesh been used in the prisms region as well. A solution adaptive scheme for viscous computations on hybrid grids is also presented. A hybrid grid adaptation scheme that employs both h-refinement and redistribution strategies is developed to provide optimum meshes for viscous flow computations. Grid refinement is a dual adaptation scheme that couples 3-D, isotropic division of tetrahedra and 2-D, directional division of prisms.

Improved shear wave group velocity estimation method based on spatiotemporal peak and thresholding motion search

PubMed Central

Amador, Carolina; Chen, Shigao; Manduca, Armando; Greenleaf, James F.; Urban, Matthew W.

2017-01-01

Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocities values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index (BMI), ultrasound scanners, scanning protocols, ultrasound image quality, etc. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this study, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time (spatiotemporal peak, STP); the second method applies an amplitude filter (spatiotemporal thresholding, STTH) to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared to TTP in phantom. Moreover, in a cohort of 14 healthy subjects STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared to conventional TTP. PMID:28092532

Improved Shear Wave Group Velocity Estimation Method Based on Spatiotemporal Peak and Thresholding Motion Search.

PubMed

Amador Carrascal, Carolina; Chen, Shigao; Manduca, Armando; Greenleaf, James F; Urban, Matthew W

2017-04-01

Quantitative ultrasound elastography is increasingly being used in the assessment of chronic liver disease. Many studies have reported ranges of liver shear wave velocity values for healthy individuals and patients with different stages of liver fibrosis. Nonetheless, ongoing efforts exist to stabilize quantitative ultrasound elastography measurements by assessing factors that influence tissue shear wave velocity values, such as food intake, body mass index, ultrasound scanners, scanning protocols, and ultrasound image quality. Time-to-peak (TTP) methods have been routinely used to measure the shear wave velocity. However, there is still a need for methods that can provide robust shear wave velocity estimation in the presence of noisy motion data. The conventional TTP algorithm is limited to searching for the maximum motion in time profiles at different spatial locations. In this paper, two modified shear wave speed estimation algorithms are proposed. The first method searches for the maximum motion in both space and time [spatiotemporal peak (STP)]; the second method applies an amplitude filter [spatiotemporal thresholding (STTH)] to select points with motion amplitude higher than a threshold for shear wave group velocity estimation. The two proposed methods (STP and STTH) showed higher precision in shear wave velocity estimates compared with TTP in phantom. Moreover, in a cohort of 14 healthy subjects, STP and STTH methods improved both the shear wave velocity measurement precision and the success rate of the measurement compared with conventional TTP.

Reliability of TMS phosphene threshold estimation: Toward a standardized protocol.

PubMed

Mazzi, Chiara; Savazzi, Silvia; Abrahamyan, Arman; Ruzzoli, Manuela

Phosphenes induced by transcranial magnetic stimulation (TMS) are a subjectively described visual phenomenon employed in basic and clinical research as index of the excitability of retinotopically organized areas in the brain. Phosphene threshold estimation is a preliminary step in many TMS experiments in visual cognition for setting the appropriate level of TMS doses; however, the lack of a direct comparison of the available methods for phosphene threshold estimation leaves unsolved the reliability of those methods in setting TMS doses. The present work aims at fulfilling this gap. We compared the most common methods for phosphene threshold calculation, namely the Method of Constant Stimuli (MOCS), the Modified Binary Search (MOBS) and the Rapid Estimation of Phosphene Threshold (REPT). In two experiments we tested the reliability of PT estimation under each of the three methods, considering the day of administration, participants' expertise in phosphene perception and the sensitivity of each method to the initial values used for the threshold calculation. We found that MOCS and REPT have comparable reliability when estimating phosphene thresholds, while MOBS estimations appear less stable. Based on our results, researchers and clinicians can estimate phosphene threshold according to MOCS or REPT equally reliably, depending on their specific investigation goals. We suggest several important factors for consideration when calculating phosphene thresholds and describe strategies to adopt in experimental procedures. Copyright © 2017 Elsevier Inc. All rights reserved.

Thresholds for Shifting Visually Perceived Eye Level Due to Incremental Pitches

NASA Technical Reports Server (NTRS)

Scott, Donald M.; Welch, Robert; Cohen, M. M.; Hill, Cyndi

2001-01-01

Visually perceived eye level (VPEL) was judged by subjects as they viewed a luminous grid pattern that was pitched by 2 or 5 deg increments between -20 deg and +20 deg. Subjects were dark adapted for 20 min and indicated--VPEL by directing the beam of a laser pointer to the rear wall of a 1.25 m cubic pitch box that rotated about a horizontal axis midpoint on the rear wall. Data were analyzed by ANOVA and the Tukey HSD procedure. Results showed a 10.0 deg threshold for pitches P(sub i) above the reference pitch P(sub 0), and a -10.3 deg threshold for pitches P(sub i) below-the reference-pitch P(sub 0). Threshold data for pitches P(sub i) < P(sub 0) suggest an asymmetric threshold for VPEL below and above physical eye level.

Thresholds in chemical respiratory sensitisation.

PubMed

Cochrane, Stella A; Arts, Josje H E; Ehnes, Colin; Hindle, Stuart; Hollnagel, Heli M; Poole, Alan; Suto, Hidenori; Kimber, Ian

2015-07-03

There is a continuing interest in determining whether it is possible to identify thresholds for chemical allergy. Here allergic sensitisation of the respiratory tract by chemicals is considered in this context. This is an important occupational health problem, being associated with rhinitis and asthma, and in addition provides toxicologists and risk assessors with a number of challenges. In common with all forms of allergic disease chemical respiratory allergy develops in two phases. In the first (induction) phase exposure to a chemical allergen (by an appropriate route of exposure) causes immunological priming and sensitisation of the respiratory tract. The second (elicitation) phase is triggered if a sensitised subject is exposed subsequently to the same chemical allergen via inhalation. A secondary immune response will be provoked in the respiratory tract resulting in inflammation and the signs and symptoms of a respiratory hypersensitivity reaction. In this article attention has focused on the identification of threshold values during the acquisition of sensitisation. Current mechanistic understanding of allergy is such that it can be assumed that the development of sensitisation (and also the elicitation of an allergic reaction) is a threshold phenomenon; there will be levels of exposure below which sensitisation will not be acquired. That is, all immune responses, including allergic sensitisation, have threshold requirement for the availability of antigen/allergen, below which a response will fail to develop. The issue addressed here is whether there are methods available or clinical/epidemiological data that permit the identification of such thresholds. This document reviews briefly relevant human studies of occupational asthma, and experimental models that have been developed (or are being developed) for the identification and characterisation of chemical respiratory allergens. The main conclusion drawn is that although there is evidence that the

Adaptation Method for Overall and Local Performances of Gas Turbine Engine Model

NASA Astrophysics Data System (ADS)

Kim, Sangjo; Kim, Kuisoon; Son, Changmin

2018-04-01

An adaptation method was proposed to improve the modeling accuracy of overall and local performances of gas turbine engine. The adaptation method was divided into two steps. First, the overall performance parameters such as engine thrust, thermal efficiency, and pressure ratio were adapted by calibrating compressor maps, and second, the local performance parameters such as temperature of component intersection and shaft speed were adjusted by additional adaptation factors. An optimization technique was used to find the correlation equation of adaptation factors for compressor performance maps. The multi-island genetic algorithm (MIGA) was employed in the present optimization. The correlations of local adaptation factors were generated based on the difference between the first adapted engine model and performance test data. The proposed adaptation method applied to a low-bypass ratio turbofan engine of 12,000 lb thrust. The gas turbine engine model was generated and validated based on the performance test data in the sea-level static condition. In flight condition at 20,000 ft and 0.9 Mach number, the result of adapted engine model showed improved prediction in engine thrust (overall performance parameter) by reducing the difference from 14.5 to 3.3%. Moreover, there was further improvement in the comparison of low-pressure turbine exit temperature (local performance parameter) as the difference is reduced from 3.2 to 0.4%.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition

PubMed Central

2016-01-01

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects’ clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech

Fixed or adapted conditioning intensity for repeated conditioned pain modulation.

PubMed

Hoegh, M; Petersen, K K; Graven-Nielsen, T

2017-12-29

Aims Conditioned pain modulation (CPM) is used to assess descending pain modulation through a test stimulation (TS) and a conditioning stimulation (CS). Due to potential carry-over effects, sequential CPM paradigms might alter the intensity of the CS, which potentially can alter the CPM-effect. This study aimed to investigate the difference between a fixed and adaptive CS intensity on CPM-effect. Methods On the dominant leg of 20 healthy subjects the cuff pressure detection threshold (PDT) was recorded as TS and the pain tolerance threshold (PTT) was assessed on the non-dominant leg for estimating the CS. The difference in PDT before and during CS defined the CPM-effect. The CPM-effect was assessed four times using a CS with intensities of 70% of baseline PTT (fixed) or 70% of PTT measured throughout the session (adaptive). Pain intensity of the conditioning stimulus was assessed on a numeric rating scale (NRS). Data were analyzed with repeated-measures ANOVA. Results No difference was found comparing the four PDTs assessed before CSs for the fixed and the adaptive paradigms. The CS pressure intensity for the adaptive paradigm was increasing during the four repeated assessments (P < 0.01). The pain intensity was similar during the fixed (NRS: 5.8±0.5) and the adjusted paradigm (NRS: 6.0±0.4). The CPM-effect was higher using the fixed condition compared with the adaptive condition (P < 0.05). Conclusions The current study found that sequential CPM paradigms using a fixed conditioning stimulus produced an increased CPM-effect compared with adaptive and increasing conditioning intensities.

Parallel 3D Mortar Element Method for Adaptive Nonconforming Meshes

NASA Technical Reports Server (NTRS)

Feng, Huiyu; Mavriplis, Catherine; VanderWijngaart, Rob; Biswas, Rupak

2004-01-01

High order methods are frequently used in computational simulation for their high accuracy. An efficient way to avoid unnecessary computation in smooth regions of the solution is to use adaptive meshes which employ fine grids only in areas where they are needed. Nonconforming spectral elements allow the grid to be flexibly adjusted to satisfy the computational accuracy requirements. The method is suitable for computational simulations of unsteady problems with very disparate length scales or unsteady moving features, such as heat transfer, fluid dynamics or flame combustion. In this work, we select the Mark Element Method (MEM) to handle the non-conforming interfaces between elements. A new technique is introduced to efficiently implement MEM in 3-D nonconforming meshes. By introducing an "intermediate mortar", the proposed method decomposes the projection between 3-D elements and mortars into two steps. In each step, projection matrices derived in 2-D are used. The two-step method avoids explicitly forming/deriving large projection matrices for 3-D meshes, and also helps to simplify the implementation. This new technique can be used for both h- and p-type adaptation. This method is applied to an unsteady 3-D moving heat source problem. With our new MEM implementation, mesh adaptation is able to efficiently refine the grid near the heat source and coarsen the grid once the heat source passes. The savings in computational work resulting from the dynamic mesh adaptation is demonstrated by the reduction of the the number of elements used and CPU time spent. MEM and mesh adaptation, respectively, bring irregularity and dynamics to the computer memory access pattern. Hence, they provide a good way to gauge the performance of computer systems when running scientific applications whose memory access patterns are irregular and unpredictable. We select a 3-D moving heat source problem as the Unstructured Adaptive (UA) grid benchmark, a new component of the NAS Parallel

Contrast adaptation induced by defocus - a possible error signal for emmetropization?

PubMed

Ohlendorf, Arne; Schaeffel, Frank

2009-01-01

To describe some features of contrast adaptation as induced by imposed positive or negative defocus. To study its time course and selectivity for the sign of the imposed defocus. Contrast adaptation, CA (here referred to as any change in supra-threshold contrast sensitivity) was induced by presenting a movie to the subjects on a computer screen at 1m distance for 10min, while the right eye was defocused by a trial lens (+4D (n=25); -4D (n=10); -2D (n=11 subjects). The PowerRefractor was used to track accommodation binocularly. Contrast sensitivity at threshold was measured by a method of adjustment with a Gabor patch of 1deg angular subtense, filled with 3.22cyc/deg sine wave grating presented on a computer screen at 1m distance on gray background (33cd/m(2)). Supra-threshold contrast sensitivity was quantified by an interocular contrast matching task, in which the subject had to match the contrast of the sine wave grating seen with the right eye with the contrast of a grating with fixed contrast of 0.1. (1) Contrast sensitivity thresholds were not lowered by previous viewing of defocused movies. (2) By wearing positive lenses, the supra-threshold contrast sensitivity in the right eye was raised by about 30% and remained elevated for at least 2min until baseline was reached after about 5min. (3) CA was induced only by positive, but not by negative lenses, even after the distance of the computer screen was taken into account (1m, equivalent to +1D). In five subjects, binocular accommodation was tracked over the full adaptation period. Accommodation appeared to focus the eye not wearing a lens, but short transient switches in focus to the lens wearing eye could not be entirely excluded. Transient contrast adaptation was found at 3.22cyc/deg when positive lenses were worn but not with negative lenses. This asymmetry is intriguing. While it may represent an epiphenomenon of physiological optics, further experiments are necessary to determine whether it could also trace

Quantitative evaluation method of the threshold adjustment and the flat field correction performances of hybrid photon counting pixel detectors

NASA Astrophysics Data System (ADS)

Medjoubi, K.; Dawiec, A.

2017-12-01

A simple method is proposed in this work for quantitative evaluation of the quality of the threshold adjustment and the flat-field correction of Hybrid Photon Counting pixel (HPC) detectors. This approach is based on the Photon Transfer Curve (PTC) corresponding to the measurement of the standard deviation of the signal in flat field images. Fixed pattern noise (FPN), easily identifiable in the curve, is linked to the residual threshold dispersion, sensor inhomogeneity and the remnant errors in flat fielding techniques. The analytical expression of the signal to noise ratio curve is developed for HPC and successfully used as a fit function applied to experimental data obtained with the XPAD detector. The quantitative evaluation of the FPN, described by the photon response non-uniformity (PRNU), is measured for different configurations (threshold adjustment method and flat fielding technique) and is demonstrated to be used in order to evaluate the best setting for having the best image quality from a commercial or a R&D detector.

Solving delay differential equations in S-ADAPT by method of steps.

PubMed

Bauer, Robert J; Mo, Gary; Krzyzanski, Wojciech

2013-09-01

S-ADAPT is a version of the ADAPT program that contains additional simulation and optimization abilities such as parametric population analysis. S-ADAPT utilizes LSODA to solve ordinary differential equations (ODEs), an algorithm designed for large dimension non-stiff and stiff problems. However, S-ADAPT does not have a solver for delay differential equations (DDEs). Our objective was to implement in S-ADAPT a DDE solver using the methods of steps. The method of steps allows one to solve virtually any DDE system by transforming it to an ODE system. The solver was validated for scalar linear DDEs with one delay and bolus and infusion inputs for which explicit analytic solutions were derived. Solutions of nonlinear DDE problems coded in S-ADAPT were validated by comparing them with ones obtained by the MATLAB DDE solver dde23. The estimation of parameters was tested on the MATLB simulated population pharmacodynamics data. The comparison of S-ADAPT generated solutions for DDE problems with the explicit solutions as well as MATLAB produced solutions which agreed to at least 7 significant digits. The population parameter estimates from using importance sampling expectation-maximization in S-ADAPT agreed with ones used to generate the data. Published by Elsevier Ireland Ltd.

An adaptive tensor voting algorithm combined with texture spectrum

NASA Astrophysics Data System (ADS)

Wang, Gang; Su, Qing-tang; Lü, Gao-huan; Zhang, Xiao-feng; Liu, Yu-huan; He, An-zhi

2015-01-01

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

[Application of adaptive canceling methods in temperature control in ultrasonic therapeutical treatment].

PubMed

Deng, Jun; Liu, Du-ren

2002-12-01

Objective. To improve the quality of ultrasonic therapeutical treatment by improving the accuracy of temperature control. Method. Adaptive canceling methods were used to reduce the noise of temperature signal gained, and enhance signal-to-noise ratio. Result. The test's result corresponds basically to the theoretical curve. Conclusion. Adaptive canceling methods can be applied to clinic treatment.

A novel fusion method of improved adaptive LTP and two-directional two-dimensional PCA for face feature extraction

NASA Astrophysics Data System (ADS)

Luo, Yuan; Wang, Bo-yu; Zhang, Yi; Zhao, Li-ming

2018-03-01

In this paper, under different illuminations and random noises, focusing on the local texture feature's defects of a face image that cannot be completely described because the threshold of local ternary pattern (LTP) cannot be calculated adaptively, a local three-value model of improved adaptive local ternary pattern (IALTP) is proposed. Firstly, the difference function between the center pixel and the neighborhood pixel weight is established to obtain the statistical characteristics of the central pixel and the neighborhood pixel. Secondly, the adaptively gradient descent iterative function is established to calculate the difference coefficient which is defined to be the threshold of the IALTP operator. Finally, the mean and standard deviation of the pixel weight of the local region are used as the coding mode of IALTP. In order to reflect the overall properties of the face and reduce the dimension of features, the two-directional two-dimensional PCA ((2D)2PCA) is adopted. The IALTP is used to extract local texture features of eyes and mouth area. After combining the global features and local features, the fusion features (IALTP+) are obtained. The experimental results on the Extended Yale B and AR standard face databases indicate that under different illuminations and random noises, the algorithm proposed in this paper is more robust than others, and the feature's dimension is smaller. The shortest running time reaches 0.329 6 s, and the highest recognition rate reaches 97.39%.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

PubMed Central

Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

2016-01-01

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter—describing somatic integration—and the spike-history filter—accounting for spike-frequency adaptation—dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations. PMID:26907675

SU-C-9A-01: Parameter Optimization in Adaptive Region-Growing for Tumor Segmentation in PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, S; Huazhong University of Science and Technology, Wuhan, Hubei; Xue, M

Purpose: To design a reliable method to determine the optimal parameter in the adaptive region-growing (ARG) algorithm for tumor segmentation in PET. Methods: The ARG uses an adaptive similarity criterion m - fσ ≤ I-PET ≤ m + fσ, so that a neighboring voxel is appended to the region based on its similarity to the current region. When increasing the relaxing factor f (f ≥ 0), the resulting volumes monotonically increased with a sharp increase when the region just grew into the background. The optimal f that separates the tumor from the background is defined as the first point withmore » the local maximum curvature on an Error function fitted to the f-volume curve. The ARG was tested on a tumor segmentation Benchmark that includes ten lung cancer patients with 3D pathologic tumor volume as ground truth. For comparison, the widely used 42% and 50% SUVmax thresholding, Otsu optimal thresholding, Active Contours (AC), Geodesic Active Contours (GAC), and Graph Cuts (GC) methods were tested. The dice similarity index (DSI), volume error (VE), and maximum axis length error (MALE) were calculated to evaluate the segmentation accuracy. Results: The ARG provided the highest accuracy among all tested methods. Specifically, the ARG has an average DSI, VE, and MALE of 0.71, 0.29, and 0.16, respectively, better than the absolute 42% thresholding (DSI=0.67, VE= 0.57, and MALE=0.23), the relative 42% thresholding (DSI=0.62, VE= 0.41, and MALE=0.23), the absolute 50% thresholding (DSI=0.62, VE=0.48, and MALE=0.21), the relative 50% thresholding (DSI=0.48, VE=0.54, and MALE=0.26), OTSU (DSI=0.44, VE=0.63, and MALE=0.30), AC (DSI=0.46, VE= 0.85, and MALE=0.47), GAC (DSI=0.40, VE= 0.85, and MALE=0.46) and GC (DSI=0.66, VE= 0.54, and MALE=0.21) methods. Conclusions: The results suggest that the proposed method reliably identified the optimal relaxing factor in ARG for tumor segmentation in PET. This work was supported in part by National Cancer Institute Grant R01 CA172638

User-relevant, threshold-specific observations of climate change

NASA Astrophysics Data System (ADS)

Stainforth, Dave; Chapman, Sandra; Watkins, Nicholas

2014-05-01

Users of climate information look for details of changing climate at local scales (to inform specific activities) and on the geographical patterns of such changes (to prioritise adaptation investments). They often have user-specific thresholds of vulnerability so the changes of interest must refer to such thresholds or to the related quantile of the climatic distribution. A method for providing such information from timeseries of temperature data has recently been published [1] along with maps of changes at thresholds and quantiles [2] derived from the European Observational dataset E-Obs [3]. In this presentation we will do two things. First we will discuss the opportunities to tailor such methods to provide user-specific information through climate services, using illustrations from the existing methodology applied to daily maximum and minimum temperatures [1,2]. Second we will present new results on threshold specific observed changes in precipitation. The methodology for precipitation is related to that which has been applied to temperature but has been developed to handle the characteristics of precipitation distributions. The results identify some regions with systematic increases in precipitation on the seasonally wettest days and others which show drying across all days, on a seasonal basis. We will present the geographic locations and precipitation thresholds where strong signals of changes are seen across Europe. The coherency of such results and the methodology used to process the observational data will be discussed. We will also highlight the justifications for having confidence in the results in some regions and at some thresholds while having a lack of confidence in others. Such information should be an important element of any climate services. It is worth noting that here "wettest days" refers to events which are uncommon within a season (e.g. one in ~20 wet days). This is in contrast and complementary to, for instance, the one in a hundred year

An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography

PubMed Central

Hu, Hai; Guo, Shengxin; Liu, Ran

2017-01-01

Artifacts removal and rhythms extraction from electroencephalography (EEG) signals are important for portable and wearable EEG recording devices. Incorporating a novel grouping rule, we proposed an adaptive singular spectrum analysis (SSA) method for artifacts removal and rhythms extraction. Based on the EEG signal amplitude, the grouping rule determines adaptively the first one or two SSA reconstructed components as artifacts and removes them. The remaining reconstructed components are then grouped based on their peak frequencies in the Fourier transform to extract the desired rhythms. The grouping rule thus enables SSA to be adaptive to EEG signals containing different levels of artifacts and rhythms. The simulated EEG data based on the Markov Process Amplitude (MPA) EEG model and the experimental EEG data in the eyes-open and eyes-closed states were used to verify the adaptive SSA method. Results showed a better performance in artifacts removal and rhythms extraction, compared with the wavelet decomposition (WDec) and another two recently reported SSA methods. Features of the extracted alpha rhythms using adaptive SSA were calculated to distinguish between the eyes-open and eyes-closed states. Results showed a higher accuracy (95.8%) than those of the WDec method (79.2%) and the infinite impulse response (IIR) filtering method (83.3%). PMID:28674650

Experimental and environmental factors affect spurious detection of ecological thresholds

USGS Publications Warehouse

Daily, Jonathan P.; Hitt, Nathaniel P.; Smith, David; Snyder, Craig D.

2012-01-01

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (τ) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.

A modified adjoint-based grid adaptation and error correction method for unstructured grid

NASA Astrophysics Data System (ADS)

Cui, Pengcheng; Li, Bin; Tang, Jing; Chen, Jiangtao; Deng, Youqi

2018-05-01

Grid adaptation is an important strategy to improve the accuracy of output functions (e.g. drag, lift, etc.) in computational fluid dynamics (CFD) analysis and design applications. This paper presents a modified robust grid adaptation and error correction method for reducing simulation errors in integral outputs. The procedure is based on discrete adjoint optimization theory in which the estimated global error of output functions can be directly related to the local residual error. According to this relationship, local residual error contribution can be used as an indicator in a grid adaptation strategy designed to generate refined grids for accurately estimating the output functions. This grid adaptation and error correction method is applied to subsonic and supersonic simulations around three-dimensional configurations. Numerical results demonstrate that the sensitive grids to output functions are detected and refined after grid adaptation, and the accuracy of output functions is obviously improved after error correction. The proposed grid adaptation and error correction method is shown to compare very favorably in terms of output accuracy and computational efficiency relative to the traditional featured-based grid adaptation.

A new iterative triclass thresholding technique in image segmentation.

PubMed

Cai, Hongmin; Yang, Zhong; Cao, Xinhua; Xia, Weiming; Xu, Xiaoyin

2014-03-01

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.

New method to evaluate the 7Li(p, n)7Be reaction near threshold

NASA Astrophysics Data System (ADS)

Herrera, María S.; Moreno, Gustavo A.; Kreiner, Andrés J.

2015-04-01

In this work a complete description of the 7Li(p, n)7Be reaction near threshold is given using center-of-mass and relative coordinates. It is shown that this standard approach, not used before in this context, leads to a simple mathematical representation which gives easy access to all relevant quantities in the reaction and allows a precise numerical implementation. It also allows in a simple way to include proton beam-energy spread affects. The method, implemented as a C++ code, was validated both with numerical and experimental data finding a good agreement. This tool is also used here to analyze scattered published measurements such as (p, n) cross sections, differential and total neutron yields for thick targets. Using these data we derive a consistent set of parameters to evaluate neutron production near threshold. Sensitivity of the results to data uncertainty and the possibility of incorporating new measurements are also discussed.

Determining electrically evoked compound action potential thresholds: a comparison of computer versus human analysis methods.

PubMed

Glassman, E Katelyn; Hughes, Michelle L

2013-01-01

Current cochlear implants (CIs) have telemetry capabilities for measuring the electrically evoked compound action potential (ECAP). Neural Response Telemetry (Cochlear) and Neural Response Imaging (Advanced Bionics [AB]) can measure ECAP responses across a range of stimulus levels to obtain an amplitude growth function. Software-specific algorithms automatically mark the leading negative peak, N1, and the following positive peak/plateau, P2, and apply linear regression to estimate ECAP threshold. Alternatively, clinicians may apply expert judgments to modify the peak markers placed by the software algorithms, or use visual detection to identify the lowest level yielding a measurable ECAP response. The goals of this study were to: (1) assess the variability between human and computer decisions for (a) marking N1 and P2 and (b) determining linear-regression threshold (LRT) and visual-detection threshold (VDT); and (2) compare LRT and VDT methods within and across human- and computer-decision methods. ECAP amplitude-growth functions were measured for three electrodes in each of 20 ears (10 Cochlear Nucleus® 24RE/CI512, and 10 AB CII/90K). LRT, defined as the current level yielding an ECAP with zero amplitude, was calculated for both computer- (C-LRT) and human-picked peaks (H-LRT). VDT, defined as the lowest level resulting in a measurable ECAP response, was also calculated for both computer- (C-VDT) and human-picked peaks (H-VDT). Because Neural Response Imaging assigns peak markers to all waveforms but does not include waveforms with amplitudes less than 20 μV in its regression calculation, C-VDT for AB subjects was defined as the lowest current level yielding an amplitude of 20 μV or more. Overall, there were significant correlations between human and computer decisions for peak-marker placement, LRT, and VDT for both manufacturers (r = 0.78-1.00, p < 0.001). For Cochlear devices, LRT and VDT correlated equally well for both computer- and human-picked peaks (r

Method for Assessing Contrast Performance under Lighting Conditions such as Entering a Tunnel on Sunny Day.

PubMed

Huang, Y; Menozzi, M

2015-04-01

transition from 2000 to 8 cd/m2. By raising the dark adaption luminance level from 8 to 60 cd/m2 in the stronger transition case, the contrast detection threshold was then improved by a factor of four. Another main finding showed that for the adaptation process from strong glare stimuli to the dark adaptation, a peak deterioration in contrast sensitivity occurred at the light adaptation level of 6000 cd/m2. Comparing the contrast performance assessed by the proposed test with that of the nyktometer test, there was no clear correlation between the two methods. Our suggested method to assess dark adaptation performance proved to be practical in use and, since the patient does not have to spend a long time to attain complete dark adaptation, the method required a short time for measurement. Our negative experience in the use of the myktometer was in agreement with reported experience in the literature. Georg Thieme Verlag KG Stuttgart · New York.

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

Self-adaptive demodulation for polarization extinction ratio in distributed polarization coupling.

PubMed

Zhang, Hongxia; Ren, Yaguang; Liu, Tiegen; Jia, Dagong; Zhang, Yimo

2013-06-20

A self-adaptive method for distributed polarization extinction ratio (PER) demodulation is demonstrated. It is characterized by dynamic PER threshold coupling intensity (TCI) and nonuniform PER iteration step length (ISL). Based on the preset PER calculation accuracy and original distribution coupling intensity, TCI and ISL can be made self-adaptive to determine contributing coupling points inside the polarizing devices. Distributed PER is calculated by accumulating those coupling points automatically and selectively. Two different kinds of polarization-maintaining fibers are tested, and PERs are obtained after merely 3-5 iterations using the proposed method. Comparison experiments with Thorlabs commercial instrument are also conducted, and results show high consistency. In addition, the optimum preset PER calculation accuracy of 0.05 dB is obtained through many repeated experiments.

Adaptive finite element methods for two-dimensional problems in computational fracture mechanics

NASA Technical Reports Server (NTRS)

Min, J. B.; Bass, J. M.; Spradley, L. W.

1994-01-01

Some recent results obtained using solution-adaptive finite element methods in two-dimensional problems in linear elastic fracture mechanics are presented. The focus is on the basic issue of adaptive finite element methods for validating the new methodology by computing demonstration problems and comparing the stress intensity factors to analytical results.

a New Multi-Spectral Threshold Normalized Difference Water Index Mst-Ndwi Water Extraction Method - a Case Study in Yanhe Watershed

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhao, H.; Hao, H.; Wang, C.

2018-05-01

Accurate remote sensing water extraction is one of the primary tasks of watershed ecological environment study. Since the Yanhe water system has typical characteristics of a small water volume and narrow river channel, which leads to the difficulty for conventional water extraction methods such as Normalized Difference Water Index (NDWI). A new Multi-Spectral Threshold segmentation of the NDWI (MST-NDWI) water extraction method is proposed to achieve the accurate water extraction in Yanhe watershed. In the MST-NDWI method, the spectral characteristics of water bodies and typical backgrounds on the Landsat/TM images have been evaluated in Yanhe watershed. The multi-spectral thresholds (TM1, TM4, TM5) based on maximum-likelihood have been utilized before NDWI water extraction to realize segmentation for a division of built-up lands and small linear rivers. With the proposed method, a water map is extracted from the Landsat/TM images in 2010 in China. An accuracy assessment is conducted to compare the proposed method with the conventional water indexes such as NDWI, Modified NDWI (MNDWI), Enhanced Water Index (EWI), and Automated Water Extraction Index (AWEI). The result shows that the MST-NDWI method generates better water extraction accuracy in Yanhe watershed and can effectively diminish the confusing background objects compared to the conventional water indexes. The MST-NDWI method integrates NDWI and Multi-Spectral Threshold segmentation algorithms, with richer valuable information and remarkable results in accurate water extraction in Yanhe watershed.

An adaptive grid scheme using the boundary element method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Munipalli, R.; Anderson, D.A.

1996-09-01

A technique to solve the Poisson grid generation equations by Green`s function related methods has been proposed, with the source terms being purely position dependent. The use of distributed singularities in the flow domain coupled with the boundary element method (BEM) formulation is presented in this paper as a natural extension of the Green`s function method. This scheme greatly simplifies the adaption process. The BEM reduces the dimensionality of the given problem by one. Internal grid-point placement can be achieved for a given boundary distribution by adding continuous and discrete source terms in the BEM formulation. A distribution of vortexmore » doublets is suggested as a means of controlling grid-point placement and grid-line orientation. Examples for sample adaption problems are presented and discussed. 15 refs., 20 figs.« less

Peripheral absolute threshold spectral sensitivity in retinitis pigmentosa.

PubMed Central

Massof, R W; Johnson, M A; Finkelstein, D

1981-01-01

Dark-adapted spectral sensitivities were measured in the peripheral retinas of 38 patients diagnosed as having typical retinitis pigmentosa (RP) and in 3 normal volunteers. The patients included those having autosomal dominant and autosomal recessive inheritance patterns. Results were analysed by comparisons with the CIE standard scotopic spectral visibility function and with Judd's modification of the photopic spectral visibility function, with consideration of contributions from changes in spectral transmission of preretinal media. The data show 3 general patterns. One group of patients had absolute threshold spectral sensitivities that were fit by Judd's photopic visibility curve. Absolute threshold spectral sensitivities for a second group of patients were fit by a normal scotopic spectral visibility curve. The third group of patients had absolute threshold spectral sensitivities that were fit by a combination of scotopic and photopic spectral visibility curves. The autosomal dominant and autosomal recessive modes of inheritance were represented in each group of patients. These data indicate that RP patients have normal rod and/or cone spectral sensitivities, and support the subclassification of patients described previously by Massof and Finkelstein. PMID:7459312

Correspondence between evoked vocal responses and auditory thresholds in Pleurodema thaul (Amphibia; Leptodactylidae).

PubMed

Penna, Mario; Velásquez, Nelson; Solís, Rigoberto

2008-04-01

Thresholds for evoked vocal responses and thresholds of multiunit midbrain auditory responses to pure tones and synthetic calls were investigated in males of Pleurodema thaul, as behavioral thresholds well above auditory sensitivity have been reported for other anurans. Thresholds for evoked vocal responses to synthetic advertisement calls played back at increasing intensity averaged 43 dB RMS SPL (range 31-52 dB RMS SPL), measured at the subjects' position. Number of pulses increased with stimulus intensities, reaching a plateau at about 18-39 dB above threshold and decreased at higher intensities. Latency to call followed inverse trends relative to number of pulses. Neural audiograms yielded an average best threshold in the high frequency range of 46.6 dB RMS SPL (range 41-51 dB RMS SPL) and a center frequency of 1.9 kHz (range 1.7-2.6 kHz). Auditory thresholds for a synthetic call having a carrier frequency of 2.1 kHz averaged 44 dB RMS SPL (range 39-47 dB RMS SPL). The similarity between thresholds for advertisement calling and auditory thresholds for the advertisement call indicates that male P. thaul use the full extent of their auditory sensitivity in acoustic interactions, likely an evolutionary adaptation allowing chorusing activity in low-density aggregations.

Smart algorithms and adaptive methods in computational fluid dynamics

NASA Astrophysics Data System (ADS)

Tinsley Oden, J.

1989-05-01

A review is presented of the use of smart algorithms which employ adaptive methods in processing large amounts of data in computational fluid dynamics (CFD). Smart algorithms use a rationally based set of criteria for automatic decision making in an attempt to produce optimal simulations of complex fluid dynamics problems. The information needed to make these decisions is not known beforehand and evolves in structure and form during the numerical solution of flow problems. Once the code makes a decision based on the available data, the structure of the data may change, and criteria may be reapplied in order to direct the analysis toward an acceptable end. Intelligent decisions are made by processing vast amounts of data that evolve unpredictably during the calculation. The basic components of adaptive methods and their application to complex problems of fluid dynamics are reviewed. The basic components of adaptive methods are: (1) data structures, that is what approaches are available for modifying data structures of an approximation so as to reduce errors; (2) error estimation, that is what techniques exist for estimating error evolution in a CFD calculation; and (3) solvers, what algorithms are available which can function in changing meshes. Numerical examples which demonstrate the viability of these approaches are presented.

Free-energy landscapes from adaptively biased methods: Application to quantum systems

NASA Astrophysics Data System (ADS)

Calvo, F.

2010-10-01

Several parallel adaptive biasing methods are applied to the calculation of free-energy pathways along reaction coordinates, choosing as a difficult example the double-funnel landscape of the 38-atom Lennard-Jones cluster. In the case of classical statistics, the Wang-Landau and adaptively biased molecular-dynamics (ABMD) methods are both found efficient if multiple walkers and replication and deletion schemes are used. An extension of the ABMD technique to quantum systems, implemented through the path-integral MD framework, is presented and tested on Ne38 against the quantum superposition method.

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Thresholding histogram equalization.

PubMed

Chuang, K S; Chen, S; Hwang, I M

2001-12-01

The drawbacks of adaptive histogram equalization techniques are the loss of definition on the edges of the object and overenhancement of noise in the images. These drawbacks can be avoided if the noise is excluded in the equalization transformation function computation. A method has been developed to separate the histogram into zones, each with its own equalization transformation. This method can be used to suppress the nonanatomic noise and enhance only certain parts of the object. This method can be combined with other adaptive histogram equalization techniques. Preliminary results indicate that this method can produce images with superior contrast.

A constrained Delaunay discretization method for adaptively meshing highly discontinuous geological media

NASA Astrophysics Data System (ADS)

Wang, Yang; Ma, Guowei; Ren, Feng; Li, Tuo

2017-12-01

A constrained Delaunay discretization method is developed to generate high-quality doubly adaptive meshes of highly discontinuous geological media. Complex features such as three-dimensional discrete fracture networks (DFNs), tunnels, shafts, slopes, boreholes, water curtains, and drainage systems are taken into account in the mesh generation. The constrained Delaunay triangulation method is used to create adaptive triangular elements on planar fractures. Persson's algorithm (Persson, 2005), based on an analogy between triangular elements and spring networks, is enriched to automatically discretize a planar fracture into mesh points with varying density and smooth-quality gradient. The triangulated planar fractures are treated as planar straight-line graphs (PSLGs) to construct piecewise-linear complex (PLC) for constrained Delaunay tetrahedralization. This guarantees the doubly adaptive characteristic of the resulted mesh: the mesh is adaptive not only along fractures but also in space. The quality of elements is compared with the results from an existing method. It is verified that the present method can generate smoother elements and a better distribution of element aspect ratios. Two numerical simulations are implemented to demonstrate that the present method can be applied to various simulations of complex geological media that contain a large number of discontinuities.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Wavelet threshold method of resolving noise interference in periodic short-impulse signals chaotic detection

NASA Astrophysics Data System (ADS)

Deng, Ke; Zhang, Lu; Luo, Mao-Kang

2010-03-01

The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises (even white noise). In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.

Nonlinear threshold effect in the Z-scan method of characterizing limiters for high-intensity laser light

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tereshchenko, S. A., E-mail: tsa@miee.ru; Savelyev, M. S.; Podgaetsky, V. M.

A threshold model is described which permits one to determine the properties of limiters for high-powered laser light. It takes into account the threshold characteristics of the nonlinear optical interaction between the laser beam and the limiter working material. The traditional non-threshold model is a particular case of the threshold model when the limiting threshold is zero. The nonlinear characteristics of carbon nanotubes in liquid and solid media are obtained from experimental Z-scan data. Specifically, the nonlinear threshold effect was observed for aqueous dispersions of nanotubes, but not for nanotubes in solid polymethylmethacrylate. The threshold model fits the experimental Z-scanmore » data better than the non-threshold model. Output characteristics were obtained that integrally describe the nonlinear properties of the optical limiters.« less

Closed-loop adaptation of neurofeedback based on mental effort facilitates reinforcement learning of brain self-regulation.

PubMed

Bauer, Robert; Fels, Meike; Royter, Vladislav; Raco, Valerio; Gharabaghi, Alireza

2016-09-01

Considering self-rated mental effort during neurofeedback may improve training of brain self-regulation. Twenty-one healthy, right-handed subjects performed kinesthetic motor imagery of opening their left hand, while threshold-based classification of beta-band desynchronization resulted in proprioceptive robotic feedback. The experiment consisted of two blocks in a cross-over design. The participants rated their perceived mental effort nine times per block. In the adaptive block, the threshold was adjusted on the basis of these ratings whereas adjustments were carried out at random in the other block. Electroencephalography was used to examine the cortical activation patterns during the training sessions. The perceived mental effort was correlated with the difficulty threshold of neurofeedback training. Adaptive threshold-setting reduced mental effort and increased the classification accuracy and positive predictive value. This was paralleled by an inter-hemispheric cortical activation pattern in low frequency bands connecting the right frontal and left parietal areas. Optimal balance of mental effort was achieved at thresholds significantly higher than maximum classification accuracy. Rating of mental effort is a feasible approach for effective threshold-adaptation during neurofeedback training. Closed-loop adaptation of the neurofeedback difficulty level facilitates reinforcement learning of brain self-regulation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Genetic variance of tolerance and the toxicant threshold model.

PubMed

Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

2012-04-01

A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change. Copyright © 2012 SETAC.

A multilevel correction adaptive finite element method for Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Hu, Guanghui; Xie, Hehu; Xu, Fei

2018-02-01

In this paper, an adaptive finite element method is proposed for solving Kohn-Sham equation with the multilevel correction technique. In the method, the Kohn-Sham equation is solved on a fixed and appropriately coarse mesh with the finite element method in which the finite element space is kept improving by solving the derived boundary value problems on a series of adaptively and successively refined meshes. A main feature of the method is that solving large scale Kohn-Sham system is avoided effectively, and solving the derived boundary value problems can be handled efficiently by classical methods such as the multigrid method. Hence, the significant acceleration can be obtained on solving Kohn-Sham equation with the proposed multilevel correction technique. The performance of the method is examined by a variety of numerical experiments.

Standardised method of determining vibratory perception thresholds for diagnosis and screening in neurological investigation.

PubMed Central

Goldberg, J M; Lindblom, U

1979-01-01

Vibration threshold determinations were made by means of an electromagnetic vibrator at three sites (carpal, tibial, and tarsal), which were primarily selected for examining patients with polyneuropathy. Because of the vast variation demonstrated for both vibrator output and tissue damping, the thresholds were expressed in terms of amplitude of stimulator movement measured by means of an accelerometer, instead of applied voltage which is commonly used. Statistical analysis revealed a higher power of discimination for amplitude measurements at all three stimulus sites. Digital read-out gave the best statistical result and was also most practical. Reference values obtained from 110 healthy males, 10 to 74 years of age, were highly correlated with age for both upper and lower extremities. The variance of the vibration perception threshold was less than that of the disappearance threshold, and determination of the perception threshold alone may be sufficient in most cases. PMID:501379

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

Estimating phonation threshold pressure.

PubMed

Fisher, K V; Swank, P R

1997-10-01

Phonation threshold pressure (PTP) is the minimum subglottal pressure required to initiate vocal fold oscillation. Although potentially useful clinically, PTP is difficult to estimate noninvasively because of limitations to vocal motor control near the threshold of soft phonation. Previous investigators observed, for example, that trained subjects were unable to produce flat, consistent oral pressure peaks during/pae/syllable strings when they attempted to phonate as softly as possible (Verdolini-Marston, Titze, & Druker, 1990). The present study aimed to determine if nasal airflow or vowel context affected phonation threshold pressure as estimated from oral pressure (Smitheran & Hixon, 1981) in 5 untrained female speakers with normal velopharyngeal and voice function. Nasal airflow during /p/occlusion was observed for 3 of 5 participants when they attempted to phonate near threshold pressure. When the nose was occluded, nasal airflow was reduced or eliminated during /p/;however, individuals then evidenced compensatory changes in glottal adduction and/or respiratory effort that may be expected to alter PTP estimates. Results demonstrate the importance of monitoring nasal flow (or the flow zero point in undivided masks) when obtaining PTP measurements noninvasively. Results also highlight the need to pursue improved methods for noninvasive estimation of PTP.

Implementation of an improved adaptive-implicit method in a thermal compositional simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, T.B.

1988-11-01

A multicomponent thermal simulator with an adaptive-implicit-method (AIM) formulation/inexact-adaptive-Newton (IAN) method is presented. The final coefficient matrix retains the original banded structure so that conventional iterative methods can be used. Various methods for selection of the eliminated unknowns are tested. AIM/IAN method has a lower work count per Newtonian iteration than fully implicit methods, but a wrong choice of unknowns will result in excessive Newtonian iterations. For the problems tested, the residual-error method described in the paper for selecting implicit unknowns, together with the IAN method, had an improvement of up to 28% of the CPU time over the fullymore » implicit method.« less

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

An adaptive approach to the physical annealing strategy for simulated annealing

NASA Astrophysics Data System (ADS)

Hasegawa, M.

2013-02-01

A new and reasonable method for adaptive implementation of simulated annealing (SA) is studied on two types of random traveling salesman problems. The idea is based on the previous finding on the search characteristics of the threshold algorithms, that is, the primary role of the relaxation dynamics in their finite-time optimization process. It is shown that the effective temperature for optimization can be predicted from the system's behavior analogous to the stabilization phenomenon occurring in the heating process starting from a quenched solution. The subsequent slow cooling near the predicted point draws out the inherent optimizing ability of finite-time SA in more straightforward manner than the conventional adaptive approach.

Is heart rate variability a feasible method to determine anaerobic threshold in progressive resistance exercise in coronary artery disease?

PubMed Central

Sperling, Milena P. R.; Simões, Rodrigo P.; Caruso, Flávia C. R.; Mendes, Renata G.; Arena, Ross; Borghi-Silva, Audrey

2016-01-01

ABSTRACT Background Recent studies have shown that the magnitude of the metabolic and autonomic responses during progressive resistance exercise (PRE) is associated with the determination of the anaerobic threshold (AT). AT is an important parameter to determine intensity in dynamic exercise. Objectives To investigate the metabolic and cardiac autonomic responses during dynamic resistance exercise in patients with Coronary Artery Disease (CAD). Method Twenty men (age = 63±7 years) with CAD [Left Ventricular Ejection Fraction (LVEF) = 60±10%] underwent a PRE protocol on a leg press until maximal exertion. The protocol began at 10% of One Repetition Maximum Test (1-RM), with subsequent increases of 10% until maximal exhaustion. Heart Rate Variability (HRV) indices from Poincaré plots (SD1, SD2, SD1/SD2) and time domain (rMSSD and RMSM), and blood lactate were determined at rest and during PRE. Results Significant alterations in HRV and blood lactate were observed starting at 30% of 1-RM (p<0.05). Bland-Altman plots revealed a consistent agreement between blood lactate threshold (LT) and rMSSD threshold (rMSSDT) and between LT and SD1 threshold (SD1T). Relative values of 1-RM in all LT, rMSSDT and SD1T did not differ (29%±5 vs 28%±5 vs 29%±5 Kg, respectively). Conclusion HRV during PRE could be a feasible noninvasive method of determining AT in CAD patients to plan intensities during cardiac rehabilitation. PMID:27556384

Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control

NASA Technical Reports Server (NTRS)

Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)

2015-01-01

Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

Protecting the entanglement of twisted photons by adaptive optics

NASA Astrophysics Data System (ADS)

Leonhard, Nina; Sorelli, Giacomo; Shatokhin, Vyacheslav N.; Reinlein, Claudia; Buchleitner, Andreas

2018-01-01

We study the efficiency of adaptive optics (AO) correction for the free-space propagation of entangled photonic orbital-angular-momentum (OAM) qubit states to reverse moderate atmospheric turbulence distortions. We show that AO can significantly reduce crosstalk to modes within and outside the encoding subspace and thereby stabilize entanglement against turbulence. This method establishes a reliable quantum channel for OAM photons in turbulence, and it enhances the threshold turbulence strength for secure quantum communication by at least a factor 2.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

When do Indians feel hot? Internet searches indicate seasonality suppresses adaptation to heat

NASA Astrophysics Data System (ADS)

Singh, Tanya; Siderius, Christian; Van der Velde, Ype

2018-05-01

In a warming world an increasing number of people are being exposed to heat, making a comfortable thermal environment an important need. This study explores the potential of using Regional Internet Search Frequencies (RISF) for air conditioning devices as an indicator for thermal discomfort (i.e. dissatisfaction with the thermal environment) with the aim to quantify the adaptation potential of individuals living across different climate zones and at the high end of the temperature range, in India, where access to health data is limited. We related RISF for the years 2011–2015 to daily daytime outdoor temperature in 17 states and determined at which temperature RISF for air conditioning starts to peak, i.e. crosses a ‘heat threshold’, in each state. Using the spatial variation in heat thresholds, we explored whether people continuously exposed to higher temperatures show a lower response to heat extremes through adaptation (e.g. physiological, behavioural or psychological). State-level heat thresholds ranged from 25.9 °C in Madhya Pradesh to 31.0 °C in Orissa. Local adaptation was found to occur at state level: the higher the average temperature in a state, the higher the heat threshold; and the higher the intra-annual temperature range (warmest minus coldest month) the lower the heat threshold. These results indicate there is potential within India to adapt to warmer temperatures, but that a large intra-annual temperature variability attenuates this potential to adapt to extreme heat. This winter ‘reset’ mechanism should be taken into account when assessing the impact of global warming, with changes in minimum temperatures being an important factor in addition to the change in maximum temperatures itself. Our findings contribute to a better understanding of local heat thresholds and people’s adaptive capacity, which can support the design of local thermal comfort standards and early heat warning systems.

[The analysis of threshold effect using Empower Stats software].

PubMed

Lin, Lin; Chen, Chang-zhong; Yu, Xiao-dan

2013-11-01

In many studies about biomedical research factors influence on the outcome variable, it has no influence or has a positive effect within a certain range. Exceeding a certain threshold value, the size of the effect and/or orientation will change, which called threshold effect. Whether there are threshold effects in the analysis of factors (x) on the outcome variable (y), it can be observed through a smooth curve fitting to see whether there is a piecewise linear relationship. And then using segmented regression model, LRT test and Bootstrap resampling method to analyze the threshold effect. Empower Stats software developed by American X & Y Solutions Inc has a threshold effect analysis module. You can input the threshold value at a given threshold segmentation simulated data. You may not input the threshold, but determined the optimal threshold analog data by the software automatically, and calculated the threshold confidence intervals.

A comparison of locally adaptive multigrid methods: LDC, FAC and FIC

NASA Technical Reports Server (NTRS)

Khadra, Khodor; Angot, Philippe; Caltagirone, Jean-Paul

1993-01-01

This study is devoted to a comparative analysis of three 'Adaptive ZOOM' (ZOom Overlapping Multi-level) methods based on similar concepts of hierarchical multigrid local refinement: LDC (Local Defect Correction), FAC (Fast Adaptive Composite), and FIC (Flux Interface Correction)--which we proposed recently. These methods are tested on two examples of a bidimensional elliptic problem. We compare, for V-cycle procedures, the asymptotic evolution of the global error evaluated by discrete norms, the corresponding local errors, and the convergence rates of these algorithms.

Defining indoor heat thresholds for health in the UK.

PubMed

Anderson, Mindy; Carmichael, Catriona; Murray, Virginia; Dengel, Andy; Swainson, Michael

2013-05-01

It has been recognised that as outdoor ambient temperatures increase past a particular threshold, so do mortality/morbidity rates. However, similar thresholds for indoor temperatures have not yet been identified. Due to a warming climate, the non-sustainability of air conditioning as a solution, and the desire for more energy-efficient airtight homes, thresholds for indoor temperature should be defined as a public health issue. The aim of this paper is to outline the need for indoor heat thresholds and to establish if they can be identified. Our objectives include: describing how indoor temperature is measured; highlighting threshold measurements and indices; describing adaptation to heat; summary of the risk of susceptible groups to heat; reviewing the current evidence on the link between sleep, heat and health; exploring current heat and health warning systems and thresholds; exploring the built environment and the risk of overheating; and identifying the gaps in current knowledge and research. A global literature search of key databases was conducted using a pre-defined set of keywords to retrieve peer-reviewed and grey literature. The paper will apply the findings to the context of the UK. A summary of 96 articles, reports, government documents and textbooks were analysed and a gap analysis was conducted. Evidence on the effects of indoor heat on health implies that buildings are modifiers of the effect of climate on health outcomes. Personal exposure and place-based heat studies showed the most significant correlations between indoor heat and health outcomes. However, the data are sparse and inconclusive in terms of identifying evidence-based definitions for thresholds. Further research needs to be conducted in order to provide an evidence base for threshold determination. Indoor and outdoor heat are related but are different in terms of language and measurement. Future collaboration between the health and building sectors is needed to develop a common

Experimental Design and Primary Data Analysis Methods for Comparing Adaptive Interventions

PubMed Central

Nahum-Shani, Inbal; Qian, Min; Almirall, Daniel; Pelham, William E.; Gnagy, Beth; Fabiano, Greg; Waxmonsky, Jim; Yu, Jihnhee; Murphy, Susan

2013-01-01

In recent years, research in the area of intervention development is shifting from the traditional fixed-intervention approach to adaptive interventions, which allow greater individualization and adaptation of intervention options (i.e., intervention type and/or dosage) over time. Adaptive interventions are operationalized via a sequence of decision rules that specify how intervention options should be adapted to an individual’s characteristics and changing needs, with the general aim to optimize the long-term effectiveness of the intervention. Here, we review adaptive interventions, discussing the potential contribution of this concept to research in the behavioral and social sciences. We then propose the sequential multiple assignment randomized trial (SMART), an experimental design useful for addressing research questions that inform the construction of high-quality adaptive interventions. To clarify the SMART approach and its advantages, we compare SMART with other experimental approaches. We also provide methods for analyzing data from SMART to address primary research questions that inform the construction of a high-quality adaptive intervention. PMID:23025433

Meta‐analysis of test accuracy studies using imputation for partial reporting of multiple thresholds

PubMed Central

Deeks, J.J.; Martin, E.C.; Riley, R.D.

2017-01-01

Introduction For tests reporting continuous results, primary studies usually provide test performance at multiple but often different thresholds. This creates missing data when performing a meta‐analysis at each threshold. A standard meta‐analysis (no imputation [NI]) ignores such missing data. A single imputation (SI) approach was recently proposed to recover missing threshold results. Here, we propose a new method that performs multiple imputation of the missing threshold results using discrete combinations (MIDC). Methods The new MIDC method imputes missing threshold results by randomly selecting from the set of all possible discrete combinations which lie between the results for 2 known bounding thresholds. Imputed and observed results are then synthesised at each threshold. This is repeated multiple times, and the multiple pooled results at each threshold are combined using Rubin's rules to give final estimates. We compared the NI, SI, and MIDC approaches via simulation. Results Both imputation methods outperform the NI method in simulations. There was generally little difference in the SI and MIDC methods, but the latter was noticeably better in terms of estimating the between‐study variances and generally gave better coverage, due to slightly larger standard errors of pooled estimates. Given selective reporting of thresholds, the imputation methods also reduced bias in the summary receiver operating characteristic curve. Simulations demonstrate the imputation methods rely on an equal threshold spacing assumption. A real example is presented. Conclusions The SI and, in particular, MIDC methods can be used to examine the impact of missing threshold results in meta‐analysis of test accuracy studies. PMID:29052347

A STATISTICAL MODELING METHODOLOGY FOR THE DETECTION, QUANTIFICATION, AND PREDICTION OF ECOLOGICAL THRESHOLDS

EPA Science Inventory

This study will provide a general methodology for integrating threshold information from multiple species ecological metrics, allow for prediction of changes of alternative stable states, and provide a risk assessment tool that can be applied to adaptive management. The integr...

Application of a Threshold Method to Airborne-Spaceborne Attenuating-Wavelength Radars for the Estimation of Space-Time Rain-Rate Statistics.

NASA Astrophysics Data System (ADS)

Meneghini, Robert

1998-09-01

A method is proposed for estimating the area-average rain-rate distribution from attenuating-wavelength spaceborne or airborne radar data. Because highly attenuated radar returns yield unreliable estimates of the rain rate, these are eliminated by means of a proxy variable, Q, derived from the apparent radar reflectivity factors and a power law relating the attenuation coefficient and the reflectivity factor. In determining the probability distribution function of areawide rain rates, the elimination of attenuated measurements at high rain rates and the loss of data at light rain rates, because of low signal-to-noise ratios, leads to truncation of the distribution at the low and high ends. To estimate it over all rain rates, a lognormal distribution is assumed, the parameters of which are obtained from a nonlinear least squares fit to the truncated distribution. Implementation of this type of threshold method depends on the method used in estimating the high-resolution rain-rate estimates (e.g., either the standard Z-R or the Hitschfeld-Bordan estimate) and on the type of rain-rate estimate (either point or path averaged). To test the method, measured drop size distributions are used to characterize the rain along the radar beam. Comparisons with the standard single-threshold method or with the sample mean, taken over the high-resolution estimates, show that the present method usually provides more accurate determinations of the area-averaged rain rate if the values of the threshold parameter, QT, are chosen in the range from 0.2 to 0.4.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding

PubMed Central

Elleithy, Khaled; Elleithy, Abdelrahman

2018-01-01

Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue for detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc, and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This paper proposes an automated retinal fundus image segmentation system composed of three segmentation subsystems follow same core segmentation algorithm. Despite of broad difference in features and characteristics; retinal vessels, optic disc, and exudate lesions are extracted by each subsystem without the need for texture analysis or synthesis. For sake of compact diagnosis and complete clinical insight, our proposed system can detect these anatomical structures in one session with high accuracy even in pathological retina images. The proposed system uses a robust hybrid segmentation algorithm combines adaptive fuzzy thresholding and mathematical morphology. The proposed system is validated using four benchmark datasets: DRIVE and STARE (vessels), DRISHTI-GS (optic disc), and DIARETDB1 (exudates lesions). Competitive segmentation performance is achieved, outperforming a variety of up-to-date systems and demonstrating the capacity to deal with other heterogeneous anatomical structures. PMID:29888146

A self-organizing Lagrangian particle method for adaptive-resolution advection-diffusion simulations

NASA Astrophysics Data System (ADS)

Reboux, Sylvain; Schrader, Birte; Sbalzarini, Ivo F.

2012-05-01

We present a novel adaptive-resolution particle method for continuous parabolic problems. In this method, particles self-organize in order to adapt to local resolution requirements. This is achieved by pseudo forces that are designed so as to guarantee that the solution is always well sampled and that no holes or clusters develop in the particle distribution. The particle sizes are locally adapted to the length scale of the solution. Differential operators are consistently evaluated on the evolving set of irregularly distributed particles of varying sizes using discretization-corrected operators. The method does not rely on any global transforms or mapping functions. After presenting the method and its error analysis, we demonstrate its capabilities and limitations on a set of two- and three-dimensional benchmark problems. These include advection-diffusion, the Burgers equation, the Buckley-Leverett five-spot problem, and curvature-driven level-set surface refinement.

Method and apparatus for telemetry adaptive bandwidth compression

NASA Technical Reports Server (NTRS)

Graham, Olin L.

1987-01-01

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Global gray-level thresholding based on object size.

PubMed

Ranefall, Petter; Wählby, Carolina

2016-04-01

In this article, we propose a fast and robust global gray-level thresholding method based on object size, where the selection of threshold level is based on recall and maximum precision with regard to objects within a given size interval. The method relies on the component tree representation, which can be computed in quasi-linear time. Feature-based segmentation is especially suitable for biomedical microscopy applications where objects often vary in number, but have limited variation in size. We show that for real images of cell nuclei and synthetic data sets mimicking fluorescent spots the proposed method is more robust than all standard global thresholding methods available for microscopy applications in ImageJ and CellProfiler. The proposed method, provided as ImageJ and CellProfiler plugins, is simple to use and the only required input is an interval of the expected object sizes. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Distortion analysis of subband adaptive filtering methods for FMRI active noise control systems.

PubMed

Milani, Ali A; Panahi, Issa M; Briggs, Richard

2007-01-01

Delayless subband filtering structure, as a high performance frequency domain filtering technique, is used for canceling broadband fMRI noise (8 kHz bandwidth). In this method, adaptive filtering is done in subbands and the coefficients of the main canceling filter are computed by stacking the subband weights together. There are two types of stacking methods called FFT and FFT-2. In this paper, we analyze the distortion introduced by these two stacking methods. The effect of the stacking distortion on the performance of different adaptive filters in FXLMS algorithm with non-minimum phase secondary path is explored. The investigation is done for different adaptive algorithms (nLMS, APA and RLS), different weight stacking methods, and different number of subbands.

Matrix-normalised quantification of species by threshold-calibrated competitive real-time PCR: allergenic peanut in food as one example.

PubMed

Holzhauser, Thomas; Kleiner, Kornelia; Janise, Annabella; Röder, Martin

2014-11-15

A novel method to quantify species or DNA on the basis of a competitive quantitative real-time polymerase chain reaction (cqPCR) was developed. Potentially allergenic peanut in food served as one example. Based on an internal competitive DNA sequence for normalisation of DNA extraction and amplification, the cqPCR was threshold-calibrated against 100mg/kg incurred peanut in milk chocolate. No external standards were necessary. The competitive molecule successfully served as calibrator for quantification, matrix normalisation, and inhibition control. Although designed for verification of a virtual threshold of 100mg/kg, the method allowed quantification of 10-1,000 mg/kg peanut incurred in various food matrices and without further matrix adaption: On the basis of four PCR replicates per sample, mean recovery of 10-1,000 mg/kg peanut in chocolate, vanilla ice cream, cookie dough, cookie, and muesli was 87% (range: 39-147%) in comparison to 199% (range: 114-237%) by three commercial ELISA kits. Copyright © 2014 Elsevier Ltd. All rights reserved.

Thermal detection thresholds in 5-year-old preterm born children; IQ does matter.

PubMed

de Graaf, Joke; Valkenburg, Abraham J; Tibboel, Dick; van Dijk, Monique

2012-07-01

Experiencing pain at newborn age may have consequences on one's somatosensory perception later in life. Children's perception for cold and warm stimuli may be determined with the Thermal Sensory Analyzer (TSA) device by two different methods. This pilot study in 5-year-old children born preterm aimed at establishing whether the TSA method of limits, which is dependent of reaction time, and the method of levels, which is independent of reaction time, would yield different cold and warm detection thresholds. The second aim was to establish possible associations between intellectual ability and the detection thresholds obtained with either method. A convenience sample was drawn from the participants in an ongoing 5-year follow-up study of a randomized controlled trial on effects of morphine during mechanical ventilation. Thresholds were assessed using both methods and statistically compared. Possible associations between the child's intelligence quotient (IQ) and threshold levels were analyzed. The method of levels yielded more sensitive thresholds than did the method of limits, i.e. mean (SD) cold detection thresholds: 30.3 (1.4) versus 28.4 (1.7) (Cohen'sd=1.2, P=0.001) and warm detection thresholds; 33.9 (1.9) versus 35.6 (2.1) (Cohen's d=0.8, P=0.04). IQ was statistically significantly associated only with the detection thresholds obtained with the method of limits (cold: r=0.64, warm: r=-0.52). The TSA method of levels, is to be preferred over the method of limits in 5-year-old preterm born children, as it establishes more sensitive detection thresholds and is independent of IQ. Copyright © 2011 Elsevier Ltd. All rights reserved.

Managing ecological thresholds in coupled environmental–human systems

PubMed Central

Horan, Richard D.; Fenichel, Eli P.; Drury, Kevin L. S.; Lodge, David M.

2011-01-01

Many ecosystems appear subject to regime shifts—abrupt changes from one state to another after crossing a threshold or tipping point. Thresholds and their associated stability landscapes are determined within a coupled socioeconomic–ecological system (SES) where human choices, including those of managers, are feedback responses. Prior work has made one of two assumptions about managers: that they face no institutional constraints, in which case the SES may be managed to be fairly robust to shocks and tipping points are of little importance, or that managers are rigidly constrained with no flexibility to adapt, in which case the inferred thresholds may poorly reflect actual managerial flexibility. We model a multidimensional SES to investigate how alternative institutions affect SES stability landscapes and alter tipping points. With institutionally dependent human feedbacks, the stability landscape depends on institutional arrangements. Strong institutions that account for feedback responses create the possibility for desirable states of the world and can cause undesirable states to cease to exist. Intermediate institutions interact with ecological relationships to determine the existence and nature of tipping points. Finally, weak institutions can eliminate tipping points so that only undesirable states of the world remain. PMID:21502517

Threshold quantum cryptography

NASA Astrophysics Data System (ADS)

Tokunaga, Yuuki; Okamoto, Tatsuaki; Imoto, Nobuyuki

2005-01-01

We present the concept of threshold collaborative unitary transformation or threshold quantum cryptography, which is a kind of quantum version of threshold cryptography. Threshold quantum cryptography states that classical shared secrets are distributed to several parties and a subset of them, whose number is greater than a threshold, collaborates to compute a quantum cryptographic function, while keeping each share secretly inside each party. The shared secrets are reusable if no cheating is detected. As a concrete example of this concept, we show a distributed protocol (with threshold) of conjugate coding.

MEthods of ASsessing blood pressUre: identifying thReshold and target valuEs (MeasureBP): a review & study protocol.

PubMed

Blom, Kimberly C; Farina, Sasha; Gomez, Yessica-Haydee; Campbell, Norm R C; Hemmelgarn, Brenda R; Cloutier, Lyne; McKay, Donald W; Dawes, Martin; Tobe, Sheldon W; Bolli, Peter; Gelfer, Mark; McLean, Donna; Bartlett, Gillian; Joseph, Lawrence; Featherstone, Robin; Schiffrin, Ernesto L; Daskalopoulou, Stella S

2015-04-01

Despite progress in automated blood pressure measurement (BPM) technology, there is limited research linking hard outcomes to automated office BPM (OBPM) treatment targets and thresholds. Equivalences for automated BPM devices have been estimated from approximations of standardized manual measurements of 140/90 mmHg. Until outcome-driven targets and thresholds become available for automated measurement methods, deriving evidence-based equivalences between automated methods and standardized manual OBPM is the next best solution. The MeasureBP study group was initiated by the Canadian Hypertension Education Program to close this critical knowledge gap. MeasureBP aims to define evidence-based equivalent values between standardized manual OBPM and automated BPM methods by synthesizing available evidence using a systematic review and individual subject-level data meta-analyses. This manuscript provides a review of the literature and MeasureBP study protocol. These results will lay the evidenced-based foundation to resolve uncertainties within blood pressure guidelines which, in turn, will improve the management of hypertension.

Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

NASA Astrophysics Data System (ADS)

Yang, Senlin; Li, Xilong; Chong, Xin

2017-10-01

The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

Addressing the limits to adaptation across four damage--response systems

EPA Science Inventory

Our ability to adapt to climate change is not boundless, and previous modeling shows that capacity limited adaptation will play a policy-significant role in future decisions about climate change. These limits are delineated by capacity thresholds, after which climate damages beg...

Successful adaptation of a research methods course in South America.

PubMed

Tamariz, Leonardo; Vasquez, Diego; Loor, Cecilia; Palacio, Ana

2017-01-01

South America has low research productivity. The lack of a structured research curriculum is one of the barriers to conducting research. To report our experience adapting an active learning-based research methods curriculum to improve research productivity at a university in Ecuador. We used a mixed-method approach to test the adaptation of the research curriculum at Universidad Catolica Santiago de Guayaquil. The curriculum uses a flipped classroom and active learning approach to teach research methods. When adapted, it was longitudinal and had 16-hour programme of in-person teaching and a six-month follow-up online component. Learners were organized in theme groups according to interest, and each group had a faculty leader. Our primary outcome was research productivity, which was measured by the succesful presentation of the research project at a national meeting, or publication in a peer-review journal. Our secondary outcomes were knowledge and perceived competence before and after course completion. We conducted qualitative interviews of faculty members and students to evaluate themes related to participation in research. Fifty university students and 10 faculty members attended the course. We had a total of 15 groups. Both knowledge and perceived competence increased by 17 and 18 percentage points, respectively. The presentation or publication rate for the entire group was 50%. The qualitative analysis showed that a lack of research culture and curriculum were common barriers to research. A US-based curriculum can be successfully adapted in low-middle income countries. A research curriculum aids in achieving pre-determined milestones. UCSG: Universidad Catolica Santiago de Guayaquil; UM: University of Miami.

The Sensory Difference Threshold of Menthol Odor in Flavored Tobacco Determined by Combining Sensory and Chemical Analysis.

PubMed

Krüsemann, Erna J Z; Cremers, Johannes W J M; Visser, Wouter F; Punter, Pieter H; Talhout, Reinskje

2017-03-01

Cigarettes are an often-used consumer product, and flavor is an important determinant of their product appeal. Cigarettes with strong nontobacco flavors are popular among young people, and may facilitate smoking initiation. Discriminating flavors in tobacco is important for regulation purposes, for instance to set upper limits to the levels of important flavor additives. We provide a simple and fast method to determine the human odor difference threshold for flavor additives in a tobacco matrix, using a combination of chemical and sensory analysis. For an example, the human difference threshold for menthol odor, one of the most frequently used tobacco flavors, was determined. A consumer panel consisting of 20 women compared different concentrations of menthol-flavored tobacco to unflavored cigarette tobacco using the 2-alternative forced choice method. Components contributing to menthol odor were quantified using headspace GC-MS. The sensory difference threshold of menthol odor corresponded to a mixture of 43 (37-50)% menthol-flavored tobacco, containing 1.8 (1.6-2.1) mg menthol, 2.7 (2.3-3.1) µg menthone, and 1.0 (0.9-1.2) µg neomenthyl acetate per gram of tobacco. Such a method is important in the context of the European Tobacco Product Directive, and the US Food and Drug Administration Tobacco Control Act, that both prohibit cigarettes and roll-your-own tobacco with a characterizing flavor other than tobacco. Our method can also be adapted for matrices other than tobacco, such as food. © The Author 2016. Published by Oxford University Press.

[Comparative adaptation of crowns of selective laser melting and wax-lost-casting method].

PubMed

Li, Guo-qiang; Shen, Qing-yi; Gao, Jian-hua; Wu, Xue-ying; Chen, Li; Dai, Wen-an

2012-07-01

To investigate the marginal adaptation of crowns fabricated by selective laser melting (SLM) and wax-lost-casting method, so as to provide an experimental basis for clinic. Co-Cr alloy full crown were fabricated by SLM and wax-lost-casting for 24 samples in each group. All crowns were cemented with zinc phosphate cement and cut along longitudinal axis by line cutting machine. The gap between crown tissue surface and die was measured by 6-point measuring method with scanning electron microscope (SEM). The marginal adaptation of crowns fabricated by SLM and wax-lost-casting were compared statistically. The gap between SLM crowns were (36.51 ± 2.94), (49.36 ± 3.31), (56.48 ± 3.35), (42.20 ± 3.60) µm, and wax-lost-casting crowns were (68.86 ± 5.41), (58.86 ± 6.10), (70.62 ± 5.79), (69.90 ± 6.00) µm. There were significant difference between two groups (P < 0.05). Co-Cr alloy full crown fabricated by wax-lost-casting method and SLM method provide acceptable marginal adaptation in clinic, and the marginal adaptation of SLM is better than that of wax-lost-casting method.

Rejection thresholds in solid chocolate-flavored compound coating.

PubMed

Harwood, Meriel L; Ziegler, Gregory R; Hayes, John E

2012-10-01

Classical detection thresholds do not predict liking, as they focus on the presence or absence of a sensation. Recently however, Prescott and colleagues described a new method, the rejection threshold, where a series of forced choice preference tasks are used to generate a dose-response function to determine hedonically acceptable concentrations. That is, how much is too much? To date, this approach has been used exclusively in liquid foods. Here, we determined group rejection thresholds in solid chocolate-flavored compound coating for bitterness. The influences of self-identified preferences for milk or dark chocolate, as well as eating style (chewers compared to melters) on rejection thresholds were investigated. Stimuli included milk chocolate-flavored compound coating spiked with increasing amounts of sucrose octaacetate, a bitter and generally recognized as safe additive. Paired preference tests (blank compared to spike) were used to determine the proportion of the group that preferred the blank. Across pairs, spiked samples were presented in ascending concentration. We were able to quantify and compare differences between 2 self-identified market segments. The rejection threshold for the dark chocolate preferring group was significantly higher than the milk chocolate preferring group (P= 0.01). Conversely, eating style did not affect group rejection thresholds (P= 0.14), although this may reflect the amount of chocolate given to participants. Additionally, there was no association between chocolate preference and eating style (P= 0.36). Present work supports the contention that this method can be used to examine preferences within specific market segments and potentially individual differences as they relate to ingestive behavior. This work makes use of the rejection threshold method to study market segmentation, extending its use to solid foods. We believe this method has broad applicability to the sensory specialist and product developer by providing a

Adaptive eigenspace method for inverse scattering problems in the frequency domain

NASA Astrophysics Data System (ADS)

Grote, Marcus J.; Kray, Marie; Nahum, Uri

2017-02-01

A nonlinear optimization method is proposed for the solution of inverse scattering problems in the frequency domain, when the scattered field is governed by the Helmholtz equation. The time-harmonic inverse medium problem is formulated as a PDE-constrained optimization problem and solved by an inexact truncated Newton-type iteration. Instead of a grid-based discrete representation, the unknown wave speed is projected to a particular finite-dimensional basis of eigenfunctions, which is iteratively adapted during the optimization. Truncating the adaptive eigenspace (AE) basis at a (small and slowly increasing) finite number of eigenfunctions effectively introduces regularization into the inversion and thus avoids the need for standard Tikhonov-type regularization. Both analytical and numerical evidence underpins the accuracy of the AE representation. Numerical experiments demonstrate the efficiency and robustness to missing or noisy data of the resulting adaptive eigenspace inversion method.

Evaluation of thresholding techniques for segmenting scaffold images in tissue engineering

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Yaszemski, Michael J.; Robb, Richard A.

2004-05-01

Tissue engineering attempts to address the ever widening gap between the demand and supply of organ and tissue transplants using natural and biomimetic scaffolds. The regeneration of specific tissues aided by synthetic materials is dependent on the structural and morphometric properties of the scaffold. These properties can be derived non-destructively using quantitative analysis of high resolution microCT scans of scaffolds. Thresholding of the scanned images into polymeric and porous phase is central to the outcome of the subsequent structural and morphometric analysis. Visual thresholding of scaffolds produced using stochastic processes is inaccurate. Depending on the algorithmic assumptions made, automatic thresholding might also be inaccurate. Hence there is a need to analyze the performance of different techniques and propose alternate ones, if needed. This paper provides a quantitative comparison of different thresholding techniques for segmenting scaffold images. The thresholding algorithms examined include those that exploit spatial information, locally adaptive characteristics, histogram entropy information, histogram shape information, and clustering of gray-level information. The performance of different techniques was evaluated using established criteria, including misclassification error, edge mismatch, relative foreground error, and region non-uniformity. Algorithms that exploit local image characteristics seem to perform much better than those using global information.

A generalized adaptive mathematical morphological filter for LIDAR data

NASA Astrophysics Data System (ADS)

Cui, Zheng

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in

Self-adjusting threshold mechanism for pixel detectors

NASA Astrophysics Data System (ADS)

Heim, Timon; Garcia-Sciveres, Maurice

2017-09-01

Readout chips of hybrid pixel detectors use a low power amplifier and threshold discrimination to process charge deposited in semiconductor sensors. Due to transistor mismatch each pixel circuit needs to be calibrated individually to achieve response uniformity. Traditionally this is addressed by programmable threshold trimming in each pixel, but requires robustness against radiation effects, temperature, and time. In this paper a self-adjusting threshold mechanism is presented, which corrects the threshold for both spatial inequality and time variation and maintains a constant response. It exploits the electrical noise as relative measure for the threshold and automatically adjust the threshold of each pixel to always achieve a uniform frequency of noise hits. A digital implementation of the method in the form of an up/down counter and combinatorial logic filter is presented. The behavior of this circuit has been simulated to evaluate its performance and compare it to traditional calibration results. The simulation results show that this mechanism can perform equally well, but eliminates instability over time and is immune to single event upsets.

Predicting coral bleaching hotspots: the role of regional variability in thermal stress and potential adaptation rates

NASA Astrophysics Data System (ADS)

Teneva, Lida; Karnauskas, Mandy; Logan, Cheryl A.; Bianucci, Laura; Currie, Jock C.; Kleypas, Joan A.

2012-03-01

Sea surface temperature fields (1870-2100) forced by CO2-induced climate change under the IPCC SRES A1B CO2 scenario, from three World Climate Research Programme Coupled Model Intercomparison Project Phase 3 (WCRP CMIP3) models (CCSM3, CSIRO MK 3.5, and GFDL CM 2.1), were used to examine how coral sensitivity to thermal stress and rates of adaption affect global projections of coral-reef bleaching. The focus of this study was two-fold, to: (1) assess how the impact of Degree-Heating-Month (DHM) thermal stress threshold choice affects potential bleaching predictions and (2) examine the effect of hypothetical adaptation rates of corals to rising temperature. DHM values were estimated using a conventional threshold of 1°C and a variability-based threshold of 2σ above the climatological maximum Coral adaptation rates were simulated as a function of historical 100-year exposure to maximum annual SSTs with a dynamic rather than static climatological maximum based on the previous 100 years, for a given reef cell. Within CCSM3 simulations, the 1°C threshold predicted later onset of mild bleaching every 5 years for the fraction of reef grid cells where 1°C > 2σ of the climatology time series of annual SST maxima (1961-1990). Alternatively, DHM values using both thresholds, with CSIRO MK 3.5 and GFDL CM 2.1 SSTs, did not produce drastically different onset timing for bleaching every 5 years. Across models, DHMs based on 1°C thermal stress threshold show the most threatened reefs by 2100 could be in the Central and Western Equatorial Pacific, whereas use of the variability-based threshold for DHMs yields the Coral Triangle and parts of Micronesia and Melanesia as bleaching hotspots. Simulations that allow corals to adapt to increases in maximum SST drastically reduce the rates of bleaching. These findings highlight the importance of considering the thermal stress threshold in DHM estimates as well as potential adaptation models in future coral bleaching projections.

Earthquake Rupture Dynamics using Adaptive Mesh Refinement and High-Order Accurate Numerical Methods

NASA Astrophysics Data System (ADS)

Kozdon, J. E.; Wilcox, L.

2013-12-01

Our goal is to develop scalable and adaptive (spatial and temporal) numerical methods for coupled, multiphysics problems using high-order accurate numerical methods. To do so, we are developing an opensource, parallel library known as bfam (available at http://bfam.in). The first application to be developed on top of bfam is an earthquake rupture dynamics solver using high-order discontinuous Galerkin methods and summation-by-parts finite difference methods. In earthquake rupture dynamics, wave propagation in the Earth's crust is coupled to frictional sliding on fault interfaces. This coupling is two-way, required the simultaneous simulation of both processes. The use of laboratory-measured friction parameters requires near-fault resolution that is 4-5 orders of magnitude higher than that needed to resolve the frequencies of interest in the volume. This, along with earlier simulations using a low-order, finite volume based adaptive mesh refinement framework, suggest that adaptive mesh refinement is ideally suited for this problem. The use of high-order methods is motivated by the high level of resolution required off the fault in earlier the low-order finite volume simulations; we believe this need for resolution is a result of the excessive numerical dissipation of low-order methods. In bfam spatial adaptivity is handled using the p4est library and temporal adaptivity will be accomplished through local time stepping. In this presentation we will present the guiding principles behind the library as well as verification of code against the Southern California Earthquake Center dynamic rupture code validation test problems.

Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold.

PubMed

Claxton, Karl; Martin, Steve; Soares, Marta; Rice, Nigel; Spackman, Eldon; Hinde, Sebastian; Devlin, Nancy; Smith, Peter C; Sculpher, Mark

2015-02-01

that it is < £30,000 per QALY is 0.97. Additional 'structural' uncertainty suggests, on balance, that the central or best estimate is, if anything, likely to be an overestimate. The health effects of changes in expenditure are greater when PCTs are under more financial pressure and are more likely to be disinvesting than investing. This indicates that the central estimate of the threshold is likely to be an overestimate for all technologies which impose net costs on the NHS and the appropriate threshold to apply should be lower for technologies which have a greater impact on NHS costs. The central estimate is based on identifying a preferred analysis at each stage based on the analysis that made the best use of available information, whether or not the assumptions required appeared more reasonable than the other alternatives available, and which provided a more complete picture of the likely health effects of a change in expenditure. However, the limitation of currently available data means that there is substantial uncertainty associated with the estimate of the overall threshold. The methods go some way to providing an empirical estimate of the scale of opportunity costs the NHS faces when considering whether or not the health benefits associated with new technologies are greater than the health that is likely to be lost elsewhere in the NHS. Priorities for future research include estimating the threshold for subsequent waves of expenditure and outcome data, for example by utilising expenditure and outcomes available at the level of Clinical Commissioning Groups as well as additional data collected on QoL and updated estimates of incidence (by age and gender) and duration of disease. Nonetheless, the study also starts to make the other NHS patients, who ultimately bear the opportunity costs of such decisions, less abstract and more 'known' in social decisions. The National Institute for Health Research-Medical Research Council Methodology Research Programme.

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

Parallel, adaptive finite element methods for conservation laws

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Devine, Karen D.; Flaherty, Joseph E.

1994-01-01

We construct parallel finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. A posteriori estimates of spatial errors are obtained by a p-refinement technique using superconvergence at Radau points. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We compare results using different limiting schemes and demonstrate parallel efficiency through computations on an NCUBE/2 hypercube. We also present results using adaptive h- and p-refinement to reduce the computational cost of the method.

Simulation of Healing Threshold in Strain-Induced Inflammation Through a Discrete Informatics Model.

PubMed

Ibrahim, Israr Bin M; Sarma O V, Sanjay; Pidaparti, Ramana M

2018-05-01

Respiratory diseases such as asthma and acute respiratory distress syndrome as well as acute lung injury involve inflammation at the cellular level. The inflammation process is very complex and is characterized by the emergence of cytokines along with other changes in cellular processes. Due to the complexity of the various constituents that makes up the inflammation dynamics, it is necessary to develop models that can complement experiments to fully understand inflammatory diseases. In this study, we developed a discrete informatics model based on cellular automata (CA) approach to investigate the influence of elastic field (stretch/strain) on the dynamics of inflammation and account for probabilistic adaptation based on statistical interpretation of existing experimental data. Our simulation model investigated the effects of low, medium, and high strain conditions on inflammation dynamics. Results suggest that the model is able to indicate the threshold of innate healing of tissue as a response to strain experienced by the tissue. When strain is under the threshold, the tissue is still capable of adapting its structure to heal the damaged part. However, there exists a strain threshold where healing capability breaks down. The results obtained demonstrate that the developed discrete informatics based CA model is capable of modeling and giving insights into inflammation dynamics parameters under various mechanical strain/stretch environments.

Identifying Thresholds for Ecosystem-Based Management

PubMed Central

Samhouri, Jameal F.; Levin, Phillip S.; Ainsworth, Cameron H.

2010-01-01

Background One of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action. Methodology/Principal Findings To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem's structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs. Conclusions/Significance For any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management. PMID:20126647

An improved method to set significance thresholds for β diversity testing in microbial community comparisons.

PubMed

Gülay, Arda; Smets, Barth F

2015-09-01

Exploring the variation in microbial community diversity between locations (β diversity) is a central topic in microbial ecology. Currently, there is no consensus on how to set the significance threshold for β diversity. Here, we describe and quantify the technical components of β diversity, including those associated with the process of subsampling. These components exist for any proposed β diversity measurement procedure. Further, we introduce a strategy to set significance thresholds for β diversity of any group of microbial samples using rarefaction, invoking the notion of a meta-community. The proposed technique was applied to several in silico generated operational taxonomic unit (OTU) libraries and experimental 16S rRNA pyrosequencing libraries. The latter represented microbial communities from different biological rapid sand filters at a full-scale waterworks. We observe that β diversity, after subsampling, is inflated by intra-sample differences; this inflation is avoided in the proposed method. In addition, microbial community evenness (Gini > 0.08) strongly affects all β diversity estimations due to bias associated with rarefaction. Where published methods to test β significance often fail, the proposed meta-community-based estimator is more successful at rejecting insignificant β diversity values. Applying our approach, we reveal the heterogeneous microbial structure of biological rapid sand filters both within and across filters. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Adaptive and dynamic meshing methods for numerical simulations

NASA Astrophysics Data System (ADS)

Acikgoz, Nazmiye

-hoc application of the simulated annealing technique, which improves the likelihood of removing poor elements from the grid. Moreover, a local implementation of the simulated annealing is proposed to reduce the computational cost. Many challenging multi-physics and multi-field problems that are unsteady in nature are characterized by moving boundaries and/or interfaces. When the boundary displacements are large, which typically occurs when implicit time marching procedures are used, degenerate elements are easily formed in the grid such that frequent remeshing is required. To deal with this problem, in the second part of this work, we propose a new r-adaptation methodology. The new technique is valid for both simplicial (e.g., triangular, tet) and non-simplicial (e.g., quadrilateral, hex) deforming grids that undergo large imposed displacements at their boundaries. A two- or three-dimensional grid is deformed using a network of linear springs composed of edge springs and a set of virtual springs. The virtual springs are constructed in such a way as to oppose element collapsing. This is accomplished by confining each vertex to its ball through springs that are attached to the vertex and its projection on the ball entities. The resulting linear problem is solved using a preconditioned conjugate gradient method. The new method is compared with the classical spring analogy technique in two- and three-dimensional examples, highlighting the performance improvements achieved by the new method. Meshes are an important part of numerical simulations. Depending on the geometry and flow conditions, the most suitable mesh for each particular problem is different. Meshes are usually generated by either using a suitable software package or solving a PDE. In both cases, engineering intuition plays a significant role in deciding where clusterings should take place. In addition, for unsteady problems, the gradients vary for each time step, which requires frequent remeshing during simulations

Psychophysics with children: Investigating the effects of attentional lapses on threshold estimates.

PubMed

Manning, Catherine; Jones, Pete R; Dekker, Tessa M; Pellicano, Elizabeth

2018-03-26

When assessing the perceptual abilities of children, researchers tend to use psychophysical techniques designed for use with adults. However, children's poorer attentiveness might bias the threshold estimates obtained by these methods. Here, we obtained speed discrimination threshold estimates in 6- to 7-year-old children in UK Key Stage 1 (KS1), 7- to 9-year-old children in Key Stage 2 (KS2), and adults using three psychophysical procedures: QUEST, a 1-up 2-down Levitt staircase, and Method of Constant Stimuli (MCS). We estimated inattentiveness using responses to "easy" catch trials. As expected, children had higher threshold estimates and made more errors on catch trials than adults. Lower threshold estimates were obtained from psychometric functions fit to the data in the QUEST condition than the MCS and Levitt staircases, and the threshold estimates obtained when fitting a psychometric function to the QUEST data were also lower than when using the QUEST mode. This suggests that threshold estimates cannot be compared directly across methods. Differences between the procedures did not vary significantly with age group. Simulations indicated that inattentiveness biased threshold estimates particularly when threshold estimates were computed as the QUEST mode or the average of staircase reversals. In contrast, thresholds estimated by post-hoc psychometric function fitting were less biased by attentional lapses. Our results suggest that some psychophysical methods are more robust to attentiveness, which has important implications for assessing the perception of children and clinical groups.

ZZ-Type a posteriori error estimators for adaptive boundary element methods on a curve☆

PubMed Central

Feischl, Michael; Führer, Thomas; Karkulik, Michael; Praetorius, Dirk

2014-01-01

In the context of the adaptive finite element method (FEM), ZZ-error estimators named after Zienkiewicz and Zhu (1987) [52] are mathematically well-established and widely used in practice. In this work, we propose and analyze ZZ-type error estimators for the adaptive boundary element method (BEM). We consider weakly singular and hyper-singular integral equations and prove, in particular, convergence of the related adaptive mesh-refining algorithms. Throughout, the theoretical findings are underlined by numerical experiments. PMID:24748725

Cool, warm, and heat-pain detection thresholds: testing methods and inferences about anatomic distribution of receptors.

PubMed

Dyck, P J; Zimmerman, I; Gillen, D A; Johnson, D; Karnes, J L; O'Brien, P C

1993-08-01

We recently found that vibratory detection threshold is greatly influenced by the algorithm of testing. Here, we study the influence of stimulus characteristics and algorithm of testing and estimating threshold on cool (CDT), warm (WDT), and heat-pain (HPDT) detection thresholds. We show that continuously decreasing (for CDT) or increasing (for WDT) thermode temperature to the point at which cooling or warming is perceived and signaled by depressing a response key ("appearance" threshold) overestimates threshold with rapid rates of thermal change. The mean of the appearance and disappearance thresholds also does not perform well for insensitive sites and patients. Pyramidal (or flat-topped pyramidal) stimuli ranging in magnitude, in 25 steps, from near skin temperature to 9 degrees C for 10 seconds (for CDT), from near skin temperature to 45 degrees C for 10 seconds (for WDT), and from near skin temperature to 49 degrees C for 10 seconds (for HPDT) provide ideal stimuli for use in several algorithms of testing and estimating threshold. Near threshold, only the initial direction of thermal change from skin temperature is perceived, and not its return to baseline. Use of steps of stimulus intensity allows the subject or patient to take the needed time to decide whether the stimulus was felt or not (in 4, 2, and 1 stepping algorithms), or whether it occurred in stimulus interval 1 or 2 (in two-alternative forced-choice testing). Thermal thresholds were generally significantly lower with a large (10 cm2) than with a small (2.7 cm2) thermode.(ABSTRACT TRUNCATED AT 250 WORDS)

An adaptive angle-doppler compensation method for airborne bistatic radar based on PAST

NASA Astrophysics Data System (ADS)

Hang, Xu; Jun, Zhao

2018-05-01

Adaptive angle-Doppler compensation method extract the requisite information based on the data itself adaptively, thus avoiding the problem of performance degradation caused by inertia system error. However, this method requires estimation and egiendecomposition of sample covariance matrix, which has a high computational complexity and limits its real-time application. In this paper, an adaptive angle Doppler compensation method based on projection approximation subspace tracking (PAST) is studied. The method uses cyclic iterative processing to quickly estimate the positions of the spectral center of the maximum eigenvector of each range cell, and the computational burden of matrix estimation and eigen-decompositon is avoided, and then the spectral centers of all range cells is overlapped by two dimensional compensation. Simulation results show the proposed method can effectively reduce the no homogeneity of airborne bistatic radar, and its performance is similar to that of egien-decomposition algorithms, but the computation load is obviously reduced and easy to be realized.

Testing for thresholds of ecosystem collapse in seagrass meadows.

PubMed

Connell, Sean D; Fernandes, Milena; Burnell, Owen W; Doubleday, Zoë A; Griffin, Kingsley J; Irving, Andrew D; Leung, Jonathan Y S; Owen, Samuel; Russell, Bayden D; Falkenberg, Laura J

2017-10-01

Although the public desire for healthy environments is clear-cut, the science and management of ecosystem health has not been as simple. Ecological systems can be dynamic and can shift abruptly from one ecosystem state to another. Such unpredictable shifts result when ecological thresholds are crossed; that is, small cumulative increases in an environmental stressor drive a much greater change than could be predicted from linear effects, suggesting an unforeseen tipping point is crossed. In coastal waters, broad-scale seagrass loss often occurs as a sudden event associated with human-driven nutrient enrichment (eutrophication). We tested whether the response of seagrass ecosystems to coastal nutrient enrichment is subject to a threshold effect. We exposed seagrass plots to different levels of nutrient enrichment (dissolved inorganic nitrogen) for 10 months and measured net production. Seagrass response exhibited a threshold pattern when nutrient enrichment exceeded moderate levels: there was an abrupt and large shift from positive to negative net leaf production (from approximately 0.04 leaf production to 0.02 leaf loss per day). Epiphyte load also increased as nutrient enrichment increased, which may have driven the shift in leaf production. Inadvertently crossing such thresholds, as can occur through ineffective management of land-derived inputs such as wastewater and stormwater runoff along urbanized coasts, may account for the widely observed sudden loss of seagrass meadows. Identification of tipping points may improve not only adaptive-management monitoring that seeks to avoid threshold effects, but also restoration approaches in systems that have crossed them. © 2017 Society for Conservation Biology.

A dual-adaptive support-based stereo matching algorithm

NASA Astrophysics Data System (ADS)

Zhang, Yin; Zhang, Yun

2017-07-01

Many stereo matching algorithms use fixed color thresholds and a rigid cross skeleton to segment supports (viz., Cross method), which, however, does not work well for different images. To address this issue, this paper proposes a novel dual adaptive support (viz., DAS)-based stereo matching method, which uses both appearance and shape information of a local region to segment supports automatically, and, then, integrates the DAS-based cost aggregation with the absolute difference plus census transform cost, scanline optimization and disparity refinement to develop a stereo matching system. The performance of the DAS method is also evaluated in the Middlebury benchmark and by comparing with the Cross method. The results show that the average error for the DAS method 25.06% lower than that for the Cross method, indicating that the proposed method is more accurate, with fewer parameters and suitable for parallel computing.

A multi-block adaptive solving technique based on lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Zhang, Yang; Xie, Jiahua; Li, Xiaoyue; Ma, Zhenghai; Zou, Jianfeng; Zheng, Yao

2018-05-01

In this paper, a CFD parallel adaptive algorithm is self-developed by combining the multi-block Lattice Boltzmann Method (LBM) with Adaptive Mesh Refinement (AMR). The mesh refinement criterion of this algorithm is based on the density, velocity and vortices of the flow field. The refined grid boundary is obtained by extending outward half a ghost cell from the coarse grid boundary, which makes the adaptive mesh more compact and the boundary treatment more convenient. Two numerical examples of the backward step flow separation and the unsteady flow around circular cylinder demonstrate the vortex structure of the cold flow field accurately and specifically.

Influence of surgical gloves on haptic perception thresholds.

PubMed

Hatzfeld, Christian; Dorsch, Sarah; Neupert, Carsten; Kupnik, Mario

2018-02-01

Impairment of haptic perception by surgical gloves could reduce requirements on haptic systems for surgery. While grip forces and manipulation capabilities were not impaired in previous studies, no data is available for perception thresholds. Absolute and differential thresholds (20 dB above threshold) of 24 subjects were measured for frequencies of 25 and 250 Hz with a Ψ-method. Effects of wearing a surgical glove, moisture on the contact surface and subject's experience with gloves were incorporated in a full-factorial experimental design. Absolute thresholds of 12.8 dB and -29.6 dB (means for 25 and 250 Hz, respectively) and differential thresholds of -12.6 dB and -9.5 dB agree with previous studies. A relevant effect of the frequency on absolute thresholds was found. Comparisons of glove- and no-glove-conditions did not reveal a significant mean difference. Wearing a single surgical glove does not affect absolute and differential haptic perception thresholds. Copyright © 2017 John Wiley & Sons, Ltd.

Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

NASA Technical Reports Server (NTRS)

Wang, Ray (Inventor)

2009-01-01

A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft

NASA Technical Reports Server (NTRS)

Davidson, John B.; Lallman, Frederick J.; Bundick, W. Thomas

2001-01-01

Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.

Bilevel thresholding of sliced image of sludge floc.

PubMed

Chu, C P; Lee, D J

2004-02-15

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

Algorithm for improving psychophysical threshold estimates by detecting sustained inattention in experiments using PEST.

PubMed

Rinderknecht, Mike D; Ranzani, Raffaele; Popp, Werner L; Lambercy, Olivier; Gassert, Roger

2018-05-10

Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can be altered, for example by loss of attention to the presentation of stimuli, leading to biased data, which results in poor threshold estimates. The few existing approaches attempting to identify non-stationarities either detect only whether there was a change in perception, or are not suitable for experiments with a relatively small number of trials (e.g., [Formula: see text] 300). We present a method to detect inattention periods on a trial-by-trial basis with the aim of improving threshold estimates in psychophysical experiments using the adaptive sampling procedure Parameter Estimation by Sequential Testing (PEST). The performance of the algorithm was evaluated in computer simulations modeling inattention, and tested in a behavioral experiment on proprioceptive difference threshold assessment in 20 stroke patients, a population where attention deficits are likely to be present. Simulations showed that estimation errors could be reduced by up to 77% for inattentive subjects, even in sequences with less than 100 trials. In the behavioral data, inattention was detected in 14% of assessments, and applying the proposed algorithm resulted in reduced test-retest variability in 73% of these corrected assessments pairs. The novel algorithm complements existing approaches and, besides being applicable post hoc, could also be used online to prevent collection of biased data. This could have important implications in assessment practice by shortening experiments and improving estimates, especially for clinical settings.

Polynomial sequences for bond percolation critical thresholds

DOE PAGES

Scullard, Christian R.

2011-09-22

In this paper, I compute the inhomogeneous (multi-probability) bond critical surfaces for the (4, 6, 12) and (3 4, 6) using the linearity approximation described in (Scullard and Ziff, J. Stat. Mech. 03021), implemented as a branching process of lattices. I find the estimates for the bond percolation thresholds, pc(4, 6, 12) = 0.69377849... and p c(3 4, 6) = 0.43437077..., compared with Parviainen’s numerical results of p c = 0.69373383... and p c = 0.43430621... . These deviations are of the order 10 -5, as is standard for this method. Deriving thresholds in this way for a given latticemore » leads to a polynomial with integer coefficients, the root in [0, 1] of which gives the estimate for the bond threshold and I show how the method can be refined, leading to a series of higher order polynomials making predictions that likely converge to the exact answer. Finally, I discuss how this fact hints that for certain graphs, such as the kagome lattice, the exact bond threshold may not be the root of any polynomial with integer coefficients.« less

AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation

DOE PAGES

Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; ...

2016-04-19

We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less

AP-Cloud: Adaptive Particle-in-Cloud method for optimal solutions to Vlasov–Poisson equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xingyu; Samulyak, Roman, E-mail: roman.samulyak@stonybrook.edu; Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973

We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less

AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin

We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less

Threshold units: A correct metric for reaction time?

PubMed Central

Zele, Andrew J.; Cao, Dingcai; Pokorny, Joel

2007-01-01

Purpose To compare reaction time (RT) to rod incremental and decremental stimuli expressed in physical contrast units or psychophysical threshold units. Methods Rod contrast detection thresholds and suprathreshold RTs were measured for Rapid-On and Rapid-Off ramp stimuli. Results Threshold sensitivity to Rapid-Off stimuli was higher than to Rapid-On stimuli. Suprathreshold RTs specified in Weber contrast for Rapid-Off stimuli were shorter than for Rapid-On stimuli. Reaction time data expressed in multiples of threshold reversed the outcomes: Reaction times for Rapid-On stimuli were shorter than those for Rapid-Off stimuli. The use of alternative contrast metrics also failed to equate RTs. Conclusions A case is made that the interpretation of RT data may be confounded when expressed in threshold units. Stimulus energy or contrast is the only metric common to the response characteristics of the cells underlying speeded responses. The use of threshold metrics for RT can confuse the interpretation of an underlying physiological process. PMID:17240416

Threshold Assessment of Gear Diagnostic Tools on Flight and Test Rig Data

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Mosher, Marianne; Huff, Edward M.

2003-01-01

A method for defining thresholds for vibration-based algorithms that provides the minimum number of false alarms while maintaining sensitivity to gear damage was developed. This analysis focused on two vibration based gear damage detection algorithms, FM4 and MSA. This method was developed using vibration data collected during surface fatigue tests performed in a spur gearbox rig. The thresholds were defined based on damage progression during tests with damage. The thresholds false alarm rates were then evaluated on spur gear tests without damage. Next, the same thresholds were applied to flight data from an OH-58 helicopter transmission. Results showed that thresholds defined in test rigs can be used to define thresholds in flight to correctly classify the transmission operation as normal.

CARA Risk Assessment Thresholds

NASA Technical Reports Server (NTRS)

Hejduk, M. D.

2016-01-01

Warning remediation threshold (Red threshold): Pc level at which warnings are issued, and active remediation considered and usually executed. Analysis threshold (Green to Yellow threshold): Pc level at which analysis of event is indicated, including seeking additional information if warranted. Post-remediation threshold: Pc level to which remediation maneuvers are sized in order to achieve event remediation and obviate any need for immediate follow-up maneuvers. Maneuver screening threshold: Pc compliance level for routine maneuver screenings (more demanding than regular Red threshold due to additional maneuver uncertainty).

Dark adaptation and the retinoid cycle of vision.

PubMed

Lamb, T D; Pugh, E N

2004-05-01

Following exposure of our eye to very intense illumination, we experience a greatly elevated visual threshold, that takes tens of minutes to return completely to normal. The slowness of this phenomenon of "dark adaptation" has been studied for many decades, yet is still not fully understood. Here we review the biochemical and physical processes involved in eliminating the products of light absorption from the photoreceptor outer segment, in recycling the released retinoid to its original isomeric form as 11-cis retinal, and in regenerating the visual pigment rhodopsin. Then we analyse the time-course of three aspects of human dark adaptation: the recovery of psychophysical threshold, the recovery of rod photoreceptor circulating current, and the regeneration of rhodopsin. We begin with normal human subjects, and then analyse the recovery in several retinal disorders, including Oguchi disease, vitamin A deficiency, fundus albipunctatus, Bothnia dystrophy and Stargardt disease. We review a large body of evidence showing that the time-course of human dark adaptation and pigment regeneration is determined by the local concentration of 11-cis retinal, and that after a large bleach the recovery is limited by the rate at which 11-cis retinal is delivered to opsin in the bleached rod outer segments. We present a mathematical model that successfully describes a wide range of results in human and other mammals. The theoretical analysis provides a simple means of estimating the relative concentration of free 11-cis retinal in the retina/RPE, in disorders exhibiting slowed dark adaptation, from analysis of psychophysical measurements of threshold recovery or from analysis of pigment regeneration kinetics.

Data compression using adaptive transform coding. Appendix 1: Item 1. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rost, Martin Christopher

1988-01-01

Adaptive low-rate source coders are described in this dissertation. These coders adapt by adjusting the complexity of the coder to match the local coding difficulty of the image. This is accomplished by using a threshold driven maximum distortion criterion to select the specific coder used. The different coders are built using variable blocksized transform techniques, and the threshold criterion selects small transform blocks to code the more difficult regions and larger blocks to code the less complex regions. A theoretical framework is constructed from which the study of these coders can be explored. An algorithm for selecting the optimal bit allocation for the quantization of transform coefficients is developed. The bit allocation algorithm is more fully developed, and can be used to achieve more accurate bit assignments than the algorithms currently used in the literature. Some upper and lower bounds for the bit-allocation distortion-rate function are developed. An obtainable distortion-rate function is developed for a particular scalar quantizer mixing method that can be used to code transform coefficients at any rate.

An Adaptive Cross-Architecture Combination Method for Graph Traversal

DOE Office of Scientific and Technical Information (OSTI.GOV)

You, Yang; Song, Shuaiwen; Kerbyson, Darren J.

2014-06-18

Breadth-First Search (BFS) is widely used in many real-world applications including computational biology, social networks, and electronic design automation. The combination method, using both top-down and bottom-up techniques, is the most effective BFS approach. However, current combination methods rely on trial-and-error and exhaustive search to locate the optimal switching point, which may cause significant runtime overhead. To solve this problem, we design an adaptive method based on regression analysis to predict an optimal switching point for the combination method at runtime within less than 0.1% of the BFS execution time.

Hard decoding algorithm for optimizing thresholds under general Markovian noise

NASA Astrophysics Data System (ADS)

Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond

2017-04-01

Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.

A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection

DOE PAGES

Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max D.; ...

2015-06-24

This study proposes and analyzes a hyperspherical adaptive hierarchical sparse-grid method for detecting jump discontinuities of functions in high-dimensional spaces. The method is motivated by the theoretical and computational inefficiencies of well-known adaptive sparse-grid methods for discontinuity detection. Our novel approach constructs a function representation of the discontinuity hypersurface of an N-dimensional discontinuous quantity of interest, by virtue of a hyperspherical transformation. Then, a sparse-grid approximation of the transformed function is built in the hyperspherical coordinate system, whose value at each point is estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the newmore » technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. In addition, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous complexity analyses of the new method are provided as are several numerical examples that illustrate the effectiveness of the approach.« less

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

Data Assimilation Methods on a Non-conservative Adaptive Mesh