Robust linear discriminant models to solve financial crisis in banking sectors

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Idris, Faoziah; Ali, Hazlina; Omar, Zurni

2014-12-01

Linear discriminant analysis (LDA) is a widely-used technique in patterns classification via an equation which will minimize the probability of misclassifying cases into their respective categories. However, the performance of classical estimators in LDA highly depends on the assumptions of normality and homoscedasticity. Several robust estimators in LDA such as Minimum Covariance Determinant (MCD), S-estimators and Minimum Volume Ellipsoid (MVE) are addressed by many authors to alleviate the problem of non-robustness of the classical estimates. In this paper, we investigate on the financial crisis of the Malaysian banking institutions using robust LDA and classical LDA methods. Our objective is to distinguish the "distress" and "non-distress" banks in Malaysia by using the LDA models. Hit ratio is used to validate the accuracy predictive of LDA models. The performance of LDA is evaluated by estimating the misclassification rate via apparent error rate. The results and comparisons show that the robust estimators provide a better performance than the classical estimators for LDA.

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements.

PubMed

Caprihan, A; Pearlson, G D; Calhoun, V D

2008-08-15

Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.

Dual tasking negatively impacts obstacle avoidance abilities in post-stroke individuals with visuospatial neglect: Task complexity matters!

PubMed

Aravind, Gayatri; Lamontagne, Anouk

2017-01-01

Persons with perceptual-attentional deficits due to visuospatial neglect (VSN) after a stroke are at a risk of collisions while walking in the presence of moving obstacles. The attentional burden of performing a dual-task may further compromise their obstacle avoidance performance, putting them at a greater risk of collisions. The objective of this study was to compare the ability of persons with (VSN+) and without VSN (VSN-) to dual task while negotiating moving obstacles. Twenty-six stroke survivors (13 VSN+, 13 VSN-) were assessed on their ability to (a) negotiate moving obstacles while walking (locomotor single task); (b) perform a pitch-discrimination task (cognitive single task) and (c) simultaneously perform the walking and cognitive tasks (dual task). We compared the groups on locomotor (collision rates, minimum distance from obstacle and onset of strategies) and cognitive (error rates) outcomes. For both single and dual task walking, VSN+ individuals showed higher collision rates compared to VSN- individuals. Dual tasking caused deterioration of locomotor (more collisions, delayed onset and smaller minimum distances) and cognitive performances (higher error rate) in VSN+ individuals. Contrastingly, VSN- individuals maintained collision rates, increased minimum distance, but showed more cognitive errors, prioritizing their locomotor performance. Individuals with VSN demonstrate cognitive-locomotor interference under dual task conditions, which could severely compromise safety when ambulating in community environments and may explain the poor recovery of independent community ambulation in these individuals.

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Optimal subsystem approach to multi-qubit quantum state discrimination and experimental investigation

NASA Astrophysics Data System (ADS)

Xue, ShiChuan; Wu, JunJie; Xu, Ping; Yang, XueJun

2018-02-01

Quantum computing is a significant computing capability which is superior to classical computing because of its superposition feature. Distinguishing several quantum states from quantum algorithm outputs is often a vital computational task. In most cases, the quantum states tend to be non-orthogonal due to superposition; quantum mechanics has proved that perfect outcomes could not be achieved by measurements, forcing repetitive measurement. Hence, it is important to determine the optimum measuring method which requires fewer repetitions and a lower error rate. However, extending current measurement approaches mainly aiming at quantum cryptography to multi-qubit situations for quantum computing confronts challenges, such as conducting global operations which has considerable costs in the experimental realm. Therefore, in this study, we have proposed an optimum subsystem method to avoid these difficulties. We have provided an analysis of the comparison between the reduced subsystem method and the global minimum error method for two-qubit problems; the conclusions have been verified experimentally. The results showed that the subsystem method could effectively discriminate non-orthogonal two-qubit states, such as separable states, entangled pure states, and mixed states; the cost of the experimental process had been significantly reduced, in most circumstances, with acceptable error rate. We believe the optimal subsystem method is the most valuable and promising approach for multi-qubit quantum computing applications.

Robust linear discriminant analysis with distance based estimators

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

2017-11-01

Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

Automatic tissue characterization from ultrasound imagery

NASA Astrophysics Data System (ADS)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

The effects of errors on children's performance on a circle-ellipse discrimination.

PubMed

Stoddard, L T; Sidman, M

1967-05-01

Children first learned by means of a teaching program to discriminate a circle from relatively flat ellipses. Children in the control group then proceeded into a program which gradually reduced the difference between the circle and the ellipses. They advanced to a finer discrimination when they made a correct choice, and reversed to an easier discrimination after making errors ("backup" procedure). The children made relatively few errors until they approached the region of their difference threshold (empirically determined under the conditions described). When they could no longer discriminate the forms, they learned other bases for responding that could be classified as specifiable error patterns. Children in the experimental group, having learned the preliminary circle-ellipse discrimination, were started at the upper end of the ellipse series, where it was impossible for them to discriminate the forms. The backup procedure returned them to an easier discrimination after they made errors. They made many errors and reversed down through the ellipse series. Eventually, most of the children reached a point in the ellipse series where they abandoned their systematic errors and began to make correct first choices; then they advanced upward through the program. All of the children advanced to ellipse sizes that were much larger than the ellipse size at the point of their furthest descent.

Moments and Root-Mean-Square Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2014-06-01

The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge, in the form of a prior distribution on an uncertainty class of feature-label distributions to which the true, but unknown, feature-distribution belongs, can facilitate accurate error estimation (in the mean-square sense) in circumstances where accurate completely model-free error estimation is impossible. This paper provides analytic asymptotically exact finite-sample approximations for various performance metrics of the resulting Bayesian Minimum Mean-Square-Error (MMSE) error estimator in the case of linear discriminant analysis (LDA) in the multivariate Gaussian model. These performance metrics include the first, second, and cross moments of the Bayesian MMSE error estimator with the true error of LDA, and therefore, the Root-Mean-Square (RMS) error of the estimator. We lay down the theoretical groundwork for Kolmogorov double-asymptotics in a Bayesian setting, which enables us to derive asymptotic expressions of the desired performance metrics. From these we produce analytic finite-sample approximations and demonstrate their accuracy via numerical examples. Various examples illustrate the behavior of these approximations and their use in determining the necessary sample size to achieve a desired RMS. The Supplementary Material contains derivations for some equations and added figures.

A comparative study of optimum and suboptimum direct-detection laser ranging receivers

NASA Technical Reports Server (NTRS)

Abshire, J. B.

1978-01-01

A summary of previously proposed receiver strategies for direct-detection laser ranging receivers is presented. Computer simulations are used to compare performance of candidate implementation strategies in the 1- to 100-photoelectron region. Under the condition of no background radiation, the maximum-likelihood and minimum mean-square error estimators were found to give the same performance for both bell-shaped and rectangular optical-pulse shapes. For signal energies greater than 100 photoelectrons, the root-mean-square range error is shown to decrease as Q to the -1/2 power for bell-shaped pulses and Q to the -1 power for rectangular pulses, where Q represents the average pulse energy. Of several receiver implementations presented, the matched-filter peak detector was found to be preferable. A similar configuration, using a constant-fraction discriminator, exhibited a signal-level dependent time bias.

Field testing the ENSEMBLE Minimum Dataset: performance of an instrument to address heterogeneity of treatment effects.

PubMed

Brenneman, Susan K; Shen, Wei; Brekke, Lee; Paczkowski, Rosirene; Bancroft, Tim; Kaplan, Sherrie H; Greenfield, Sheldon; Berger, Marc; Buesching, Don P

2014-09-01

To assess the ability of ENterprising SElective Multi-instrument BLend for hEterogeneity analysis (ENSEMBLE) Minimum Dataset instrument dimensions to discriminate among subgroups of patients expected to have differential outcomes. Patients with Type 2 diabetes, knee osteoarthritis, ischemic heart disease or heart failure completed a survey designed to represent three dimensions (health, personality and behavior). Health-related outcomes and utilization were investigated using claims data. Discriminant validity and associations between the dimensions and outcomes were assessed. A total of 2625 patients completed the survey. The dimensions discriminated 50-100% of the outcome levels across disease cohorts; behavior dimension scores did not differ significantly among the healthcare utilization level subgroups in any disease cohort. ENSEMBLE Minimum Dataset dimensions discriminated health-related outcome levels among patients with varied diseases.

On the assimilation-discrimination relationship in American English adults’ French vowel learning1

PubMed Central

Levy, Erika S.

2009-01-01

A quantitative “cross-language assimilation overlap” method for testing predictions of the Perceptual Assimilation Model (PAM) was implemented to compare results of a discrimination experiment with the listeners’ previously reported assimilation data. The experiment examined discrimination of Parisian French (PF) front rounded vowels ∕y∕ and ∕œ∕. Three groups of American English listeners differing in their French experience (no experience [NoExp], formal experience [ModExp], and extensive formal-plus-immersion experience [HiExp]) performed discrimination of PF ∕y-u∕, ∕y-o∕, ∕œ-o∕, ∕œ-u∕, ∕y-i∕, ∕y-ɛ∕, ∕œ-ɛ∕, ∕œ-i∕, ∕y-œ∕, ∕u-i∕, and ∕a-ɛ∕. Vowels were in bilabial ∕rabVp∕ and alveolar ∕radVt∕ contexts. More errors were found for PF front vs back rounded vowel pairs (16%) than for PF front unrounded vs rounded pairs (2%). Overall, ModExp listeners did not perform more accurately (11% errors) than NoExp listeners (13% errors). Extensive immersion experience, however, was associated with fewer errors (3%) than formal experience alone, although discrimination of PF ∕y-u∕ remained relatively poor (12% errors) for HiExp listeners. More errors occurred on pairs involving front vs back rounded vowels in alveolar context (20% errors) than in bilabial (11% errors). Significant correlations were revealed between listeners’ assimilation overlap scores and their discrimination errors, suggesting that the PAM may be extended to second-language (L2) vowel learning. PMID:19894844

IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion.

PubMed

Dehzangi, Omid; Taherisadr, Mojtaba; ChangalVala, Raghvendar

2017-11-27

The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective. Furthermore, the motion data collected from inertial sensors have complex structure and the detachment between manual feature extraction module and the predictive learning models might limit the generalization capabilities. In this paper, we propose a novel approach for human gait identification using time-frequency (TF) expansion of human gait cycles in order to capture joint 2 dimensional (2D) spectral and temporal patterns of gait cycles. Then, we design a deep convolutional neural network (DCNN) learning to extract discriminative features from the 2D expanded gait cycles and jointly optimize the identification model and the spectro-temporal features in a discriminative fashion. We collect raw motion data from five inertial sensors placed at the chest, lower-back, right hand wrist, right knee, and right ankle of each human subject synchronously in order to investigate the impact of sensor location on the gait identification performance. We then present two methods for early (input level) and late (decision score level) multi-sensor fusion to improve the gait identification generalization performance. We specifically propose the minimum error score fusion (MESF) method that discriminatively learns the linear fusion weights of individual DCNN scores at the decision level by minimizing the error rate on the training data in an iterative manner. 10 subjects participated in this study and hence, the problem is a 10-class identification task. Based on our experimental results, 91% subject identification accuracy was achieved using the best individual IMU and 2DTF-DCNN. We then investigated our proposed early and late sensor fusion approaches, which improved the gait identification accuracy of the system to 93.36% and 97.06%, respectively.

Context affects nestmate recognition errors in honey bees and stingless bees.

PubMed

Couvillon, Margaret J; Segers, Francisca H I D; Cooper-Bowman, Roseanne; Truslove, Gemma; Nascimento, Daniela L; Nascimento, Fabio S; Ratnieks, Francis L W

2013-08-15

Nestmate recognition studies, where a discriminator first recognises and then behaviourally discriminates (accepts/rejects) another individual, have used a variety of methodologies and contexts. This is potentially problematic because recognition errors in discrimination behaviour are predicted to be context-dependent. Here we compare the recognition decisions (accept/reject) of discriminators in two eusocial bees, Apis mellifera and Tetragonisca angustula, under different contexts. These contexts include natural guards at the hive entrance (control); natural guards held in plastic test arenas away from the hive entrance that vary either in the presence or absence of colony odour or the presence or absence of an additional nestmate discriminator; and, for the honey bee, the inside of the nest. For both honey bee and stingless bee guards, total recognition errors of behavioural discrimination made by guards (% nestmates rejected + % non-nestmates accepted) are much lower at the colony entrance (honey bee: 30.9%; stingless bee: 33.3%) than in the test arenas (honey bee: 60-86%; stingless bee: 61-81%; P<0.001 for both). Within the test arenas, the presence of colony odour specifically reduced the total recognition errors in honey bees, although this reduction still fell short of bringing error levels down to what was found at the colony entrance. Lastly, in honey bees, the data show that the in-nest collective behavioural discrimination by ca. 30 workers that contact an intruder is insufficient to achieve error-free recognition and is not as effective as the discrimination by guards at the entrance. Overall, these data demonstrate that context is a significant factor in a discriminators' ability to make appropriate recognition decisions, and should be considered when designing recognition study methodologies.

Authentication and Quantitation of Fraud in Extra Virgin Olive Oils Based on HPLC-UV Fingerprinting and Multivariate Calibration

PubMed Central

Carranco, Núria; Farrés-Cebrián, Mireia; Saurina, Javier

2018-01-01

High performance liquid chromatography method with ultra-violet detection (HPLC-UV) fingerprinting was applied for the analysis and characterization of olive oils, and was performed using a Zorbax Eclipse XDB-C8 reversed-phase column under gradient elution, employing 0.1% formic acid aqueous solution and methanol as mobile phase. More than 130 edible oils, including monovarietal extra-virgin olive oils (EVOOs) and other vegetable oils, were analyzed. Principal component analysis results showed a noticeable discrimination between olive oils and other vegetable oils using raw HPLC-UV chromatographic profiles as data descriptors. However, selected HPLC-UV chromatographic time-window segments were necessary to achieve discrimination among monovarietal EVOOs. Partial least square (PLS) regression was employed to tackle olive oil authentication of Arbequina EVOO adulterated with Picual EVOO, a refined olive oil, and sunflower oil. Highly satisfactory results were obtained after PLS analysis, with overall errors in the quantitation of adulteration in the Arbequina EVOO (minimum 2.5% adulterant) below 2.9%. PMID:29561820

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

NASA Astrophysics Data System (ADS)

Audenaert, Koenraad M. R.; Mosonyi, Milán

2014-10-01

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ1, …, σr. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ1, …, σr), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov's classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min _{j

Implementation of projective measurements with linear optics and continuous photon counting

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

Takeoka, Masahiro; Sasaki, Masahide; Loock, Peter van

2005-02-01

We investigate the possibility of implementing a given projection measurement using linear optics and arbitrarily fast feedforward based on the continuous detection of photons. In particular, we systematically derive the so-called Dolinar scheme that achieves the minimum-error discrimination of binary coherent states. Moreover, we show that the Dolinar-type approach can also be applied to projection measurements in the regime of photonic-qubit signals. Our results demonstrate that for implementing a projection measurement with linear optics, in principle, unit success probability may be approached even without the use of expensive entangled auxiliary states, as they are needed in all known (near-)deterministic linear-opticsmore » proposals.« less

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

A Predictive Model to Identify Patients With Fecal Incontinence Based on High-Definition Anorectal Manometry.

PubMed

Zifan, Ali; Ledgerwood-Lee, Melissa; Mittal, Ravinder K

2016-12-01

Three-dimensional high-definition anorectal manometry (3D-HDAM) is used to assess anal sphincter function; it determines profiles of regional pressure distribution along the length and circumference of the anal canal. There is no consensus, however, on the best way to analyze data from 3D-HDAM to distinguish healthy individuals from persons with sphincter dysfunction. We developed a computer analysis system to analyze 3D-HDAM data and to aid in the diagnosis and assessment of patients with fecal incontinence (FI). In a prospective study, we performed 3D-HDAM analysis of 24 asymptomatic healthy subjects (control subjects; all women; mean age, 39 ± 10 years) and 24 patients with symptoms of FI (all women; mean age, 58 ± 13 years). Patients completed a standardized questionnaire (FI severity index) to score the severity of FI symptoms. We developed and evaluated a robust prediction model to distinguish patients with FI from control subjects using linear discriminant, quadratic discriminant, and logistic regression analyses. In addition to collecting pressure information from the HDAM data, we assessed regional features based on shape characteristics and the anal sphincter pressure symmetry index. The combination of pressure values, anal sphincter area, and reflective symmetry values was identified in patients with FI versus control subjects with an area under the curve value of 1.0. In logistic regression analyses using different predictors, the model identified patients with FI with an area under the curve value of 0.96 (interquartile range, 0.22). In discriminant analysis, results were classified with a minimum error of 0.02, calculated using 10-fold cross-validation; different combinations of predictors produced median classification errors of 0.16 in linear discriminant analysis (interquartile range, 0.25) and 0.08 in quadratic discriminant analysis (interquartile range, 0.25). We developed and validated a novel prediction model to analyze 3D-HDAM data. This system can accurately distinguish patients with FI from control subjects. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Associations between intrusive thoughts, reality discrimination and hallucination-proneness in healthy young adults.

PubMed

Smailes, David; Meins, Elizabeth; Fernyhough, Charles

2015-01-01

People who experience intrusive thoughts are at increased risk of developing hallucinatory experiences, as are people who have weak reality discrimination skills. No study has yet examined whether these two factors interact to make a person especially prone to hallucinatory experiences. The present study examined this question in a non-clinical sample. Participants were 160 students, who completed a reality discrimination task, as well as self-report measures of cannabis use, negative affect, intrusive thoughts and auditory hallucination-proneness. The possibility of an interaction between reality discrimination performance and level of intrusive thoughts was assessed using multiple regression. The number of reality discrimination errors and level of intrusive thoughts were independent predictors of hallucination-proneness. The reality discrimination errors × intrusive thoughts interaction term was significant, with participants who made many reality discrimination errors and reported high levels of intrusive thoughts being especially prone to hallucinatory experiences. Hallucinatory experiences are more likely to occur in people who report high levels of intrusive thoughts and have weak reality discrimination skills. If applicable to clinical samples, these findings suggest that improving patients' reality discrimination skills and reducing the number of intrusive thoughts they experience may reduce the frequency of hallucinatory experiences.

Estimation of discrimination errors in the technique for determining the geographic origin of onions by mineral composition: interlaboratory study.

PubMed

Ariyama, Kaoru; Kadokura, Masashi; Suzuki, Tadanao

2008-01-01

Techniques to determine the geographic origin of foods have been developed for various agricultural and fishery products, and they have used various principles. Some of these techniques are already in use for checking the authenticity of the labeling. Many are based on multielement analysis and chemometrics. We have developed such a technique to determine the geographic origin of onions (Allium cepa L.). This technique, which determines whether an onion is from outside Japan, is designed for onions labeled as having a geographic origin of Hokkaido, Hyogo, or Saga, the main onion production areas in Japan. However, estimations of discrimination errors for this technique have not been fully conducted; they have been limited to those for discrimination models and do not include analytical errors. Interlaboratory studies were conducted to estimate the analytical errors of the technique. Four collaborators each determined 11 elements (Na, Mg, P, Mn, Zn, Rb, Sr, Mo, Cd, Cs, and Ba) in 4 test materials of fresh and dried onions. Discrimination errors in this technique were estimated by summing (1) individual differences within lots, (2) variations between lots from the same production area, and (3) analytical errors. The discrimination errors for onions from Hokkaido, Hyogo, and Saga were estimated to be 2.3, 9.5, and 8.0%, respectively. Those for onions from abroad in determinations targeting Hokkaido, Hyogo, and Saga were estimated to be 28.2, 21.6, and 21.9%, respectively.

Time course of discrimination between emotional facial expressions: the role of visual saliency.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2011-08-01

Saccadic and manual responses were used to investigate the speed of discrimination between happy and non-happy facial expressions in two-alternative-forced-choice tasks. The minimum latencies of correct saccadic responses indicated that the earliest time point at which discrimination occurred ranged between 200 and 280ms, depending on type of expression. Corresponding minimum latencies for manual responses ranged between 440 and 500ms. For both response modalities, visual saliency of the mouth region was a critical factor in facilitating discrimination: The more salient the mouth was in happy face targets in comparison with non-happy distracters, the faster discrimination was. Global image characteristics (e.g., luminance) and semantic factors (i.e., categorical similarity and affective valence of expression) made minor or no contribution to discrimination efficiency. This suggests that visual saliency of distinctive facial features, rather than the significance of expression, is used to make both early and later expression discrimination decisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Minimum-error quantum distinguishability bounds from matrix monotone functions: A comment on 'Two-sided estimates of minimum-error distinguishability of mixed quantum states via generalized Holevo-Curlander bounds' [J. Math. Phys. 50, 032106 (2009)

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

Tyson, Jon

2009-06-15

Matrix monotonicity is used to obtain upper bounds on minimum-error distinguishability of arbitrary ensembles of mixed quantum states. This generalizes one direction of a two-sided bound recently obtained by the author [J. Tyson, J. Math. Phys. 50, 032106 (2009)]. It is shown that the previously obtained special case has unique properties.

Item Discrimination and Type I Error in the Detection of Differential Item Functioning

ERIC Educational Resources Information Center

Li, Yanju; Brooks, Gordon P.; Johanson, George A.

2012-01-01

In 2009, DeMars stated that when impact exists there will be Type I error inflation, especially with larger sample sizes and larger discrimination parameters for items. One purpose of this study is to present the patterns of Type I error rates using Mantel-Haenszel (MH) and logistic regression (LR) procedures when the mean ability between the…

Discriminant WSRC for Large-Scale Plant Species Recognition.

PubMed

Zhang, Shanwen; Zhang, Chuanlei; Zhu, Yihai; You, Zhuhong

2017-01-01

In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.

Image data compression having minimum perceptual error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1995-01-01

A method for performing image compression that eliminates redundant and invisible image components is described. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Method and Apparatus for Powered Descent Guidance

NASA Technical Reports Server (NTRS)

Acikmese, Behcet (Inventor); Blackmore, James C. L. (Inventor); Scharf, Daniel P. (Inventor)

2013-01-01

A method and apparatus for landing a spacecraft having thrusters with non-convex constraints is described. The method first computes a solution to a minimum error landing problem for a convexified constraints, then applies that solution to a minimum fuel landing problem for convexified constraints. The result is a solution that is a minimum error and minimum fuel solution that is also a feasible solution to the analogous system with non-convex thruster constraints.

Joint Entropy for Space and Spatial Frequency Domains Estimated from Psychometric Functions of Achromatic Discrimination

PubMed Central

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised. PMID:24466158

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

PubMed

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised.

Assessing Auditory Discrimination Skill of Malay Children Using Computer-based Method.

PubMed

Ting, H; Yunus, J; Mohd Nordin, M Z

2005-01-01

The purpose of this paper is to investigate the auditory discrimination skill of Malay children using computer-based method. Currently, most of the auditory discrimination assessments are conducted manually by Speech-Language Pathologist. These conventional tests are actually general tests of sound discrimination, which do not reflect the client's specific speech sound errors. Thus, we propose computer-based Malay auditory discrimination test to automate the whole process of assessment as well as to customize the test according to the specific speech error sounds of the client. The ability in discriminating voiced and unvoiced Malay speech sounds was studied for the Malay children aged between 7 and 10 years old. The study showed no major difficulty for the children in discriminating the Malay speech sounds except differentiating /g/-/k/ sounds. Averagely the children of 7 years old failed to discriminate /g/-/k/ sounds.

The perception of complex tones by a false killer whale (Pseudorca crassidens).

PubMed

Yuen, Michelle M L; Nachtigall, Paul E; Breese, Marlee; Vlachos, Stephanie A

2007-03-01

Complex tonal whistles are frequently produced by some odontocete species. However, no experimental evidence exists regarding the detection of complex tones or the discrimination of harmonic frequencies by a marine mammal. The objectives of this investigation were to examine the ability of a false killer whale to discriminate pure tones from complex tones and to determine the minimum intensity level of a harmonic tone required for the whale to make the discrimination. The study was conducted with a go/no-go modified staircase procedure. The different stimuli were complex tones with a fundamental frequency of 5 kHz with one to five harmonic frequencies. The results from this complex tone discrimination task demonstrated: (1) that the false killer whale was able to discriminate a 5 kHz pure tone from a complex tone with up to five harmonics, and (2) that discrimination thresholds or minimum intensity levels exist for each harmonic combination measured. These results indicate that both frequency level and harmonic content may have contributed to the false killer whale's discrimination of complex tones.

Image Data Compression Having Minimum Perceptual Error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1997-01-01

A method is presented for performing color or grayscale image compression that eliminates redundant and invisible image components. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The quantization matrix comprises visual masking by luminance and contrast technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Automatic Recognition of Phonemes Using a Syntactic Processor for Error Correction.

DTIC Science & Technology

1980-12-01

OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS AFIT/GE/EE/8D-45 Robert B. ’Taylor 2Lt USAF Approved for public release...distribution unlimilted. AbP AFIT/GE/EE/ 80D-45 AUTOMATIC RECOGNITION OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS Presented to the...Testing ..................... 37 Bayes Decision Rule for Minimum Error ........... 37 Bayes Decision Rule for Minimum Risk ............ 39 Mini Max Test

Errorless Establishment of a Match-to-Sample Form Discrimination in Preschool Children. I. A Modification of Animal Laboratory Procedures for Children, II. A Comparison of Errorless and Trial-and-Error Discrimination. Progress Report.

ERIC Educational Resources Information Center

LeBlanc, Judith M.

A sequence of studies compared two types of discrimination formation: errorless learning and trial-and-error procedures. The subjects were three boys and five girls from a university preschool. The children performed the experimental tasks at a typical match-to-sample apparatus with one sample window above and four match (response) windows below.…

Design Considerations of Polishing Lap for Computer-Controlled Cylindrical Polishing Process

NASA Technical Reports Server (NTRS)

Khan, Gufran S.; Gubarev, Mikhail; Arnold, William; Ramsey, Brian D.

2009-01-01

This paper establishes a relationship between the polishing process parameters and the generation of mid spatial-frequency error. The consideration of the polishing lap design to optimize the process in order to keep residual errors to a minimum and optimization of the process (speeds, stroke, etc.) and to keep the residual mid spatial-frequency error to a minimum, is also presented.

Synthesis of correlation filters: a generalized space-domain approach for improved filter characteristics

NASA Astrophysics Data System (ADS)

Sudharsanan, Subramania I.; Mahalanobis, Abhijit; Sundareshan, Malur K.

1990-12-01

Discrete frequency domain design of Minimum Average Correlation Energy filters for optical pattern recognition introduces an implementational limitation of circular correlation. An alternative methodology which uses space domain computations to overcome this problem is presented. The technique is generalized to construct an improved synthetic discriminant function which satisfies the conflicting requirements of reduced noise variance and sharp correlation peaks to facilitate ease of detection. A quantitative evaluation of the performance characteristics of the new filter is conducted and is shown to compare favorably with the well known Minimum Variance Synthetic Discriminant Function and the space domain Minimum Average Correlation Energy filter, which are special cases of the present design.

Strong Converse Exponents for a Quantum Channel Discrimination Problem and Quantum-Feedback-Assisted Communication

NASA Astrophysics Data System (ADS)

Cooney, Tom; Mosonyi, Milán; Wilde, Mark M.

2016-06-01

This paper studies the difficulty of discriminating between an arbitrary quantum channel and a "replacer" channel that discards its input and replaces it with a fixed state. The results obtained here generalize those known in the theory of quantum hypothesis testing for binary state discrimination. We show that, in this particular setting, the most general adaptive discrimination strategies provide no asymptotic advantage over non-adaptive tensor-power strategies. This conclusion follows by proving a quantum Stein's lemma for this channel discrimination setting, showing that a constant bound on the Type I error leads to the Type II error decreasing to zero exponentially quickly at a rate determined by the maximum relative entropy registered between the channels. The strong converse part of the lemma states that any attempt to make the Type II error decay to zero at a rate faster than the channel relative entropy implies that the Type I error necessarily converges to one. We then refine this latter result by identifying the optimal strong converse exponent for this task. As a consequence of these results, we can establish a strong converse theorem for the quantum-feedback-assisted capacity of a channel, sharpening a result due to Bowen. Furthermore, our channel discrimination result demonstrates the asymptotic optimality of a non-adaptive tensor-power strategy in the setting of quantum illumination, as was used in prior work on the topic. The sandwiched Rényi relative entropy is a key tool in our analysis. Finally, by combining our results with recent results of Hayashi and Tomamichel, we find a novel operational interpretation of the mutual information of a quantum channel {mathcal{N}} as the optimal Type II error exponent when discriminating between a large number of independent instances of {mathcal{N}} and an arbitrary "worst-case" replacer channel chosen from the set of all replacer channels.

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier

NASA Astrophysics Data System (ADS)

Hashemi, H.; Tax, D. M. J.; Duin, R. P. W.; Javaherian, A.; de Groot, P.

2008-11-01

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA). In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP) and support vector classifier (SVC) are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

PubMed

Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

2017-11-18

Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

PubMed Central

Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

2017-01-01

Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz. PMID:29156581

Minimum Bayes risk image correlation

NASA Technical Reports Server (NTRS)

Minter, T. C., Jr.

1980-01-01

In this paper, the problem of designing a matched filter for image correlation will be treated as a statistical pattern recognition problem. It is shown that, by minimizing a suitable criterion, a matched filter can be estimated which approximates the optimum Bayes discriminant function in a least-squares sense. It is well known that the use of the Bayes discriminant function in target classification minimizes the Bayes risk, which in turn directly minimizes the probability of a false fix. A fast Fourier implementation of the minimum Bayes risk correlation procedure is described.

Label consistent K-SVD: learning a discriminative dictionary for recognition.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2013-11-01

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.

Approximate error conjugation gradient minimization methods

DOEpatents

Kallman, Jeffrey S

2013-05-21

In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.

State Labor Legislation Enacted in 1973

ERIC Educational Resources Information Center

Levy, David A.

1974-01-01

The primary areas considered by State legislatures in 1973 included higher minimum wage rates and broader coverage of minimum wage laws, improved occupational safety, collective bargaining procedures for public employees, elimination of discrimination in employment, and updating of child labor standards. (Author)

Flash-Type Discrimination

NASA Technical Reports Server (NTRS)

Koshak, William J.

2010-01-01

This viewgraph presentation describes the significant progress made in the flash-type discrimination algorithm development. The contents include: 1) Highlights of Progress for GLM-R3 Flash-Type discrimination Algorithm Development; 2) Maximum Group Area (MGA) Data; 3) Retrieval Errors from Simulations; and 4) Preliminary Global-scale Retrieval.

Improved discrimination between monocotyledonous and dicotyledonous plants for weed control based on the blue-green region of ultraviolet-induced fluorescence spectra.

PubMed

Panneton, Bernard; Guillaume, Serge; Roger, Jean-Michel; Samson, Guy

2010-01-01

Precision weeding by spot spraying in real time requires sensors to discriminate between weeds and crop without contact. Among the optical based solutions, the ultraviolet (UV) induced fluorescence of the plants appears as a promising alternative. In a first paper, the feasibility of discriminating between corn hybrids, monocotyledonous, and dicotyledonous weeds was demonstrated on the basis of the complete spectra. Some considerations about the different sources of fluorescence oriented the focus to the blue-green fluorescence (BGF) part, ignoring the chlorophyll fluorescence that is inherently more variable in time. This paper investigates the potential of performing weed/crop discrimination on the basis of several large spectral bands in the BGF area. A partial least squares discriminant analysis (PLS-DA) was performed on a set of 1908 spectra of corn and weed plants over 3 years and various growing conditions. The discrimination between monocotyledonous and dicotyledonous plants based on the blue-green fluorescence yielded robust models (classification error between 1.3 and 4.6% for between-year validation). On the basis of the analysis of the PLS-DA model, two large bands were chosen in the blue-green fluorescence zone (400-425 nm and 425-490 nm). A linear discriminant analysis based on the signal from these two bands also provided very robust inter-year results (classification error from 1.5% to 5.2%). The same selection process was applied to discriminate between monocotyledonous weeds and maize but yielded no robust models (up to 50% inter-year error). Further work will be required to solve this problem and provide a complete UV fluorescence based sensor for weed-maize discrimination.

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

Discriminative echolocation in a porpoise, 12

PubMed Central

Turner, Ronald N.; Norris, Kenneth S.

1966-01-01

Operant conditioning techniques were used to establish a discriminative echolocation performance in a porpoise. Pairs of spheres of disparate diameters were presented in an under-water display, and the positions of the spheres were switched according to a scrambled sequence while the blindfolded porpoise responded on a pair of submerged response levers. Responses which identified the momentary state of the display were food-reinforced, while those which did not (errors) produced time out. Errors were then studied in relation to decreased disparity between the spheres. As disparity was decreased, errors which terminated runs of correct responses occurred more frequently and were followed by longer strings of consecutive errors. Increased errors and disruption of a stable pattern of collateral behavior were associated. Since some sources of error other than decreased disparity were present, the porpoise's final performance did not fully reflect the acuity of its echolocation channel. PMID:5964509

Navigator alignment using radar scan

DOEpatents

Doerry, Armin W.; Marquette, Brandeis

2016-04-05

The various technologies presented herein relate to the determination of and correction of heading error of platform. Knowledge of at least one of a maximum Doppler frequency or a minimum Doppler bandwidth pertaining to a plurality of radar echoes can be utilized to facilitate correction of the heading error. Heading error can occur as a result of component drift. In an ideal situation, a boresight direction of an antenna or the front of an aircraft will have associated therewith at least one of a maximum Doppler frequency or a minimum Doppler bandwidth. As the boresight direction of the antenna strays from a direction of travel at least one of the maximum Doppler frequency or a minimum Doppler bandwidth will shift away, either left or right, from the ideal situation.

Synthetic Aperture Sonar Processing with MMSE Estimation of Image Sample Values

DTIC Science & Technology

2016-12-01

UNCLASSIFIED/UNLIMITED 13. SUPPLEMENTARY NOTES 14. ABSTRACT MMSE (minimum mean- square error) target sample estimation using non-orthogonal basis...orthogonal, they can still be used in a minimum mean‐ square  error (MMSE)  estimator that models the object echo as a weighted sum of the multi‐aspect basis...problem.                     3    Introduction      Minimum mean‐ square  error (MMSE) estimation is applied to target imaging with synthetic aperture

Optimization design of spectral discriminator for high-spectral-resolution lidar based on error analysis.

PubMed

Di, Huige; Zhang, Zhanfei; Hua, Hangbo; Zhang, Jiaqi; Hua, Dengxin; Wang, Yufeng; He, Tingyao

2017-03-06

Accurate aerosol optical properties could be obtained via the high spectral resolution lidar (HSRL) technique, which employs a narrow spectral filter to suppress the Rayleigh or Mie scattering in lidar return signals. The ability of the filter to suppress Rayleigh or Mie scattering is critical for HSRL. Meanwhile, it is impossible to increase the rejection of the filter without limitation. How to optimize the spectral discriminator and select the appropriate suppression rate of the signal is important to us. The HSRL technology was thoroughly studied based on error propagation. Error analyses and sensitivity studies were carried out on the transmittance characteristics of the spectral discriminator. Moreover, ratwo different spectroscopic methods for HSRL were described and compared: one is to suppress the Mie scattering; the other is to suppress the Rayleigh scattering. The corresponding HSRLs were simulated and analyzed. The results show that excessive suppression of Rayleigh scattering or Mie scattering in a high-spectral channel is not necessary if the transmittance of the spectral filter for molecular and aerosol scattering signals can be well characterized. When the ratio of transmittance of the spectral filter for aerosol scattering and molecular scattering is less than 0.1 or greater than 10, the detection error does not change much with its value. This conclusion implies that we have more choices for the high-spectral discriminator in HSRL. Moreover, the detection errors of HSRL regarding the two spectroscopic methods vary greatly with the atmospheric backscattering ratio. To reduce the detection error, it is necessary to choose a reasonable spectroscopic method. The detection method of suppressing the Rayleigh signal and extracting the Mie signal can achieve less error in a clear atmosphere, while the method of suppressing the Mie signal and extracting the Rayleigh signal can achieve less error in a polluted atmosphere.

Discrimination of binary coherent states using a homodyne detector and a photon number resolving detector

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

Wittmann, Christoffer; Sych, Denis; Leuchs, Gerd

2010-06-15

We investigate quantum measurement strategies capable of discriminating two coherent states probabilistically with significantly smaller error probabilities than can be obtained using nonprobabilistic state discrimination. We apply a postselection strategy to the measurement data of a homodyne detector as well as a photon number resolving detector in order to lower the error probability. We compare the two different receivers with an optimal intermediate measurement scheme where the error rate is minimized for a fixed rate of inconclusive results. The photon number resolving (PNR) receiver is experimentally demonstrated and compared to an experimental realization of a homodyne receiver with postselection. Inmore » the comparison, it becomes clear that the performance of the PNR receiver surpasses the performance of the homodyne receiver, which we prove to be optimal within any Gaussian operations and conditional dynamics.« less

Adaptive feedforward control of non-minimum phase structural systems

NASA Astrophysics Data System (ADS)

Vipperman, J. S.; Burdisso, R. A.

1995-06-01

Adaptive feedforward control algorithms have been effectively applied to stationary disturbance rejection. For structural systems, the ideal feedforward compensator is a recursive filter which is a function of the transfer functions between the disturbance and control inputs and the error sensor output. Unfortunately, most control configurations result in a non-minimum phase control path; even a collocated control actuator and error sensor will not necessarily produce a minimum phase control path in the discrete domain. Therefore, the common practice is to choose a suitable approximation of the ideal compensator. In particular, all-zero finite impulse response (FIR) filters are desirable because of their inherent stability for adaptive control approaches. However, for highly resonant systems, large order filters are required for broadband applications. In this work, a control configuration is investigated for controlling non-minimum phase lightly damped structural systems. The control approach uses low order FIR filters as feedforward compensators in a configuration that has one more control actuator than error sensors. The performance of the controller was experimentally evaluated on a simply supported plate under white noise excitation for a two-input, one-output (2I1O) system. The results show excellent error signal reduction, attesting to the effectiveness of the method.

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

PubMed

Zheng, Wenjing; Balzer, Laura; van der Laan, Mark; Petersen, Maya

2018-01-30

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program. In this article, we consider a general class of constrained binary classification problems wherein the objective function and the constraint are both monotonic with respect to a threshold. These include the minimization of the rate of positive predictions subject to a minimum sensitivity, the maximization of sensitivity subject to a maximum rate of positive predictions, and the Neyman-Pearson paradigm, which minimizes the type II error subject to an upper bound on the type I error. We propose an ensemble approach to these binary classification problems based on the Super Learner methodology. This approach linearly combines a user-supplied library of scoring algorithms, with combination weights and a discriminating threshold chosen to minimize the constrained optimality criterion. We then illustrate the application of the proposed classifier to develop an individualized PrEP targeting strategy in a resource-limited setting, with the goal of minimizing the number of PrEP offerings while achieving a minimum required sensitivity. This proof of concept data analysis uses baseline data from the ongoing Sustainable East Africa Research in Community Health study. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Adaptive color halftoning for minimum perceived error using the blue noise mask

NASA Astrophysics Data System (ADS)

Yu, Qing; Parker, Kevin J.

1997-04-01

Color halftoning using a conventional screen requires careful selection of screen angles to avoid Moire patterns. An obvious advantage of halftoning using a blue noise mask (BNM) is that there are no conventional screen angle or Moire patterns produced. However, a simple strategy of employing the same BNM on all color planes is unacceptable in case where a small registration error can cause objectionable color shifts. In a previous paper by Yao and Parker, strategies were presented for shifting or inverting the BNM as well as using mutually exclusive BNMs for different color planes. In this paper, the above schemes will be studied in CIE-LAB color space in terms of root mean square error and variance for luminance channel and chrominance channel respectively. We will demonstrate that the dot-on-dot scheme results in minimum chrominance error, but maximum luminance error and the 4-mask scheme results in minimum luminance error but maximum chrominance error, while the shift scheme falls in between. Based on this study, we proposed a new adaptive color halftoning algorithm that takes colorimetric color reproduction into account by applying 2-mutually exclusive BNMs on two different color planes and applying an adaptive scheme on other planes to reduce color error. We will show that by having one adaptive color channel, we obtain increased flexibility to manipulate the output so as to reduce colorimetric error while permitting customization to specific printing hardware.

A note on the stability and discriminability of graph-based features for classification problems in digital pathology

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Xu, Jun; Madabhushi, Anant

2015-01-01

Nuclear architecture or the spatial arrangement of individual cancer nuclei on histopathology images has been shown to be associated with different grades and differential risk for a number of solid tumors such as breast, prostate, and oropharyngeal. Graph-based representations of individual nuclei (nuclei representing the graph nodes) allows for mining of quantitative metrics to describe tumor morphology. These graph features can be broadly categorized into global and local depending on the type of graph construction method. While a number of local graph (e.g. Cell Cluster Graphs) and global graph (e.g. Voronoi, Delaunay Triangulation, Minimum Spanning Tree) features have been shown to associated with cancer grade, risk, and outcome for different cancer types, the sensitivity of the preceding segmentation algorithms in identifying individual nuclei can have a significant bearing on the discriminability of the resultant features. This therefore begs the question as to which features while being discriminative of cancer grade and aggressiveness are also the most resilient to the segmentation errors. These properties are particularly desirable in the context of digital pathology images, where the method of slide preparation, staining, and type of nuclear segmentation algorithm employed can all dramatically affect the quality of the nuclear graphs and corresponding features. In this paper we evaluated the trade off between discriminability and stability of both global and local graph-based features in conjunction with a few different segmentation algorithms and in the context of two different histopathology image datasets of breast cancer from whole-slide images (WSI) and tissue microarrays (TMA). Specifically in this paper we investigate a few different performance measures including stability, discriminability and stability vs discriminability trade off, all of which are based on p-values from the Kruskal-Wallis one-way analysis of variance for local and global graph features. Apart from identifying the set of local and global features that satisfied the trade off between stability and discriminability, our most interesting finding was that a simple segmentation method was sufficient to identify the most discriminant features for invasive tumour detection in TMAs, whereas for tumour grading in WSI, the graph based features were more sensitive to the accuracy of the segmentation algorithm employed.

Application of genetic algorithm in the evaluation of the profile error of archimedes helicoid surface

NASA Astrophysics Data System (ADS)

Zhu, Lianqing; Chen, Yunfang; Chen, Qingshan; Meng, Hao

2011-05-01

According to minimum zone condition, a method for evaluating the profile error of Archimedes helicoid surface based on Genetic Algorithm (GA) is proposed. The mathematic model of the surface is provided and the unknown parameters in the equation of surface are acquired through least square method. Principle of GA is explained. Then, the profile error of Archimedes Helicoid surface is obtained through GA optimization method. To validate the proposed method, the profile error of an Archimedes helicoid surface, Archimedes Cylindrical worm (ZA worm) surface, is evaluated. The results show that the proposed method is capable of correctly evaluating the profile error of Archimedes helicoid surface and satisfy the evaluation standard of the Minimum Zone Method. It can be applied to deal with the measured data of profile error of complex surface obtained by three coordinate measurement machines (CMM).

Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter

NASA Astrophysics Data System (ADS)

Ramos, M. Rosário; Carolino, E.; Viegas, Carla; Viegas, Sandra

2016-06-01

Health effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 µm, 0.5 µm, 1 µm, 2.5 µm, 5 µm and 10 µm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 µm is the parameter that better discriminates industries.

Cross Validation Through Two-Dimensional Solution Surface for Cost-Sensitive SVM.

PubMed

Gu, Bin; Sheng, Victor S; Tay, Keng Yeow; Romano, Walter; Li, Shuo

2017-06-01

Model selection plays an important role in cost-sensitive SVM (CS-SVM). It has been proven that the global minimum cross validation (CV) error can be efficiently computed based on the solution path for one parameter learning problems. However, it is a challenge to obtain the global minimum CV error for CS-SVM based on one-dimensional solution path and traditional grid search, because CS-SVM is with two regularization parameters. In this paper, we propose a solution and error surfaces based CV approach (CV-SES). More specifically, we first compute a two-dimensional solution surface for CS-SVM based on a bi-parameter space partition algorithm, which can fit solutions of CS-SVM for all values of both regularization parameters. Then, we compute a two-dimensional validation error surface for each CV fold, which can fit validation errors of CS-SVM for all values of both regularization parameters. Finally, we obtain the CV error surface by superposing K validation error surfaces, which can find the global minimum CV error of CS-SVM. Experiments are conducted on seven datasets for cost sensitive learning and on four datasets for imbalanced learning. Experimental results not only show that our proposed CV-SES has a better generalization ability than CS-SVM with various hybrids between grid search and solution path methods, and than recent proposed cost-sensitive hinge loss SVM with three-dimensional grid search, but also show that CV-SES uses less running time.

Discrimination of Aspergillus isolates at the species and strain level by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry fingerprinting.

PubMed

Hettick, Justin M; Green, Brett J; Buskirk, Amanda D; Kashon, Michael L; Slaven, James E; Janotka, Erika; Blachere, Francoise M; Schmechel, Detlef; Beezhold, Donald H

2008-09-15

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to generate highly reproducible mass spectral fingerprints for 12 species of fungi of the genus Aspergillus and 5 different strains of Aspergillus flavus. Prior to MALDI-TOF MS analysis, the fungi were subjected to three 1-min bead beating cycles in an acetonitrile/trifluoroacetic acid solvent. The mass spectra contain abundant peaks in the range of 5 to 20kDa and may be used to discriminate between species unambiguously. A discriminant analysis using all peaks from the MALDI-TOF MS data yielded error rates for classification of 0 and 18.75% for resubstitution and cross-validation methods, respectively. If a subset of 28 significant peaks is chosen, resubstitution and cross-validation error rates are 0%. Discriminant analysis of the MALDI-TOF MS data for 5 strains of A. flavus using all peaks yielded error rates for classification of 0 and 5% for resubstitution and cross-validation methods, respectively. These data indicate that MALDI-TOF MS data may be used for unambiguous identification of members of the genus Aspergillus at both the species and strain levels.

Dissociable contributions of the orbitofrontal and infralimbic cortex to pavlovian autoshaping and discrimination reversal learning: further evidence for the functional heterogeneity of the rodent frontal cortex.

PubMed

Chudasama, Y; Robbins, Trevor W

2003-09-24

To examine possible heterogeneity of function within the ventral regions of the rodent frontal cortex, the present study compared the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) and the infralimbic cortex (ILC) on pavlovian autoshaping and discrimination reversal learning. During the pavlovian autoshaping task, in which rats learn to approach a stimulus predictive of reward [conditional stimulus (CS+)], only the OFC group failed to acquire discriminated approach but was unimpaired when preoperatively trained. In the visual discrimination learning and reversal task, rats were initially required to discriminate a stimulus positively associated with reward. There was no effect of either OFC or ILC lesions on discrimination learning. When the stimulus-reward contingencies were reversed, both groups of animals committed more errors, but only the OFC-lesioned animals were unable to suppress the previously rewarded stimulus-reward association, committing more "stimulus perseverative" errors. In contrast, the ILC group showed a pattern of errors that was more attributable to "learning" than perseveration. These findings suggest two types of dissociation between the effects of OFC and ILC lesions: (1) OFC lesions impaired the learning processes implicated in pavlovian autoshaping but not instrumental simultaneous discrimination learning, whereas ILC lesions were unimpaired at autoshaping and their reversal learning deficit did not reflect perseveration, and (2) OFC lesions induced perseverative responding in reversal learning but did not disinhibit responses to pavlovian CS-. In contrast, the ILC lesion had no effect on response inhibitory control in either of these settings. The findings are discussed in the context of dissociable executive functions in ventral sectors of the rat prefrontal cortex.

Cost effectiveness of the U.S. Geological Survey's stream-gaging program in Wisconsin

USGS Publications Warehouse

Walker, J.F.; Osen, L.L.; Hughes, P.E.

1987-01-01

A minimum budget of $510,000 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gaging stations. At this minimum budget, the theoretical average standard error of instantaneous discharge is 14.4%. The maximum budget analyzed was $650,000 and resulted in an average standard of error of instantaneous discharge of 7.2%. 

Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber

PubMed Central

Zaghloul, Mohamed A. S.; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P.

2018-01-01

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores’ temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μϵ/MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%). PMID:29649148

Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber.

PubMed

Zaghloul, Mohamed A S; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P

2018-04-12

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores' temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μ ϵ /MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%).

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks

PubMed Central

Jang, Hojin; Plis, Sergey M.; Calhoun, Vince D.; Lee, Jong-Hwan

2016-01-01

Feedforward deep neural networks (DNN), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean ± standard deviation; %) of 6.9 (± 3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4 ± 4.6) and the two-layer network (7.4 ± 4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. PMID:27079534

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

PubMed

Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

Discrimination of corn from monocotyledonous weeds with ultraviolet (UV) induced fluorescence.

PubMed

Panneton, Bernard; Guillaume, Serge; Samson, Guy; Roger, Jean-Michel

2011-01-01

In production agriculture, savings in herbicides can be achieved if weeds can be discriminated from crop, allowing the targeting of weed control to weed-infested areas only. Previous studies demonstrated the potential of ultraviolet (UV) induced fluorescence to discriminate corn from weeds and recently, robust models have been obtained for the discrimination between monocots (including corn) and dicots. Here, we developed a new approach to achieve robust discrimination of monocot weeds from corn. To this end, four corn hybrids (Elite 60T05, Monsanto DKC 26-78, Pioneer 39Y85 (RR), and Syngenta N2555 (Bt, LL)) and four monocot weeds (Digitaria ischaemum (Schreb.) I, Echinochloa crus-galli (L.) Beauv., Panicum capillare (L.), and Setaria glauca (L.) Beauv.) were grown either in a greenhouse or in a growth cabinet and UV (327 nm) induced fluorescence spectra (400 to 755 nm) were measured under controlled or uncontrolled ambient light intensity and temperature. This resulted in three contrasting data sets suitable for testing the robustness of discrimination models. In the blue-green region (400 to 550 nm), the shape of the spectra did not contain any useful information for discrimination. Therefore, the integral of the blue-green region (415 to 455 nm) was used as a normalizing factor for the red fluorescence intensity (670 to 755 nm). The shape of the normalized red fluorescence spectra did not contribute to the discrimination and in the end, only the integral of the normalized red fluorescence intensity was left as a single discriminant variable. Applying a threshold on this variable minimizing the classification error resulted in calibration errors ranging from 14.2% to 15.8%, but this threshold varied largely between data sets. Therefore, to achieve robustness, a model calibration scheme was developed based on the collection of a calibration data set from 75 corn plants. From this set, a new threshold can be estimated as the 85% quantile on the cumulative frequency curve of the integral of the normalized red fluorescence. With this approach the classification error was nearly constant (16.0% to 18.5%), thereby indicating the potential of UV-induced fluorescence to reliably discriminate corn from monocot weeds.

Global distortion of GPS networks associated with satellite antenna model errors

NASA Astrophysics Data System (ADS)

Cardellach, E.; Elósegui, P.; Davis, J. L.

2007-07-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by ˜1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PCO errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm yr-1 level, which will impact high-precision crustal deformation studies.

Global Distortion of GPS Networks Associated with Satellite Antenna Model Errors

NASA Technical Reports Server (NTRS)

Cardellach, E.; Elosequi, P.; Davis, J. L.

2007-01-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by approx.1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PC0 errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm/yr level, which will impact high-precision crustal deformation studies.

Sound localization skills in children who use bilateral cochlear implants and in children with normal acoustic hearing

PubMed Central

Grieco-Calub, Tina M.; Litovsky, Ruth Y.

2010-01-01

Objectives To measure sound source localization in children who have sequential bilateral cochlear implants (BICIs); to determine if localization accuracy correlates with performance on a right-left discrimination task (i.e., spatial acuity); to determine if there is a measurable bilateral benefit on a sound source identification task (i.e., localization accuracy) by comparing performance under bilateral and unilateral listening conditions; to determine if sound source localization continues to improve with longer durations of bilateral experience. Design Two groups of children participated in this study: a group of 21 children who received BICIs in sequential procedures (5–14 years old) and a group of 7 typically-developing children with normal acoustic hearing (5 years old). Testing was conducted in a large sound-treated booth with loudspeakers positioned on a horizontal arc with a radius of 1.2 m. Children participated in two experiments that assessed spatial hearing skills. Spatial hearing acuity was assessed with a discrimination task in which listeners determined if a sound source was presented on the right or left side of center; the smallest angle at which performance on this task was reliably above chance is the minimum audible angle. Sound localization accuracy was assessed with a sound source identification task in which children identified the perceived position of the sound source from a multi-loudspeaker array (7 or 15); errors are quantified using the root-mean-square (RMS) error. Results Sound localization accuracy was highly variable among the children with BICIs, with RMS errors ranging from 19°–56°. Performance of the NH group, with RMS errors ranging from 9°–29° was significantly better. Within the BICI group, in 11/21 children RMS errors were smaller in the bilateral vs. unilateral listening condition, indicating bilateral benefit. There was a significant correlation between spatial acuity and sound localization accuracy (R2=0.68, p<0.01), suggesting that children who achieve small RMS errors tend to have the smallest MAAs. Although there was large intersubject variability, testing of 11 children in the BICI group at two sequential visits revealed a subset of children who show improvement in spatial hearing skills over time. Conclusions A subset of children who use sequential BICIs can acquire sound localization abilities, even after long intervals between activation of hearing in the first- and second-implanted ears. This suggests that children with activation of the second implant later in life may be capable of developing spatial hearing abilities. The large variability in performance among the children with BICIs suggests that maturation of sound localization abilities in children with BICIs may be dependent on various individual subject factors such as age of implantation and chronological age. PMID:20592615

Magnetic Nanoparticle Thermometer: An Investigation of Minimum Error Transmission Path and AC Bias Error

PubMed Central

Du, Zhongzhou; Su, Rijian; Liu, Wenzhong; Huang, Zhixing

2015-01-01

The signal transmission module of a magnetic nanoparticle thermometer (MNPT) was established in this study to analyze the error sources introduced during the signal flow in the hardware system. The underlying error sources that significantly affected the precision of the MNPT were determined through mathematical modeling and simulation. A transfer module path with the minimum error in the hardware system was then proposed through the analysis of the variations of the system error caused by the significant error sources when the signal flew through the signal transmission module. In addition, a system parameter, named the signal-to-AC bias ratio (i.e., the ratio between the signal and AC bias), was identified as a direct determinant of the precision of the measured temperature. The temperature error was below 0.1 K when the signal-to-AC bias ratio was higher than 80 dB, and other system errors were not considered. The temperature error was below 0.1 K in the experiments with a commercial magnetic fluid (Sample SOR-10, Ocean Nanotechnology, Springdale, AR, USA) when the hardware system of the MNPT was designed with the aforementioned method. PMID:25875188

Color discrimination performance in patients with Alzheimer's disease.

PubMed

Salamone, Giovanna; Di Lorenzo, Concetta; Mosti, Serena; Lupo, Federica; Cravello, Luca; Palmer, Katie; Musicco, Massimo; Caltagirone, Carlo

2009-01-01

Visual deficits are frequent in Alzheimer's disease (AD), yet little is known about the nature of these disturbances. The aim of the present study was to investigate color discrimination in patients with AD to determine whether impairment of this visual function is a cognitive or perceptive/sensory disturbance. A cross-sectional clinical study was conducted in a specialized dementia unit on 20 patients with mild/moderate AD and 21 age-matched normal controls. Color discrimination was measured by the Farnsworth-Munsell 100 hue test. Cognitive functioning was measured with the Mini-Mental State Examination (MMSE) and a comprehensive battery of neuropsychological tests. The scores obtained on the color discrimination test were compared between AD patients and controls adjusting for global and domain-specific cognitive performance. Color discrimination performance was inversely related to MMSE score. AD patients had a higher number of errors in color discrimination than controls (mean +/- SD total error score: 442.4 +/- 84.5 vs. 304.1 +/- 45.9). This trend persisted even after adjustment for MMSE score and cognitive performance on specific cognitive domains. A specific reduction of color discrimination capacity is present in AD patients. This deficit does not solely depend upon cognitive impairment, and involvement of the primary visual cortex and/or retinal ganglionar cells may be contributory.

Classification accuracy on the family planning participation status using kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Kurniawan, Dian; Suparti; Sugito

2018-05-01

Population growth in Indonesia has increased every year. According to the population census conducted by the Central Bureau of Statistics (BPS) in 2010, the population of Indonesia has reached 237.6 million people. Therefore, to control the population growth rate, the government hold Family Planning or Keluarga Berencana (KB) program for couples of childbearing age. The purpose of this program is to improve the health of mothers and children in order to manifest prosperous society by controlling births while ensuring control of population growth. The data used in this study is the updated family data of Semarang city in 2016 that conducted by National Family Planning Coordinating Board (BKKBN). From these data, classifiers with kernel discriminant analysis will be obtained, and also classification accuracy will be obtained from that method. The result of the analysis showed that normal kernel discriminant analysis gives 71.05 % classification accuracy with 28.95 % classification error. Whereas triweight kernel discriminant analysis gives 73.68 % classification accuracy with 26.32 % classification error. Using triweight kernel discriminant for data preprocessing of family planning participation of childbearing age couples in Semarang City of 2016 can be stated better than with normal kernel discriminant.

LDPC Codes with Minimum Distance Proportional to Block Size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel; Thorpe, Jeremy

2009-01-01

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.

Searching for discrimination rules in protease proteolytic cleavage activity using genetic programming with a min-max scoring function.

PubMed

Yang, Zheng Rong; Thomson, Rebecca; Hodgman, T Charles; Dry, Jonathan; Doyle, Austin K; Narayanan, Ajit; Wu, XiKun

2003-11-01

This paper presents an algorithm which is able to extract discriminant rules from oligopeptides for protease proteolytic cleavage activity prediction. The algorithm is developed using genetic programming. Three important components in the algorithm are a min-max scoring function, the reverse Polish notation (RPN) and the use of minimum description length. The min-max scoring function is developed using amino acid similarity matrices for measuring the similarity between an oligopeptide and a rule, which is a complex algebraic equation of amino acids rather than a simple pattern sequence. The Fisher ratio is then calculated on the scoring values using the class label associated with the oligopeptides. The discriminant ability of each rule can therefore be evaluated. The use of RPN makes the evolutionary operations simpler and therefore reduces the computational cost. To prevent overfitting, the concept of minimum description length is used to penalize over-complicated rules. A fitness function is therefore composed of the Fisher ratio and the use of minimum description length for an efficient evolutionary process. In the application to four protease datasets (Trypsin, Factor Xa, Hepatitis C Virus and HIV protease cleavage site prediction), our algorithm is superior to C5, a conventional method for deriving decision trees.

Image-adapted visually weighted quantization matrices for digital image compression

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1994-01-01

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Synthesis and analysis of discriminators under influence of broadband non-Gaussian noise

NASA Astrophysics Data System (ADS)

Artyushenko, V. M.; Volovach, V. I.

2018-01-01

We considered the problems of the synthesis and analysis of discriminators, when the useful signal is exposed to non-Gaussian additive broadband noise. It is shown that in this case, the discriminator of the tracking meter should contain the nonlinear transformation unit, the characteristics of which are determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian broadband noise and mismatch errors. The parameters of the discriminatory and phase characteristics of the discriminators working under the above conditions are obtained. It is shown that the efficiency of non-linear processing depends on the ratio of power of FM noise to the power of Gaussian noise. The analysis of the information loss of signal transformation caused by the linear section of discriminatory characteristics of the unit of nonlinear transformations of the discriminator is carried out. It is shown that the average slope of the nonlinear transformation characteristic is determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian noise and mismatch errors.

SAMPLING DISTRIBUTIONS OF ERROR IN MULTIDIMENSIONAL SCALING.

ERIC Educational Resources Information Center

STAKE, ROBERT E.; AND OTHERS

AN EMPIRICAL STUDY WAS MADE OF THE ERROR FACTORS IN MULTIDIMENSIONAL SCALING (MDS) TO REFINE THE USE OF MDS FOR MORE EXPERT MANIPULATION OF SCALES USED IN EDUCATIONAL MEASUREMENT. THE PURPOSE OF THE RESEARCH WAS TO GENERATE TABLES OF THE SAMPLING DISTRIBUTIONS THAT ARE NECESSARY FOR DISCRIMINATING BETWEEN ERROR AND NONERROR MDS DIMENSIONS. THE…

Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)

DTIC Science & Technology

2011-01-01

Minimum Error Bounded Efficient `1 Tracker with Occlusion Detection Xue Mei\\ ∗ Haibin Ling† Yi Wu†[ Erik Blasch‡ Li Bai] \\Assembly Test Technology...proposed BPR-L1 tracker is tested on several challenging benchmark sequences involving chal- lenges such as occlusion and illumination changes. In all...point method de - pends on the value of the regularization parameter λ. In the experiments, we found that the total number of PCG is a few hundred. The

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Development of a homogeneous pulse shape discriminating flow-cell radiation detection system

NASA Astrophysics Data System (ADS)

Hastie, K. H.; DeVol, T. A.; Fjeld, R. A.

1999-02-01

A homogeneous flow-cell radiation detection system which utilizes coincidence counting and pulse shape discrimination circuitry was assembled and tested with five commercially available liquid scintillation cocktails. Two of the cocktails, Ultima Flo (Packard) and Mono Flow 5 (National Diagnostics) have low viscosities and are intended for flow applications; and three of the cocktails, Optiphase HiSafe 3 (Wallac), Ultima Gold AB (Packard), and Ready Safe (Beckman), have higher viscosities and are intended for static applications. The low viscosity cocktails were modified with 1-methylnaphthalene to increase their capability for alpha/beta pulse shape discrimination. The sample loading and pulse shape discriminator setting were optimized to give the lowest minimum detectable concentration for alpha radiation in a 30 s count time. Of the higher viscosity cocktails, Optiphase HiSafe 3 had the lowest minimum detectable activities for alpha and beta radiation, 0.2 and 0.4 Bq/ml for 233U and 90Sr/ 90Y, respectively, for a 30 s count time. The sample loading was 70% and the corresponding alpha/beta spillover was 5.5%. Of the low viscosity cocktails, Mono Flow 5 modified with 2.5% (by volume) 1-methylnaphthalene resulted in the lowest minimum detectable activities for alpha and beta radiation; 0.3 and 0.5 Bq/ml for 233U and 90Sr/ 90Y, respectively, for a 30 s count time. The sample loading was 50%, and the corresponding alpha/beta spillover was 16.6%. HiSafe 3 at a 10% sample loading was used to evaluate the system under simulated flow conditions.

SVM-Based Synthetic Fingerprint Discrimination Algorithm and Quantitative Optimization Strategy

PubMed Central

Chen, Suhang; Chang, Sheng; Huang, Qijun; He, Jin; Wang, Hao; Huang, Qiangui

2014-01-01

Synthetic fingerprints are a potential threat to automatic fingerprint identification systems (AFISs). In this paper, we propose an algorithm to discriminate synthetic fingerprints from real ones. First, four typical characteristic factors—the ridge distance features, global gray features, frequency feature and Harris Corner feature—are extracted. Then, a support vector machine (SVM) is used to distinguish synthetic fingerprints from real fingerprints. The experiments demonstrate that this method can achieve a recognition accuracy rate of over 98% for two discrete synthetic fingerprint databases as well as a mixed database. Furthermore, a performance factor that can evaluate the SVM's accuracy and efficiency is presented, and a quantitative optimization strategy is established for the first time. After the optimization of our synthetic fingerprint discrimination task, the polynomial kernel with a training sample proportion of 5% is the optimized value when the minimum accuracy requirement is 95%. The radial basis function (RBF) kernel with a training sample proportion of 15% is a more suitable choice when the minimum accuracy requirement is 98%. PMID:25347063

Spectroscopic planetary detection

NASA Technical Reports Server (NTRS)

Deming, D.; Espenak, F.; Hillman, J. J.; Kostiuk, T.; Mumma, M. J.; Jennings, D. E.

1986-01-01

The Sun-as-a-star was monitored using the McMath Fourier transform spectometer (FTS) on Kitt Peak in 1983. In 1985 the first measurement was made using the laser heterodyne technique. The FTS measurements now extend for three years, with errors of order 3 meters/sec at a given epoch. Over this 3 year period, a 33 meter/sec change was measured in the apparent velocity of integrated sunlight. The sense of the effect is that a greater blueshift is seen near solar minimum, which is consistent with expectations based on considering the changing morphology of solar granular convection. Presuming this effect is solar-cycle-related, it will mimic the Doppler reflex produced by a planetary companion of approximately two Jupiter masses, with an 11 year orbital period. Thus, Jupiter itself is below the threshold for detection by spectroscopic means, without an additional technique for discrimination. However, for planetary companions in shorter period orbits (P approx. 3 years) the threshold for unambiguous detection is well below one Jupiter mass.

New subspace methods for ATR

NASA Astrophysics Data System (ADS)

Zhang, Peng; Peng, Jing; Sims, S. Richard F.

2005-05-01

In ATR applications, each feature is a convolution of an image with a filter. It is important to use most discriminant features to produce compact representations. We propose two novel subspace methods for dimension reduction to address limitations associated with Fukunaga-Koontz Transform (FKT). The first method, Scatter-FKT, assumes that target is more homogeneous, while clutter can be anything other than target and anywhere. Thus, instead of estimating a clutter covariance matrix, Scatter-FKT computes a clutter scatter matrix that measures the spread of clutter from the target mean. We choose dimensions along which the difference in variation between target and clutter is most pronounced. When the target follows a Gaussian distribution, Scatter-FKT can be viewed as a generalization of FKT. The second method, Optimal Bayesian Subspace, is derived from the optimal Bayesian classifier. It selects dimensions such that the minimum Bayes error rate can be achieved. When both target and clutter follow Gaussian distributions, OBS computes optimal subspace representations. We compare our methods against FKT using character image as well as IR data.

Discrimination performance in aging is vulnerable to interference and dissociable from spatial memory

PubMed Central

Johnson, Sarah A.; Sacks, Patricia K.; Turner, Sean M.; Gaynor, Leslie S.; Ormerod, Brandi K.; Maurer, Andrew P.; Bizon, Jennifer L.

2016-01-01

Hippocampal-dependent episodic memory and stimulus discrimination abilities are both compromised in the elderly. The reduced capacity to discriminate between similar stimuli likely contributes to multiple aspects of age-related cognitive impairment; however, the association of these behaviors within individuals has never been examined in an animal model. In the present study, young and aged F344×BN F1 hybrid rats were cross-characterized on the Morris water maze test of spatial memory and a dentate gyrus-dependent match-to-position test of spatial discrimination ability. Aged rats showed overall impairments relative to young in spatial learning and memory on the water maze task. Although young and aged learned to apply a match-to-position response strategy in performing easy spatial discriminations within a similar number of trials, a majority of aged rats were impaired relative to young in performing difficult spatial discriminations on subsequent tests. Moreover, all aged rats were susceptible to cumulative interference during spatial discrimination tests, such that error rate increased on later trials of test sessions. These data suggest that when faced with difficult discriminations, the aged rats were less able to distinguish current goal locations from those of previous trials. Increasing acetylcholine levels with donepezil did not improve aged rats’ abilities to accurately perform difficult spatial discriminations or reduce their susceptibility to interference. Interestingly, better spatial memory abilities were not significantly associated with higher performance on difficult spatial discriminations. This observation, along with the finding that aged rats made more errors under conditions in which interference was high, suggests that match-to-position spatial discrimination performance may rely on extra-hippocampal structures such as the prefrontal cortex, in addition to the dentate gyrus. PMID:27317194

Discrimination of plant-parasitic nematodes from complex soil communities using ecometagenetics.

PubMed

Porazinska, Dorota L; Morgan, Matthew J; Gaspar, John M; Court, Leon N; Hardy, Christopher M; Hodda, Mike

2014-07-01

Many plant pathogens are microscopic, cryptic, and difficult to diagnose. The new approach of ecometagenetics, involving ultrasequencing, bioinformatics, and biostatistics, has the potential to improve diagnoses of plant pathogens such as nematodes from the complex mixtures found in many agricultural and biosecurity situations. We tested this approach on a gradient of complexity ranging from a few individuals from a few species of known nematode pathogens in a relatively defined substrate to a complex and poorly known suite of nematode pathogens in a complex forest soil, including its associated biota of unknown protists, fungi, and other microscopic eukaryotes. We added three known but contrasting species (Pratylenchus neglectus, the closely related P. thornei, and Heterodera avenae) to half the set of substrates, leaving the other half without them. We then tested whether all nematode pathogens-known and unknown, indigenous, and experimentally added-were detected consistently present or absent. We always detected the Pratylenchus spp. correctly and with the number of sequence reads proportional to the numbers added. However, a single cyst of H. avenae was only identified approximately half the time it was present. Other plant-parasitic nematodes and nematodes from other trophic groups were detected well but other eukaryotes were detected less consistently. DNA sampling errors or informatic errors or both were involved in misidentification of H. avenae; however, the proportions of each varied in the different bioinformatic pipelines and with different parameters used. To a large extent, false-positive and false-negative errors were complementary: pipelines and parameters with the highest false-positive rates had the lowest false-negative rates and vice versa. Sources of error identified included assumptions in the bioinformatic pipelines, slight differences in primer regions, the number of sequence reads regarded as the minimum threshold for inclusion in analysis, and inaccessible DNA in resistant life stages. Identification of the sources of error allows us to suggest ways to improve identification using ecometagenetics.

The multiple hop test: a discriminative or evaluative instrument for chronic ankle instability?

PubMed

Eechaute, Christophe; Bautmans, Ivan; De Hertogh, Willem; Vaes, Peter

2012-05-01

To determine whether the multiple hop test should be used as an evaluative or a discriminative instrument for chronic ankle instability (CAI). Blinded case-control study. : University research laboratory. Twenty-nine healthy subjects (21 men, 8 women, mean age 21.8 years) and 29 patients with CAI (17 men, 12 women, mean age 24.9 years) were selected. Subjects performed a multiple hop test and hopped on 10 different tape markers while trying to avoid any postural correction. Minimal detectable changes (MDC) of the number of balance errors, the time value, and the visual analog scale (VAS) score (perceived difficulty) were calculated as evaluative measures. For the discriminative properties, a receiver operating characteristic curve was determined and the area under curve (AUC), the sensitivity, specificity, diagnostic accuracy (DA), and likelihood ratios (LR) were calculated whether 1, 2, or 3 outcomes were positive. Based on their MDC, outcomes should, respectively, change by more than 7 errors (41%), 6 seconds (15%), and 27 mm (55%, VAS score) before considering it as a real change. Area under curves were, respectively, 79% (errors), 77% (time value), and 65% (VAS score). The most optimal cutoff point was, respectively, 13.5 errors, 35 seconds, and 32.5 mm. When 2 of 3 outcomes were positive, the sensitivity was 86%, the specificity was 79%, the DA was 83%, the positive LR was 4.2, and the negative LR was 0.17. The multiple hop test seems to be more a discriminative instrument for CAI, and its responsiveness needs to be demonstrated.

Direct Analysis in Real Time-Mass Spectrometry & Kohonen Artificial Neural Networks for the Rapid Species Identification of Larvae, Pupae and Adult Life Stages of Carrion Insects.

PubMed

Beyramysoltan, Samira; Giffen, Justine E; Rosati, Jennifer Y; Musah, Rabi Ann

2018-06-20

Species determination of the various life stages of flies (order: Diptera) is challenging, particularly for the immature forms, because analogous life stages of different species are difficult to differentiate morphologically. It is demonstrated here that DART high-resolution mass spectrometry (DART-HRMS) combined with supervised Kohonen Self-Organizing Maps (SOM) enables accomplishment of species-level identification of larvae, pupae and adult life stages of carrion flies. DART-HRMS data for each life stage were acquired from analysis of ethanol suspensions representing Calliphoridae, Phoridae and Sarcophagidae families, without additional sample preparation. After preprocessing, the data were subjected to a combination of minimum Redundancy Maximal Relevance (mRMR) and Sparse Discriminant Analysis (SDA) methods to select the most significant variables for creating accurate SOM models. The resulting data were divided into training and validation sets, and then analyzed by the SOM method to define the proper discrimination models. The 5-fold venetian blind cross-validation misclassification error was below 7% for all life stages, and the validation samples were correctly identified in all cases. The multiclass SOM model also revealed which chemical components were the most significant markers for each species, with several of these being amino acids. The results show that processing of DART-HRMS data using artificial neural networks (ANNs) based on the Kohonen SOM approach enables rapid discrimination and identification of fly species even for the immature life stages. The ANNs can be continuously expanded to include a larger number of species, and can be used to screen DART-HRMS data from unknowns to rapidly determine species identity.

The selective M1 muscarinic cholinergic agonist CDD-0102A enhances working memory and cognitive flexibility.

PubMed

Ragozzino, Michael E; Artis, Sonja; Singh, Amritha; Twose, Trevor M; Beck, Joseph E; Messer, William S

2012-03-01

Various neurodegenerative diseases and psychiatric disorders are marked by alterations in brain cholinergic function and cognitive deficits. Efforts to alleviate such deficits have been limited by a lack of selective M(1) muscarinic agonists. 5-(3-Ethyl-1,2,4-oxadiazol-5-yl)-1,4,5,6-tetrahydropyrimidine hydrochloride (CDD-0102A) is a partial agonist at M(1) muscarinic receptors with limited activity at other muscarinic receptor subtypes. The present studies investigated the effects of CDD-0102A on working memory and strategy shifting in rats. CDD-0102A administered intraperitoneally 30 min before testing at 0.1, 0.3, and 1 mg/kg significantly enhanced delayed spontaneous alternation performance in a four-arm cross maze, suggesting improvement in working memory. In separate experiments, CDD-0102A had potent enhancing effects on learning and switching between a place and visual cue discrimination. Treatment with CDD-0102A did not affect acquisition of either a place or visual cue discrimination. In contrast, CDD-0102A at 0.03 and 0.1 mg/kg significantly enhanced a shift between a place and visual cue discrimination. Analysis of the errors in the shift to the place or shift to the visual cue strategy revealed that in both cases CDD-0102A significantly increased the ability to initially inhibit a previously relevant strategy and maintain a new, relevant strategy once selected. In anesthetized rats, the minimum dose required to induce salivation was approximately 0.3 mg/kg i.p. Salivation increased with dose, and the estimated ED(50) was 2.0 mg/kg. The data suggest that CDD-0102A has unique memory and cognitive enhancing properties that might be useful in the treatment of neurological disorders at doses that do not produce adverse effects such as salivation.

Government mandates and employer-sponsored health insurance: who is still not covered?

PubMed

Vanness, David J; Wolfe, Barbara L

2002-06-01

We characterize employer-sponsored health insurance offering strategies in light of benefit non-discrimination and minimum wage regulation when workers have heterogeneous earnings and partially unobservable demand for (and cost of) insurance. We then empirically examine how earnings and expected medical expenses are associated with low wage workers' ability to obtain insurance before and after enactment of federal benefit non-discrimination rules. We find no evidence that the non-discrimination rules helped low wage workers (especially those with high own or children's expected medical expenses) to obtain insurance.

Stitching-error reduction in gratings by shot-shifted electron-beam lithography

NASA Technical Reports Server (NTRS)

Dougherty, D. J.; Muller, R. E.; Maker, P. D.; Forouhar, S.

2001-01-01

Calculations of the grating spatial-frequency spectrum and the filtering properties of multiple-pass electron-beam writing demonstrate a tradeoff between stitching-error suppression and minimum pitch separation. High-resolution measurements of optical-diffraction patterns show a 25-dB reduction in stitching-error side modes.

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

Statistical analysis of nonlinearly reconstructed near-infrared tomographic images: Part I--Theory and simulations.

PubMed

Pogue, Brian W; Song, Xiaomei; Tosteson, Tor D; McBride, Troy O; Jiang, Shudong; Paulsen, Keith D

2002-07-01

Near-infrared (NIR) diffuse tomography is an emerging method for imaging the interior of tissues to quantify concentrations of hemoglobin and exogenous chromophores non-invasively in vivo. It often exploits an optical diffusion model-based image reconstruction algorithm to estimate spatial property values from measurements of the light flux at the surface of the tissue. In this study, mean-squared error (MSE) over the image is used to evaluate methods for regularizing the ill-posed inverse image reconstruction problem in NIR tomography. Estimates of image bias and image standard deviation were calculated based upon 100 repeated reconstructions of a test image with randomly distributed noise added to the light flux measurements. It was observed that the bias error dominates at high regularization parameter values while variance dominates as the algorithm is allowed to approach the optimal solution. This optimum does not necessarily correspond to the minimum projection error solution, but typically requires further iteration with a decreasing regularization parameter to reach the lowest image error. Increasing measurement noise causes a need to constrain the minimum regularization parameter to higher values in order to achieve a minimum in the overall image MSE.

Idiographic duo-trio tests using a constant-reference based on preference of each consumer: Sample presentation sequence in difference test can be customized for individual consumers to reduce error.

PubMed

Kim, Min-A; Sim, Hye-Min; Lee, Hye-Seong

2016-11-01

As reformulations and processing changes are increasingly needed in the food industry to produce healthier, more sustainable, and cost effective products while maintaining superior quality, reliable measurements of consumers' sensory perception and discrimination are becoming more critical. Consumer discrimination methods using a preferred-reference duo-trio test design have been shown to be effective in improving the discrimination performance by customizing sample presentation sequences. However, this design can add complexity to the discrimination task for some consumers, resulting in more errors in sensory discrimination. The objective of the present study was to investigate the effects of different types of test instructions using the preference-reference duo-trio test design where a paired-preference test is followed by 6 repeated preferred-reference duo-trio tests, in comparison to the analytical method using the balanced-reference duo-trio. Analyses of d' estimates (product-related measure) and probabilistic sensory discriminators in momentary numbers of subjects showing statistical significance (subject-related measure) revealed that only preferred-reference duo-trio test using affective reference-framing, either by providing no information about the reference or information on a previously preferred sample, improved the sensory discrimination more than the analytical method. No decrease in discrimination performance was observed with any type of instruction, confirming that consumers could handle the test methods. These results suggest that when repeated tests are feasible, using the affective discrimination method would be operationally more efficient as well as ecologically more reliable for measuring consumers' sensory discrimination ability. Copyright © 2016 Elsevier Ltd. All rights reserved.

Maximum Relative Entropy of Coherence: An Operational Coherence Measure.

PubMed

Bu, Kaifeng; Singh, Uttam; Fei, Shao-Ming; Pati, Arun Kumar; Wu, Junde

2017-10-13

The operational characterization of quantum coherence is the cornerstone in the development of the resource theory of coherence. We introduce a new coherence quantifier based on maximum relative entropy. We prove that the maximum relative entropy of coherence is directly related to the maximum overlap with maximally coherent states under a particular class of operations, which provides an operational interpretation of the maximum relative entropy of coherence. Moreover, we show that, for any coherent state, there are examples of subchannel discrimination problems such that this coherent state allows for a higher probability of successfully discriminating subchannels than that of all incoherent states. This advantage of coherent states in subchannel discrimination can be exactly characterized by the maximum relative entropy of coherence. By introducing a suitable smooth maximum relative entropy of coherence, we prove that the smooth maximum relative entropy of coherence provides a lower bound of one-shot coherence cost, and the maximum relative entropy of coherence is equivalent to the relative entropy of coherence in the asymptotic limit. Similar to the maximum relative entropy of coherence, the minimum relative entropy of coherence has also been investigated. We show that the minimum relative entropy of coherence provides an upper bound of one-shot coherence distillation, and in the asymptotic limit the minimum relative entropy of coherence is equivalent to the relative entropy of coherence.

Radial orbit error reduction and sea surface topography determination using satellite altimetry

NASA Technical Reports Server (NTRS)

Engelis, Theodossios

1987-01-01

A method is presented in satellite altimetry that attempts to simultaneously determine the geoid and sea surface topography with minimum wavelengths of about 500 km and to reduce the radial orbit error caused by geopotential errors. The modeling of the radial orbit error is made using the linearized Lagrangian perturbation theory. Secular and second order effects are also included. After a rather extensive validation of the linearized equations, alternative expressions of the radial orbit error are derived. Numerical estimates for the radial orbit error and geoid undulation error are computed using the differences of two geopotential models as potential coefficient errors, for a SEASAT orbit. To provide statistical estimates of the radial distances and the geoid, a covariance propagation is made based on the full geopotential covariance. Accuracy estimates for the SEASAT orbits are given which agree quite well with already published results. Observation equations are develped using sea surface heights and crossover discrepancies as observables. A minimum variance solution with prior information provides estimates of parameters representing the sea surface topography and corrections to the gravity field that is used for the orbit generation. The simulation results show that the method can be used to effectively reduce the radial orbit error and recover the sea surface topography.

Force and Directional Force Modulation Effects on Accuracy and Variability in Low-Level Pinch Force Tracking.

PubMed

Park, Sangsoo; Spirduso, Waneen; Eakin, Tim; Abraham, Lawrence

2018-01-01

The authors investigated how varying the required low-level forces and the direction of force change affect accuracy and variability of force production in a cyclic isometric pinch force tracking task. Eighteen healthy right-handed adult volunteers performed the tracking task over 3 different force ranges. Root mean square error and coefficient of variation were higher at lower force levels and during minimum reversals compared with maximum reversals. Overall, the thumb showed greater root mean square error and coefficient of variation scores than did the index finger during maximum reversals, but not during minimum reversals. The observed impaired performance during minimum reversals might originate from history-dependent mechanisms of force production and highly coupled 2-digit performance.

Speech perception task with pseudowords.

PubMed

Appezzato, Mariana Martins; Hackerott, Maria Mercedes Saraiva; Avila, Clara Regina Brandão de

2018-01-01

Purpose Prepare a list of pseudowords in Brazilian Portuguese to assess the auditory discrimination ability of schoolchildren and investigate the internal consistency of test items and the effect of school grade on discrimination performance. Methods Study participants were 60 schoolchildren (60% female) enrolled in the 3rd (n=14), 4th (n=24) and 5th (n=22) grades of an elementary school in the city of Sao Paulo, Brazil, aged between eight years and two months and 11 years and eight months (99 to 136 months; mean=120.05; SD=10.26), with average school performance score of 7.21 (minimum 5.0; maximum 10; SD=1.23). Forty-eight minimal pairs of Brazilian Portuguese pseudowords distinguished by a single phoneme were prepared. The participants' responses (whether the elements of the pairs were the same or different) were noted and analyzed. The data were analyzed using the Cronbach's Alpha Coefficient, Spearman's Correlation Coefficient, and Bonferroni Post-hoc Test at significance level of 0.05. Results Internal consistency analysis indicated the deletion of 20 pairs. The 28 items with results showed good internal consistency (α=0.84). The maximum and minimum scores of correct discrimination responses were 34 and 16, respectively (mean=30.79; SD=3.68). No correlation was observed between age, school performance, and discrimination performance, and no difference between school grades was found. Conclusion Most of the items proposed for assessing the auditory discrimination of speech sounds showed good internal consistency in relation to the task. Age and school grade did not improve the auditory discrimination of speech sounds.

Validation of the Kp Geomagnetic Index Forecast at CCMC

NASA Astrophysics Data System (ADS)

Frechette, B. P.; Mays, M. L.

2017-12-01

The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

Stack Number Influence on the Accuracy of Aster Gdem (V2)

NASA Astrophysics Data System (ADS)

Mirzadeh, S. M. J.; Alizadeh Naeini, A.; Fatemi, S. B.

2017-09-01

In this research, the influence of stack number (STKN) on the accuracy of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (GDEM) has been investigated. For this purpose, two data sets of ASTER and Reference DEMs from two study areas with various topography (Bomehen and Tazehabad) were used. The Results show that in both study areas, STKN of 19 results in minimum error so that this minimum error has small difference with other STKN. The analysis of slope, STKN, and error values shows that there is no strong correlation between these parameters in both study areas. For example, the value of mean absolute error increase by changing the topography and the increase of slope values and height on cells but, the changes in STKN has no important effect on error values. Furthermore, according to high values of STKN, effect of slope on elevation accuracy has practically decreased. Also, there is no great correlation between the residual and STKN in ASTER GDEM.

Characterization of the International Linear Collider damping ring optics

NASA Astrophysics Data System (ADS)

Shanks, J.; Rubin, D. L.; Sagan, D.

2014-10-01

A method is presented for characterizing the emittance dilution and dynamic aperture for an arbitrary closed lattice that includes guide field magnet errors, multipole errors and misalignments. This method, developed and tested at the Cornell Electron Storage Ring Test Accelerator (CesrTA), has been applied to the damping ring lattice for the International Linear Collider (ILC). The effectiveness of beam based emittance tuning is limited by beam position monitor (BPM) measurement errors, number of corrector magnets and their placement, and correction algorithm. The specifications for damping ring magnet alignment, multipole errors, number of BPMs, and precision in BPM measurements are shown to be consistent with the required emittances and dynamic aperture. The methodology is then used to determine the minimum number of position monitors that is required to achieve the emittance targets, and how that minimum depends on the location of the BPMs. Similarly, the maximum tolerable multipole errors are evaluated. Finally, the robustness of each BPM configuration with respect to random failures is explored.

Comparison of radiographic joint space width and magnetic resonance imaging for prediction of knee replacement: A longitudinal case-control study from the Osteoarthritis Initiative.

PubMed

Eckstein, Felix; Boudreau, Robert; Wang, Zhijie; Hannon, Michael J; Duryea, Jeff; Wirth, Wolfgang; Cotofana, Sebastian; Guermazi, Ali; Roemer, Frank; Nevitt, Michael; John, Markus R; Ladel, Christoph; Sharma, Leena; Hunter, David J; Kwoh, C Kent

2016-06-01

To evaluate whether change in fixed-location measures of radiographic joint space width (JSW) and cartilage thickness by MRI predict knee replacement. Knees replaced between 36 and 60 months' follow-up in the Osteoarthritis Initiative were each matched with one control by age, sex and radiographic status. Radiographic JSW was determined from fixed flexion radiographs and subregional femorotibial cartilage thickness from 3 T MRI. Changes between the annual visit before replacement (T0) and 2 years before T0 (T-2) were compared using conditional logistic regression. One hundred and nineteen knees from 102 participants (55.5 % women; age 64.2 ± 8.7 [mean ± SD] years) were studied. Fixed-location JSW change at 22.5 % from medial to lateral differed more between replaced and control knees (case-control [cc] OR = 1.57; 95 % CI: 1.23-2.01) than minimum medial JSW change (ccOR = 1.38; 95 % CI: 1.11-1.71). Medial femorotibial cartilage loss displayed discrimination similar to minimum JSW, and central tibial cartilage loss similar to fixed-location JSW. Location-independent thinning and thickening scores were elevated prior to knee replacement. Discrimination of structural progression between knee pre-placement cases versus controls was stronger for fixed-location than minimum radiographic JSW. MRI displayed similar discrimination to radiography and suggested greater simultaneous cartilage thickening and loss prior to knee replacement. • Fixed-location JSW predicts surgical knee replacement more strongly than minimum JSW. • MRI predicts knee replacement with similar accuracy to radiographic JSW. • MRI reveals greater cartilage thinning and thickening prior to knee replacement.

"Presumed fair: Ironic effects of organizational diversity structures": Correction to Kaiser et al. (2013).

PubMed

2016-06-01

Reports an error in "Presumed fair: Ironic effects of organizational diversity structures" by Cheryl R. Kaiser, Brenda Major, Ines Jurcevic, Tessa L. Dover, Laura M. Brady and Jenessa R. Shapiro (Journal of Personality and Social Psychology, 2013[Mar], Vol 104[3], 504-519). In the article, a raw data merging error in one racial discrimination claim condition from Experiment 6 inadvertently resulted in data analyses on an inaccurate data set. When the error was discovered by the authors and corrected, all analyses reported in Experiment 6 for claim validity, seriousness of the claim, and support for the claimant were inaccurate and none were statistically significant. The conclusions should be altered to indicate that participants with management experience who reflected on their own workplace diversity policies did not show the predicted effects. The literature review, remaining five studies, and remaining conclusions in the article are unaffected by this error. Experiment 6 should also report that 26.4% (not 26.4.7%) of participants had a graduate degree and eight participants (not 8%) did not provide educational data. Experiment 5 should have referred to the claim validity measure as a six-item measure ( .92) rather than a five-item measure; analyses on claim validity are accurate in text. Table 2's note should have said standard errors, not standard deviations. (The following abstract of the original article appeared in record 2012-31077-001.) This research tests the hypothesis that the presence (vs. absence) of organizational diversity structures causes high-status group members (Whites, men) to perceive organizations with diversity structures as procedurally fairer environments for underrepresented groups (racial minorities, women), even when it is clear that underrepresented groups have been unfairly disadvantaged within these organizations. Furthermore, this illusory sense of fairness derived from the mere presence of diversity structures causes high-status group members to legitimize the status quo by becoming less sensitive to discrimination targeted at underrepresented groups and reacting more harshly toward underrepresented group members who claim discrimination. Six experiments support these hypotheses in designs using 4 types of diversity structures (diversity policies, diversity training, diversity awards, idiosyncratically generated diversity structures from participants' own organizations) among 2 high-status groups in tests involving several types of discrimination (discriminatory promotion practices, adverse impact in hiring, wage discrimination). Implications of these experiments for organizational diversity and employment discrimination law are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Sex determination from the radius and ulna in a modern South African sample.

PubMed

Barrier, I L O; L'Abbé, E N

2008-07-18

With a large number of unidentified skeletal remains found in South Africa, the development of population specific osteometric standards is imperative. Forensic anthropologists need to have access to a variety of techniques to establish accurate demographic profiles from complete, fragmentary and/or commingled remains. No research has been done on the forearm of African samples, even though these bones have been shown to exhibit sexual dimorphism. The purpose of this paper is to develop discriminant function formulae to determine sex from the radius and ulna in a South African population. The sample consisted of 200 male and 200 female skeletons from the Pretoria Bone (University of Pretoria) and Raymond A. Dart (Witwatersrand University) collections. Sixteen standard anthropometric measurements were taken from the radius (9) and ulna (7) and subjected to stepwise and direct discriminant function analysis. Distal breadth, minimum mid-shaft diameter and maximum head diameter were the best discriminators of sex for the radius, while minimum mid-shaft diameter and olecranon breadth were selected for the ulna. Classification accuracy for the forearm ranged from 76 to 86%. The radius and ulna can be considered moderate discriminators for determining sex in a South African group. However, it is advised that these formulae are used in conjunction with additional methods to determine sex.

Simplified Approach Charts Improve Data Retrieval Performance

PubMed Central

Stewart, Michael; Laraway, Sean; Jordan, Kevin; Feary, Michael S.

2016-01-01

The effectiveness of different instrument approach charts to deliver minimum visibility and altitude information during airport equipment outages was investigated. Eighteen pilots flew simulated instrument approaches in three conditions: (a) normal operations using a standard approach chart (standard-normal), (b) equipment outage conditions using a standard approach chart (standard-outage), and (c) equipment outage conditions using a prototype decluttered approach chart (prototype-outage). Errors and retrieval times in identifying minimum altitudes and visibilities were measured. The standard-outage condition produced significantly more errors and longer retrieval times versus the standard-normal condition. The prototype-outage condition had significantly fewer errors and shorter retrieval times than did the standard-outage condition. The prototype-outage condition produced significantly fewer errors but similar retrieval times when compared with the standard-normal condition. Thus, changing the presentation of minima may reduce risk and increase safety in instrument approaches, specifically with airport equipment outages. PMID:28491009

Optimal plane search method in blood flow measurements by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Bargiel, Pawel; Orkisz, Maciej; Przelaskowski, Artur; Piatkowska-Janko, Ewa; Bogorodzki, Piotr; Wolak, Tomasz

2004-07-01

This paper offers an algorithm for determining the blood flow parameters in the neck vessel segments using a single (optimal) measurement plane instead of the usual approach involving four planes orthogonal to the artery axis. This new approach aims at significantly shortening the time required to complete measurements using Nuclear Magnetic Resonance techniques. Based on a defined error function, the algorithm scans the solution space to find the minimum of the error function, and thus to determine a single plane characterized by a minimum measurement error, which allows for an accurate measurement of blood flow in the four carotid arteries. The paper also comprises a practical implementation of this method (as a module of a larger imaging-measuring system), including preliminary research results.

Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging.

PubMed

Iannaccone, Reto; Hauser, Tobias U; Ball, Juliane; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2015-10-01

Attention-deficit/hyperactivity disorder (ADHD) is a common disabling psychiatric disorder associated with consistent deficits in error processing, inhibition and regionally decreased grey matter volumes. The diagnosis is based on clinical presentation, interviews and questionnaires, which are to some degree subjective and would benefit from verification through biomarkers. Here, pattern recognition of multiple discriminative functional and structural brain patterns was applied to classify adolescents with ADHD and controls. Functional activation features in a Flanker/NoGo task probing error processing and inhibition along with structural magnetic resonance imaging data served to predict group membership using support vector machines (SVMs). The SVM pattern recognition algorithm correctly classified 77.78% of the subjects with a sensitivity and specificity of 77.78% based on error processing. Predictive regions for controls were mainly detected in core areas for error processing and attention such as the medial and dorsolateral frontal areas reflecting deficient processing in ADHD (Hart et al., in Hum Brain Mapp 35:3083-3094, 2014), and overlapped with decreased activations in patients in conventional group comparisons. Regions more predictive for ADHD patients were identified in the posterior cingulate, temporal and occipital cortex. Interestingly despite pronounced univariate group differences in inhibition-related activation and grey matter volumes the corresponding classifiers failed or only yielded a poor discrimination. The present study corroborates the potential of task-related brain activation for classification shown in previous studies. It remains to be clarified whether error processing, which performed best here, also contributes to the discrimination of useful dimensions and subtypes, different psychiatric disorders, and prediction of treatment success across studies and sites.

45 CFR 286.205 - How will we determine if a Tribe fails to meet the minimum work participation rate(s)?

Code of Federal Regulations, 2012 CFR

2012-10-01

..., financial records, and automated data systems; (ii) The data are free from computational errors and are... records, financial records, and automated data systems; (ii) The data are free from computational errors... records, and automated data systems; (ii) The data are free from computational errors and are internally...

Nimodipine alters acquisition of a visual discrimination task in chicks.

PubMed

Deyo, R; Panksepp, J; Conner, R L

1990-03-01

Chicks 5 days old received intraperitoneal injections of nimodipine 30 min before training on either a visual discrimination task (0, 0.5, 1.0, or 5.0 mg/kg) or a test of separation-induced distress vocalizations (0, 0.5, or 2.5 mg/kg). Chicks receiving 1.0 mg/kg nimodipine made significantly fewer visual discrimination errors than vehicle controls by trials 41-60, but did not differ from controls 24 h later. Chicks in the 5 mg/kg group made significantly more errors when compared to controls both during acquisition of the task and during retention. Nimodipine did not alter separation-induced distress vocalizations at any of the doses tested, suggesting that nimodipine's effects on learning cannot be attributed to a reduction in separation distress. These data indicate that nimodipine's facilitation of learning in young subjects is dose dependent, but nimodipine failed to enhance retention.

Signal-Detection Analyses of Conditional Discrimination and Delayed Matching-to-Sample Performance

ERIC Educational Resources Information Center

Alsop, Brent

2004-01-01

Quantitative analyses of stimulus control and reinforcer control in conditional discriminations and delayed matching-to-sample procedures often encounter a problem; it is not clear how to analyze data when subjects have not made errors. The present article examines two common methods for overcoming this problem. Monte Carlo simulations of…

Enhancing interferometer phase estimation, sensing sensitivity, and resolution using robust entangled states

NASA Astrophysics Data System (ADS)

Smith, James F.

2017-11-01

With the goal of designing interferometers and interferometer sensors, e.g., LADARs with enhanced sensitivity, resolution, and phase estimation, states using quantum entanglement are discussed. These states include N00N states, plain M and M states (PMMSs), and linear combinations of M and M states (LCMMS). Closed form expressions for the optimal detection operators; visibility, a measure of the state's robustness to loss and noise; a resolution measure; and phase estimate error, are provided in closed form. The optimal resolution for the maximum visibility and minimum phase error are found. For the visibility, comparisons between PMMSs, LCMMS, and N00N states are provided. For the minimum phase error, comparisons between LCMMS, PMMSs, N00N states, separate photon states (SPSs), the shot noise limit (SNL), and the Heisenberg limit (HL) are provided. A representative collection of computational results illustrating the superiority of LCMMS when compared to PMMSs and N00N states is given. It is found that for a resolution 12 times the classical result LCMMS has visibility 11 times that of N00N states and 4 times that of PMMSs. For the same case, the minimum phase error for LCMMS is 10.7 times smaller than that of PMMS and 29.7 times smaller than that of N00N states.

Automated error correction in IBM quantum computer and explicit generalization

NASA Astrophysics Data System (ADS)

Ghosh, Debjit; Agarwal, Pratik; Pandey, Pratyush; Behera, Bikash K.; Panigrahi, Prasanta K.

2018-06-01

Construction of a fault-tolerant quantum computer remains a challenging problem due to unavoidable noise and fragile quantum states. However, this goal can be achieved by introducing quantum error-correcting codes. Here, we experimentally realize an automated error correction code and demonstrate the nondestructive discrimination of GHZ states in IBM 5-qubit quantum computer. After performing quantum state tomography, we obtain the experimental results with a high fidelity. Finally, we generalize the investigated code for maximally entangled n-qudit case, which could both detect and automatically correct any arbitrary phase-change error, or any phase-flip error, or any bit-flip error, or combined error of all types of error.

Dynamic Positron Emission Tomography [PET] in Man Using Small Bismuth Germanate Crystals

DOE R&D Accomplishments Database

Derenzo, S. E.; Budinger, T. F.; Huesman, R. H.; Cahoon, J. L.

1982-04-01

Primary considerations for the design of positron emission tomographs for medical studies in humans are the need for high imaging sensitivity, whole organ coverage, good spatial resolution, high maximum data rates, adequate spatial sampling with minimum mechanical motion, shielding against out of plane activity, pulse height discrimination against scattered photons, and timing discrimination against accidental coincidences. We discuss the choice of detectors, sampling motion, shielding, and electronics to meet these objectives.

Decision-theoretic saliency: computational principles, biological plausibility, and implications for neurophysiology and psychophysics.

PubMed

Gao, Dashan; Vasconcelos, Nuno

2009-01-01

A decision-theoretic formulation of visual saliency, first proposed for top-down processing (object recognition) (Gao & Vasconcelos, 2005a), is extended to the problem of bottom-up saliency. Under this formulation, optimality is defined in the minimum probability of error sense, under a constraint of computational parsimony. The saliency of the visual features at a given location of the visual field is defined as the power of those features to discriminate between the stimulus at the location and a null hypothesis. For bottom-up saliency, this is the set of visual features that surround the location under consideration. Discrimination is defined in an information-theoretic sense and the optimal saliency detector derived for a class of stimuli that complies with known statistical properties of natural images. It is shown that under the assumption that saliency is driven by linear filtering, the optimal detector consists of what is usually referred to as the standard architecture of V1: a cascade of linear filtering, divisive normalization, rectification, and spatial pooling. The optimal detector is also shown to replicate the fundamental properties of the psychophysics of saliency: stimulus pop-out, saliency asymmetries for stimulus presence versus absence, disregard of feature conjunctions, and Weber's law. Finally, it is shown that the optimal saliency architecture can be applied to the solution of generic inference problems. In particular, for the class of stimuli studied, it performs the three fundamental operations of statistical inference: assessment of probabilities, implementation of Bayes decision rule, and feature selection.

The Differences in Error Rate and Type between IELTS Writing Bands and Their Impact on Academic Workload

ERIC Educational Resources Information Center

Müller, Amanda

2015-01-01

This paper attempts to demonstrate the differences in writing between International English Language Testing System (IELTS) bands 6.0, 6.5 and 7.0. An analysis of exemplars provided from the IELTS test makers reveals that IELTS 6.0, 6.5 and 7.0 writers can make a minimum of 206 errors, 96 errors and 35 errors per 1000 words. The following section…

Influence of ECG measurement accuracy on ECG diagnostic statements.

PubMed

Zywietz, C; Celikag, D; Joseph, G

1996-01-01

Computer analysis of electrocardiograms (ECGs) provides a large amount of ECG measurement data, which may be used for diagnostic classification and storage in ECG databases. Until now, neither error limits for ECG measurements have been specified nor has their influence on diagnostic statements been systematically investigated. An analytical method is presented to estimate the influence of measurement errors on the accuracy of diagnostic ECG statements. Systematic (offset) errors will usually result in an increase of false positive or false negative statements since they cause a shift of the working point on the receiver operating characteristics curve. Measurement error dispersion broadens the distribution function of discriminative measurement parameters and, therefore, usually increases the overlap between discriminative parameters. This results in a flattening of the receiver operating characteristics curve and an increase of false positive and false negative classifications. The method developed has been applied to ECG conduction defect diagnoses by using the proposed International Electrotechnical Commission's interval measurement tolerance limits. These limits appear too large because more than 30% of false positive atrial conduction defect statements and 10-18% of false intraventricular conduction defect statements could be expected due to tolerated measurement errors. To assure long-term usability of ECG measurement databases, it is recommended that systems provide its error tolerance limits obtained on a defined test set.

Perception of Self-Motion and Regulation of Walking Speed in Young-Old Adults.

PubMed

Lalonde-Parsi, Marie-Jasmine; Lamontagne, Anouk

2015-07-01

Whether a reduced perception of self-motion contributes to poor walking speed adaptations in older adults is unknown. In this study, speed discrimination thresholds (perceptual task) and walking speed adaptations (walking task) were compared between young (19-27 years) and young-old individuals (63-74 years), and the relationship between the performance on the two tasks was examined. Participants were evaluated while viewing a virtual corridor in a helmet-mounted display. Speed discrimination thresholds were determined using a staircase procedure. Walking speed modulation was assessed on a self-paced treadmill while exposed to different self-motion speeds ranging from 0.25 to 2 times the participants' comfortable speed. For each speed, participants were instructed to match the self-motion speed described by the moving corridor. On the walking task, participants displayed smaller walking speed errors at comfortable walking speeds compared with slower of faster speeds. The young-old adults presented larger speed discrimination thresholds (perceptual experiment) and larger walking speed errors (walking experiment) compared with young adults. Larger walking speed errors were associated with higher discrimination thresholds. The enhanced performance on the walking task at comfortable speed suggests that intersensory calibration processes are influenced by experience, hence optimized for frequently encountered conditions. The altered performance of the young-old adults on the perceptual and walking tasks, as well as the relationship observed between the two tasks, suggest that a poor perception of visual motion information may contribute to the poor walking speed adaptations that arise with aging.

Quantum state discrimination bounds for finite sample size

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

Audenaert, Koenraad M. R.; Mosonyi, Milan; Mathematical Institute, Budapest University of Technology and Economics, Egry Jozsef u 1., Budapest 1111

2012-12-15

In the problem of quantum state discrimination, one has to determine by measurements the state of a quantum system, based on the a priori side information that the true state is one of the two given and completely known states, {rho} or {sigma}. In general, it is not possible to decide the identity of the true state with certainty, and the optimal measurement strategy depends on whether the two possible errors (mistaking {rho} for {sigma}, or the other way around) are treated as of equal importance or not. Results on the quantum Chernoff and Hoeffding bounds and the quantum Stein'smore » lemma show that, if several copies of the system are available then the optimal error probabilities decay exponentially in the number of copies, and the decay rate is given by a certain statistical distance between {rho} and {sigma} (the Chernoff distance, the Hoeffding distances, and the relative entropy, respectively). While these results provide a complete solution to the asymptotic problem, they are not completely satisfying from a practical point of view. Indeed, in realistic scenarios one has access only to finitely many copies of a system, and therefore it is desirable to have bounds on the error probabilities for finite sample size. In this paper we provide finite-size bounds on the so-called Stein errors, the Chernoff errors, the Hoeffding errors, and the mixed error probabilities related to the Chernoff and the Hoeffding errors.« less

Acute stress influences the discrimination of complex scenes and complex faces in young healthy men.

PubMed

Paul, M; Lech, R K; Scheil, J; Dierolf, A M; Suchan, B; Wolf, O T

2016-04-01

The stress-induced release of glucocorticoids has been demonstrated to influence hippocampal functions via the modulation of specific receptors. At the behavioral level stress is known to influence hippocampus dependent long-term memory. In recent years, studies have consistently associated the hippocampus with the non-mnemonic perception of scenes, while adjacent regions in the medial temporal lobe were associated with the perception of objects, and faces. So far it is not known whether and how stress influences non-mnemonic perceptual processes. In a behavioral study, fifty male participants were subjected either to the stressful socially evaluated cold-pressor test or to a non-stressful control procedure, before they completed a visual discrimination task, comprising scenes and faces. The complexity of the face and scene stimuli was manipulated in easy and difficult conditions. A significant three way interaction between stress, stimulus type and complexity was found. Stressed participants tended to commit more errors in the complex scenes condition. For complex faces a descriptive tendency in the opposite direction (fewer errors under stress) was observed. As a result the difference between the number of errors for scenes and errors for faces was significantly larger in the stress group. These results indicate that, beyond the effects of stress on long-term memory, stress influences the discrimination of spatial information, especially when the perception is characterized by a high complexity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of three-dimensional optical coherence tomography and combining a rotating Scheimpflug camera with a Placido topography system for forme fruste keratoconus diagnosis.

PubMed

Fukuda, Shinichi; Beheregaray, Simone; Hoshi, Sujin; Yamanari, Masahiro; Lim, Yiheng; Hiraoka, Takahiro; Yasuno, Yoshiaki; Oshika, Tetsuro

2013-12-01

To evaluate the ability of parameters measured by three-dimensional (3D) corneal and anterior segment optical coherence tomography (CAS-OCT) and a rotating Scheimpflug camera combined with a Placido topography system (Scheimpflug camera with topography) to discriminate between normal eyes and forme fruste keratoconus. Forty-eight eyes of 48 patients with keratoconus, 25 eyes of 25 patients with forme fruste keratoconus and 128 eyes of 128 normal subjects were evaluated. Anterior and posterior keratometric parameters (steep K, flat K, average K), elevation, topographic parameters, regular and irregular astigmatism (spherical, asymmetry, regular and higher-order astigmatism) and five pachymetric parameters (minimum, minimum-median, inferior-superior, inferotemporal-superonasal, vertical thinnest location of the cornea) were measured using 3D CAS-OCT and a Scheimpflug camera with topography. The area under the receiver operating curve (AUROC) was calculated to assess the discrimination ability. Compatibility and repeatability of both devices were evaluated. Posterior surface elevation showed higher AUROC values in discrimination analysis of forme fruste keratoconus using both devices. Both instruments showed significant linear correlations (p<0.05, Pearson's correlation coefficient) and good repeatability (ICCs: 0.885-0.999) for normal and forme fruste keratoconus. Posterior elevation was the best discrimination parameter for forme fruste keratoconus. Both instruments presented good correlation and repeatability for this condition.

Testing a dynamic-field account of interactions between spatial attention and spatial working memory.

PubMed

Johnson, Jeffrey S; Spencer, John P

2016-05-01

Studies examining the relationship between spatial attention and spatial working memory (SWM) have shown that discrimination responses are faster for targets appearing at locations that are being maintained in SWM, and that location memory is impaired when attention is withdrawn during the delay. These observations support the proposal that sustained attention is required for successful retention in SWM: If attention is withdrawn, memory representations are likely to fail, increasing errors. In the present study, this proposal was reexamined in light of a neural-process model of SWM. On the basis of the model's functioning, we propose an alternative explanation for the observed decline in SWM performance when a secondary task is performed during retention: SWM representations drift systematically toward the location of targets appearing during the delay. To test this explanation, participants completed a color discrimination task during the delay interval of a spatial-recall task. In the critical shifting-attention condition, the color stimulus could appear either toward or away from the midline reference axis, relative to the memorized location. We hypothesized that if shifting attention during the delay leads to the failure of SWM representations, there should be an increase in the variance of recall errors, but no change in directional errors, regardless of the direction of the shift. Conversely, if shifting attention induces drift of SWM representations-as predicted by the model-systematic changes in the patterns of spatial-recall errors should occur that would depend on the direction of the shift. The results were consistent with the latter possibility-recall errors were biased toward the locations of discrimination targets appearing during the delay.

Testing a Dynamic Field Account of Interactions between Spatial Attention and Spatial Working Memory

PubMed Central

Johnson, Jeffrey S.; Spencer, John P.

2016-01-01

Studies examining the relationship between spatial attention and spatial working memory (SWM) have shown that discrimination responses are faster for targets appearing at locations that are being maintained in SWM, and that location memory is impaired when attention is withdrawn during the delay. These observations support the proposal that sustained attention is required for successful retention in SWM: if attention is withdrawn, memory representations are likely to fail, increasing errors. In the present study, this proposal is reexamined in light of a neural process model of SWM. On the basis of the model's functioning, we propose an alternative explanation for the observed decline in SWM performance when a secondary task is performed during retention: SWM representations drift systematically toward the location of targets appearing during the delay. To test this explanation, participants completed a color-discrimination task during the delay interval of a spatial recall task. In the critical shifting attention condition, the color stimulus could appear either toward or away from the memorized location relative to a midline reference axis. We hypothesized that if shifting attention during the delay leads to the failure of SWM representations, there should be an increase in the variance of recall errors but no change in directional error, regardless of the direction of the shift. Conversely, if shifting attention induces drift of SWM representations—as predicted by the model—there should be systematic changes in the pattern of spatial recall errors depending on the direction of the shift. Results were consistent with the latter possibility—recall errors were biased toward the location of discrimination targets appearing during the delay. PMID:26810574

Handwriting Error Patterns of Children with Mild Motor Difficulties.

ERIC Educational Resources Information Center

Malloy-Miller, Theresa; And Others

1995-01-01

A test of handwriting legibility and 6 perceptual-motor tests were completed by 66 children ages 7-12. Among handwriting error patterns, execution was associated with visual-motor skill and sensory discrimination, aiming with visual-motor and fine-motor skills. The visual-spatial factor had no significant association with perceptual-motor…

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

The Gulliver Effect: The Impact of Error in an Elephantine Subpopulation on Estimates for Lilliputian Subpopulations

ERIC Educational Resources Information Center

Micceri, Theodore; Parasher, Pradnya; Waugh, Gordon W.; Herreid, Charlene

2009-01-01

An extensive review of the research literature and a study comparing over 36,000 survey responses with archival true scores indicated that one should expect a minimum of at least three percent random error for the least ambiguous of self-report measures. The Gulliver Effect occurs when a small proportion of error in a sizable subpopulation exerts…

The effects of nidopallium caudolaterale inactivation on serial-order behaviour in pigeons (Columba livia).

PubMed

Johnston, Melissa Jane; Clarkson, Andrew N; Gowing, Emma K; Scarf, Damian; Colombo, Mike

2018-06-06

Serial-order behaviour is the ability to complete a sequence of responses in a predetermined order to achieve a reward. In birds, serial-order behaviour is thought to be impaired by damage to the nidopallium caudolaterale (NCL). In the current study, we examined the role of the NCL in serial-order behaviour by training pigeons on a 4-item serial-order task and a go/no-go discrimination task. Following training, pigeons were received infusions of 1μl of either tetrodotoxin (TTX) or saline. Saline infusions had no impact on serial-order behaviour whereas TTX infusions resulted in a significant decrease in performance. The serial-order impairments, however, were not the results of errors of any specific error at any specific list item. With respect to the go/no-go discrimination task, saline infusions also had no impact on performance whereas TTX infusions impaired pigeons' discrimination abilities. Given the impairments on the go/no-go discrimination task, which does not require processing of serial-order information, we tentatively conclude that damage to the NCL does not impair serial-order behaviour per se, but rather results in a more generalised impairment that may impact performance across a range of tasks.

Legal consequences of the moral duty to report errors.

PubMed

Hall, Jacqulyn Kay

2003-09-01

Increasingly, clinicians are under a moral duty to report errors to the patients who are injured by such errors. The sources of this duty are identified, and its probable impact on malpractice litigation and criminal law is discussed. The potential consequences of enforcing this new moral duty as a minimum in law are noted. One predicted consequence is that the trend will be accelerated toward government payment of compensation for errors. The effect of truth-telling on individuals is discussed.

Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas

NASA Astrophysics Data System (ADS)

Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

2013-06-01

The giant reed (Arundo donax L.) is amongst the one hundred worst invasive alien species of the world, and it is responsible for biodiversity loss and failure of ecosystem functions in riparian habitats. In this work, field spectroradiometry was used to assess the spectral separability of the giant reed from the adjacent vegetation and from the common reed, a native similar species. The study was conducted at different phenological periods and also for the giant reed stands regenerated after mechanical cutting (giant reed_RAC). A hierarchical procedure using Kruskal-Wallis test followed by Classification and Regression Trees (CART) was used to select the minimum number of optimal bands that discriminate the giant reed from the adjacent vegetation. A new approach was used to identify sets of wavelengths - wavezones - that maximize the spectral separability beyond the minimum number of optimal bands. Jeffries Matusita and Bhattacharya distance were used to evaluate the spectral separability using the minimum optimal bands and in three simulated satellite images, namely Landsat, IKONOS and SPOT. Giant reed was spectrally separable from the adjacent vegetation, both at the vegetative and the senescent period, exception made to the common reed at the vegetative period. The red edge region was repeatedly selected, although the visible region was also important to separate the giant reed from the herbaceous vegetation and the mid infrared region to the discrimination from the woody vegetation. The highest separability was obtained for the giant reed_RAC stands, due to its highly homogeneous, dense and dark-green stands. Results are discussed by relating the phenological, morphological and structural features of the giant reed stands and the adjacent vegetation with their optical traits. Weaknesses and strengths of the giant reed spectral discrimination are highlighted and implications of imagery selection for mapping purposes are argued based on present results.

The spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β

PubMed Central

Koag, Myong-Chul; Nam, Kwangho; Lee, Seongmin

2014-01-01

To provide molecular-level insights into the spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β (polβ), we report four crystal structures of polβ complexed with dG•dTTP and dA•dCTP mismatches in the presence of Mg2+ or Mn2+. The Mg2+-bound ground-state structures show that the dA•dCTP-Mg2+ complex adopts an ‘intermediate’ protein conformation while the dG•dTTP-Mg2+ complex adopts an open protein conformation. The Mn2+-bound ‘pre-chemistry-state’ structures show that the dA•dCTP-Mn2+ complex is structurally very similar to the dA•dCTP-Mg2+ complex, whereas the dG•dTTP-Mn2+ complex undergoes a large-scale conformational change to adopt a Watson–Crick-like dG•dTTP base pair and a closed protein conformation. These structural differences, together with our molecular dynamics simulation studies, suggest that polβ increases replication fidelity via a two-stage mismatch discrimination mechanism, where one is in the ground state and the other in the closed conformation state. In the closed conformation state, polβ appears to allow only a Watson–Crick-like conformation for purine•pyrimidine base pairs, thereby discriminating the mismatched base pairs based on their ability to form the Watson–Crick-like conformation. Overall, the present studies provide new insights into the spontaneous replication error and the replication fidelity mechanisms of polβ. PMID:25200079

Verb inflection in monolingual Dutch and sequential bilingual Turkish-Dutch children with and without SLI.

PubMed

Blom, Elma; de Jong, Jan; Orgassa, Antje; Baker, Anne; Weerman, Fred

2013-01-01

Both children with specific language impairment (SLI) and children who acquire a second language (L2) make errors with verb inflection. This overlap between SLI and L2 raises the question if verb inflection can discriminate between L2 children with and without SLI. In this study we addressed this question for Dutch. The secondary goal of the study was to investigate variation in error types and error profiles across groups. Data were collected from 6-8-year-old children with SLI who acquire Dutch as their first language (L1), Dutch L1 children with a typical development (TD), Dutch L2 children with SLI, and Dutch L1 TD children who were on average 2 years younger. An experimental elicitation task was employed that tested use of verb inflection; context (3SG, 3PL) was manipulated and word order and verb type were controlled. Accuracy analyses revealed effects of impairment in both L1 and L2 children with SLI. However, individual variation indicated that there is no specific error profile for SLI. Verb inflection use as measured in our study discriminated fairly well in the L1 group but classification was less accurate in the L2 group. Between-group differences emerged furthermore for certain types of errors, but all groups also showed considerable variation in errors and there was not a specific error profile that distinguished SLI from TD. © 2013 Royal College of Speech and Language Therapists.

Discriminating the precipitation phase based on different temperature thresholds in the Songhua River Basin, China

NASA Astrophysics Data System (ADS)

Zhong, Keyuan; Zheng, Fenli; Xu, Ximeng; Qin, Chao

2018-06-01

Different precipitation phases (rain, snow or sleet) differ greatly in their hydrological and erosional processes. Therefore, accurate discrimination of the precipitation phase is highly important when researching hydrologic processes and climate change at high latitudes and mountainous regions. The objective of this study was to identify suitable temperature thresholds for discriminating the precipitation phase in the Songhua River Basin (SRB) based on 20-year daily precipitation collected from 60 meteorological stations located in and around the basin. Two methods, the air temperature method (AT method) and the wet bulb temperature method (WBT method), were used to discriminate the precipitation phase. Thirteen temperature thresholds were used to discriminate snowfall in the SRB. These thresholds included air temperatures from 0 to 5.5 °C at intervals of 0.5 °C and the wet bulb temperature (WBT). Three evaluation indices, the error percentage of discriminated snowfall days (Ep), the relative error of discriminated snowfall (Re) and the determination coefficient (R2), were applied to assess the discrimination accuracy. The results showed that 2.5 °C was the optimum threshold temperature for discriminating snowfall at the scale of the entire basin. Due to differences in the landscape conditions at the different stations, the optimum threshold varied by station. The optimal threshold ranged 1.5-4.0 °C, and 19 stations, 17 stations and 18 stations had optimal thresholds of 2.5 °C, 3.0 °C, and 3.5 °C respectively, occupying 90% of all stations. Compared with using a single suitable temperature threshold to discriminate snowfall throughout the basin, it was more accurate to use the optimum threshold at each station to estimate snowfall in the basin. In addition, snowfall was underestimated when the temperature threshold was the WBT and when the temperature threshold was below 2.5 °C, whereas snowfall was overestimated when the temperature threshold exceeded 4.0 °C at most stations. The results of this study provide information for climate change research and hydrological process simulations in the SRB, as well as provide reference information for discriminating precipitation phase in other regions.

Minimum constitutive relation error based static identification of beams using force method

NASA Astrophysics Data System (ADS)

Guo, Jia; Takewaki, Izuru

2017-05-01

A new static identification approach based on the minimum constitutive relation error (CRE) principle for beam structures is introduced. The exact stiffness and the exact bending moment are shown to make the CRE minimal for given displacements to beam damages. A two-step substitution algorithm—a force-method step for the bending moment and a constitutive-relation step for the stiffness—is developed and its convergence is rigorously derived. Identifiability is further discussed and the stiffness in the undeformed region is found to be unidentifiable. An extra set of static measurements is complemented to remedy the drawback. Convergence and robustness are finally verified through numerical examples.

A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output

PubMed Central

Stevanovic, Stefan; Pervan, Boris

2018-01-01

We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator’s estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered. PMID:29351250

VEGA: A low-power front-end ASIC for large area multi-linear X-ray silicon drift detectors: Design and experimental characterization

NASA Astrophysics Data System (ADS)

Ahangarianabhari, Mahdi; Macera, Daniele; Bertuccio, Giuseppe; Malcovati, Piero; Grassi, Marco

2015-01-01

We present the design and the first experimental characterization of VEGA, an Application Specific Integrated Circuit (ASIC) designed to read out large area monolithic linear Silicon Drift Detectors (SDD's). VEGA consists of an analog and a digital/mixed-signal section to accomplish all the functionalities and specifications required for high resolution X-ray spectroscopy in the energy range between 500 eV and 50 keV. The analog section includes a charge sensitive preamplifier, a shaper with 3-bit digitally selectable shaping times from 1.6 μs to 6.6 μs and a peak stretcher/sample-and-hold stage. The digital/mixed-signal section includes an amplitude discriminator with coarse and fine threshold level setting, a peak discriminator and a logic circuit to fulfill pile-up rejection, signal sampling, trigger generation, channel reset and the preamplifier and discriminators disabling functionalities. A Serial Peripherical Interface (SPI) is integrated in VEGA for loading and storing all configuration parameters in an internal register within few microseconds. The VEGA ASIC has been designed and manufactured in 0.35 μm CMOS mixed-signal technology in single and 32 channel versions with dimensions of 200 μm×500 μm per channel. A minimum intrinsic Equivalent Noise Charge (ENC) of 12 electrons r.m.s. at 3.6 μs peaking time and room temperature is measured and the linearity error is between -0.9% and +0.6% in the whole input energy range. The total power consumption is 481 μW and 420 μW per channel for the single and 32 channels version, respectively. A comparison with other ASICs for X-ray SDD's shows that VEGA has a suitable low noise and offers high functionality as ADC-ready signal processing but at a power consumption that is a factor of four lower than other similar existing ASICs.

Measuring Error Identification and Recovery Skills in Surgical Residents.

PubMed

Sternbach, Joel M; Wang, Kevin; El Khoury, Rym; Teitelbaum, Ezra N; Meyerson, Shari L

2017-02-01

Although error identification and recovery skills are essential for the safe practice of surgery, they have not traditionally been taught or evaluated in residency training. This study validates a method for assessing error identification and recovery skills in surgical residents using a thoracoscopic lobectomy simulator. We developed a 5-station, simulator-based examination containing the most commonly encountered cognitive and technical errors occurring during division of the superior pulmonary vein for left upper lobectomy. Successful completion of each station requires identification and correction of these errors. Examinations were video recorded and scored in a blinded fashion using an examination-specific rating instrument evaluating task performance as well as error identification and recovery skills. Evidence of validity was collected in the categories of content, response process, internal structure, and relationship to other variables. Fifteen general surgical residents (9 interns and 6 third-year residents) completed the examination. Interrater reliability was high, with an intraclass correlation coefficient of 0.78 between 4 trained raters. Station scores ranged from 64% to 84% correct. All stations adequately discriminated between high- and low-performing residents, with discrimination ranging from 0.35 to 0.65. The overall examination score was significantly higher for intermediate residents than for interns (mean, 74 versus 64 of 90 possible; p = 0.03). The described simulator-based examination with embedded errors and its accompanying assessment tool can be used to measure error identification and recovery skills in surgical residents. This examination provides a valid method for comparing teaching strategies designed to improve error recognition and recovery to enhance patient safety. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

A negentropy minimization approach to adaptive equalization for digital communication systems.

PubMed

Choi, Sooyong; Lee, Te-Won

2004-07-01

In this paper, we introduce and investigate a new adaptive equalization method based on minimizing approximate negentropy of the estimation error for a finite-length equalizer. We consider an approximate negentropy using nonpolynomial expansions of the estimation error as a new performance criterion to improve performance of a linear equalizer based on minimizing minimum mean squared error (MMSE). Negentropy includes higher order statistical information and its minimization provides improved converge, performance and accuracy compared to traditional methods such as MMSE in terms of bit error rate (BER). The proposed negentropy minimization (NEGMIN) equalizer has two kinds of solutions, the MMSE solution and the other one, depending on the ratio of the normalization parameters. The NEGMIN equalizer has best BER performance when the ratio of the normalization parameters is properly adjusted to maximize the output power(variance) of the NEGMIN equalizer. Simulation experiments show that BER performance of the NEGMIN equalizer with the other solution than the MMSE one has similar characteristics to the adaptive minimum bit error rate (AMBER) equalizer. The main advantage of the proposed equalizer is that it needs significantly fewer training symbols than the AMBER equalizer. Furthermore, the proposed equalizer is more robust to nonlinear distortions than the MMSE equalizer.

Movement trajectory smoothness is not associated with the endpoint accuracy of rapid multi-joint arm movements in young and older adults

PubMed Central

Poston, Brach; Van Gemmert, Arend W.A.; Sharma, Siddharth; Chakrabarti, Somesh; Zavaremi, Shahrzad H.; Stelmach, George

2013-01-01

The minimum variance theory proposes that motor commands are corrupted by signal-dependent noise and smooth trajectories with low noise levels are selected to minimize endpoint error and endpoint variability. The purpose of the study was to determine the contribution of trajectory smoothness to the endpoint accuracy and endpoint variability of rapid multi-joint arm movements. Young and older adults performed arm movements (4 blocks of 25 trials) as fast and as accurately as possible to a target with the right (dominant) arm. Endpoint accuracy and endpoint variability along with trajectory smoothness and error were quantified for each block of trials. Endpoint error and endpoint variance were greater in older adults compared with young adults, but decreased at a similar rate with practice for the two age groups. The greater endpoint error and endpoint variance exhibited by older adults were primarily due to impairments in movement extent control and not movement direction control. The normalized jerk was similar for the two age groups, but was not strongly associated with endpoint error or endpoint variance for either group. However, endpoint variance was strongly associated with endpoint error for both the young and older adults. Finally, trajectory error was similar for both groups and was weakly associated with endpoint error for the older adults. The findings are not consistent with the predictions of the minimum variance theory, but support and extend previous observations that movement trajectories and endpoints are planned independently. PMID:23584101

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

Cavanaugh, J.E.; McQuarrie, A.D.; Shumway, R.H.

Conventional methods for discriminating between earthquakes and explosions at regional distances have concentrated on extracting specific features such as amplitude and spectral ratios from the waveforms of the P and S phases. We consider here an optimum nonparametric classification procedure derived from the classical approach to discriminating between two Gaussian processes with unequal spectra. Two robust variations based on the minimum discrimination information statistic and Renyi's entropy are also considered. We compare the optimum classification procedure with various amplitude and spectral ratio discriminants and show that its performance is superior when applied to a small population of 8 land-based earthquakesmore » and 8 mining explosions recorded in Scandinavia. Several parametric characterizations of the notion of complexity based on modeling earthquakes and explosions as autoregressive or modulated autoregressive processes are also proposed and their performance compared with the nonparametric and feature extraction approaches.« less

Effects of monocrotophos and fenthion on discrimination acquisition and reversal in northern bobwhite (Colinus virginianus)

USGS Publications Warehouse

Robbins, C.S.

1975-01-01

Adult male northern bobwhite (Colinus virginianus) were fed diets containing organophosphorus pesticides, and the birds' discrimination acquisition and reversal performance was evaluated. The birds received the pesticide-laced diets continually, beginning 2 d before behavioral testing and ending after the birds completed the test series consisting of an acquisition and 10 reversals. Bobwhites fed a diet containing 0.18 ppm monocrotophos made 118% more errors (p 0.05) from that of controls; however, bobwhites fed the fenthion diet made 48% fewer errors (p < 0.05) in the reversals. When retested after 18 (monocrotophos) and 73 (fenthion) d on clean diets, no residual behavioral effects were detected. Brain cholinesterase activity was inhibited in all treatment groups.

Effects of monocrotophos and fenthion on discrimination acquisition and reversal in northern bobwhite (Colinus virginianus)

USGS Publications Warehouse

Kreitzer, J.F.; Fleming, W.J.

1988-01-01

Adult male northern bobwhite (Colinus virginianus) were fed diets containing organophosphorus pesticides, and the birds' discrimination acquisition and reversal performance was evaluated. The birds received the pesticide-laced diets continually, beginning 2 d before behavioral testing and ending after the birds completed the test series consisting of an acquisition and 10 reversals. Bobwhites fed a diet containing 0.18 ppm monocrotophos made 118% more errors (p 0.05) from that of controls; however, bobwhites fed the fenthion diet made 48% fewer errors (p < 0.05) in the reversals. When retested after 18 (monocrotophos) and 73 (fenthion) d on clean diets, no residual behavioral effects were detected. Brain cholinesterase activity was inhibited in all treatment groups.

An investigation of reports of Controlled Flight Toward Terrain (CFTT)

NASA Technical Reports Server (NTRS)

Porter, R. F.; Loomis, J. P.

1981-01-01

Some 258 reports from more than 23,000 documents in the files of the Aviation Safety Reporting System (ASRS) were found to be to the hazard of flight into terrain with no prior awareness by the crew of impending disaster. Examination of the reports indicate that human error was a casual factor in 64% of the incidents in which some threat of terrain conflict was experienced. Approximately two-thirds of the human errors were attributed to controllers, the most common discrepancy being a radar vector below the Minimum Vector Altitude (MVA). Errors by pilots were of a much diverse nature and include a few instances of gross deviations from their assigned altitudes. The ground proximity warning system and the minimum safe altitude warning equipment were the initial recovery factor in some 18 serious incidents and were apparently the sole warning in six reported instances which otherwise would most probably have ended in disaster.

Minimum risk wavelet shrinkage operator for Poisson image denoising.

PubMed

Cheng, Wu; Hirakawa, Keigo

2015-05-01

The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

Link prediction in the network of global virtual water trade

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2016-04-01

Through the international food-trade, water resources are 'virtually' transferred from the country of production to the country of consumption. The international food-trade, thus, implies a network of virtual water flows from exporting to importing countries (i.e., nodes). Given the dynamical behavior of the network, where food-trade relations (i.e., links) are created and dismissed every year, link prediction becomes a challenge. In this study, we propose a novel methodology for link prediction in the virtual water network. The model aims at identifying the main factors (among 17 different variables) driving the creation of a food-trade relation between any two countries, along the period between 1986 and 2011. Furthermore, the model can be exploited to investigate the network configuration in the future, under different possible (climatic and demographic) scenarios. The model grounds the existence of a link between any two nodes on the link weight (i.e., the virtual water flow): a link exists when the nodes exchange a minimum (fixed) volume of virtual water. Starting from a set of potential links between any two nodes, we fit the associated virtual water flows (both the real and the null ones) by means of multivariate linear regressions. Then, links with estimated flows higher than a minimum value (i.e., threshold) are considered active-links, while the others are non-active ones. The discrimination between active and non-active links through the threshold introduces an error (called link-prediction error) because some real links are lost (i.e., missed links) and some non-existing links (i.e., spurious links) are inevitably introduced in the network. The major drivers are those significantly minimizing the link-prediction error. Once the structure of the unweighted virtual water network is known, we apply, again, linear regressions to assess the major factors driving the fluxes traded along (modelled) active-links. Results indicate that, on the one hand, population and fertilizer use, together with link properties (such as the distance between nodes), are the major factors driving the links creation; on the other hand, population, distance, and gross domestic product are essential to model the flux entity. The results are promising since the model is able to correctly predict the 85% of the 16422 food-trade links (15% are missed), by spuriously adding to the real network only the 5% of non-existing links. The link-prediction error, evaluated as the sum of the percentage of missed and spurious links, is around 20% and it is constant over the study period. Only the 0.01% of the global virtual water flow is traded along missed links and an even lower flow is added by the spurious links (0.003%).

Computer search for binary cyclic UEP codes of odd length up to 65

NASA Technical Reports Server (NTRS)

Lin, Mao-Chao; Lin, Chi-Chang; Lin, Shu

1990-01-01

Using an exhaustive computation, the unequal error protection capabilities of all binary cyclic codes of odd length up to 65 that have minimum distances at least 3 are found. For those codes that can only have upper bounds on their unequal error protection capabilities computed, an analytic method developed by Dynkin and Togonidze (1976) is used to show that the upper bounds meet the exact unequal error protection capabilities.

Continuous slope-area discharge records in Maricopa County, Arizona, 2004–2012

USGS Publications Warehouse

Wiele, Stephen M.; Heaton, John W.; Bunch, Claire E.; Gardner, David E.; Smith, Christopher F.

2015-12-29

Analyses of sources of errors and the impact stage data errors have on calculated discharge time series are considered, along with issues in data reduction. Steeper, longer stream reaches are generally less sensitive to measurement error. Other issues considered are pressure transducer drawdown, capture of flood peaks with discrete stage data, selection of stage record for development of rating curves, and minimum stages for the calculation of discharge.

Systemic factors of errors in the case identification process of the national routine health information system: A case study of Modified Field Health Services Information System in the Philippines

PubMed Central

2011-01-01

Background The quality of data in national health information systems has been questionable in most developing countries. However, the mechanisms of errors in the case identification process are not fully understood. This study aimed to investigate the mechanisms of errors in the case identification process in the existing routine health information system (RHIS) in the Philippines by measuring the risk of committing errors for health program indicators used in the Field Health Services Information System (FHSIS 1996), and characterizing those indicators accordingly. Methods A structured questionnaire on the definitions of 12 selected indicators in the FHSIS was administered to 132 health workers in 14 selected municipalities in the province of Palawan. A proportion of correct answers (difficulty index) and a disparity of two proportions of correct answers between higher and lower scored groups (discrimination index) were calculated, and the patterns of wrong answers for each of the 12 items were abstracted from 113 valid responses. Results None of 12 items reached a difficulty index of 1.00. The average difficulty index of 12 items was 0.266 and the discrimination index that showed a significant difference was 0.216 and above. Compared with these two cut-offs, six items showed non-discrimination against lower difficulty indices of 0.035 (4/113) to 0.195 (22/113), two items showed a positive discrimination against lower difficulty indices of 0.142 (16/113) and 0.248 (28/113), and four items showed a positive discrimination against higher difficulty indices of 0.469 (53/113) to 0.673 (76/113). Conclusions The results suggest three characteristics of definitions of indicators such as those that are (1) unsupported by the current conditions in the health system, i.e., (a) data are required from a facility that cannot directly generate the data and, (b) definitions of indicators are not consistent with its corresponding program; (2) incomplete or ambiguous, which allow several interpretations; and (3) complete yet easily misunderstood by health workers. Taking systemic factors into account, the case identification step needs to be reviewed and designed to generate intended data in health information systems. PMID:21995369

Color discrimination errors associate with axial motor impairments in Parkinson's disease.

PubMed

Bohnen, Nicolaas I; Haugen, Jacob; Ridder, Andrew; Kotagal, Vikas; Albin, Roger L; Frey, Kirk A; Müller, Martijn L T M

2017-01-01

Visual function deficits are more common in imbalance-predominant compared to tremor-predominant PD suggesting a pathophysiological role of impaired visual functions in axial motor impairments. To investigate the relationship between changes in color discrimination and motor impairments in PD while accounting for cognitive or other confounder factors. PD subjects (n=49, age 66.7±8.3 years; Hoehn & Yahr stage 2.6±0.6) completed color discrimination assessment using the Farnsworth-Munsell 100 Hue Color Vision Test, neuropsychological, motor assessments and [ 11 C]dihydrotetrabenazine vesicular monoamine transporter type 2 PET imaging. MDS-UPDRS sub-scores for cardinal motor features were computed. Timed up and go mobility and walking tests were assessed in 48 subjects. Bivariate correlation coefficients between color discrimination and motor variables were significant only for the Timed up and go (R S =0.44, P=0.0018) and the MDS-UPDRS axial motor scores (R S =0.38, P=0.0068). Multiple regression confounder analysis using the Timed up and go as outcome parameter showed a significant total model (F (5,43) = 7.3, P<0.0001) with significant regressor effects for color discrimination (standardized β=0.32, t=2.6, P=0.012), global cognitive Z-score (β=-0.33, t=-2.5, P=0.018), duration of disease (β=0.26, t=1.8, P=0.038), but not for age or striatal dopaminergic binding. The color discrimination test was also a significant independent regressor in the MDS-UPDRS axial motor model (standardized β=0.29, t=2.4, P=0.022; total model t (5,43) = 6.4, P=0.0002). Color discrimination errors associate with axial motor features in PD independent of cognitive deficits, nigrostriatal dopaminergic denervation, and other confounder variables. These findings may reflect shared pathophysiology between color discrimination visual impairments and axial motor burden in PD.

Monte Carlo simulation of errors in the anisotropy of magnetic susceptibility - A second-rank symmetric tensor. [for grains in sedimentary and volcanic rocks

NASA Technical Reports Server (NTRS)

Lienert, Barry R.

1991-01-01

Monte Carlo perturbations of synthetic tensors to evaluate the Hext/Jelinek elliptical confidence regions for anisotropy of magnetic susceptibility (AMS) eigenvectors are used. When the perturbations are 33 percent of the minimum anisotropy, both the shapes and probability densities of the resulting eigenvector distributions agree with the elliptical distributions predicted by the Hext/Jelinek equations. When the perturbation size is increased to 100 percent of the minimum eigenvalue difference, the major axis of the 95 percent confidence ellipse underestimates the observed eigenvector dispersion by about 10 deg. The observed distributions of the principal susceptibilities (eigenvalues) are close to being normal, with standard errors that agree well with the calculated Hext/Jelinek errors. The Hext/Jelinek ellipses are also able to describe the AMS dispersions due to instrumental noise and provide reasonable limits for the AMS dispersions observed in two Hawaiian basaltic dikes. It is concluded that the Hext/Jelinek method provides a satisfactory description of the errors in AMS data and should be a standard part of any AMS data analysis.

Aging and curvature discrimination from static and dynamic touch.

PubMed

Norman, J Farley; Kappers, Astrid M L; Cheeseman, Jacob R; Ronning, Cecilia; Thomason, Kelsey E; Baxter, Michael W; Calloway, Autum B; Lamirande, Davora N

2013-01-01

Two experiments evaluated the ability of 30 older and younger adults to discriminate the curvature of simple object surfaces from static and dynamic touch. The ages of the older adults ranged from 66 to 85 years, while those of the younger adults ranged from 20 to 29 years. For each participant in both experiments, the minimum curvature magnitude needed to reliably discriminate between convex and concave surfaces was determined. In Experiment 1, participants used static touch to make their judgments of curvature, while dynamic touch was used in Experiment 2. When static touch was used to discriminate curvature, a large effect of age occurred (the thresholds were 0.67 & 1.11/m for the younger and older participants, respectively). However, when participants used dynamic touch, there was no significant difference between the ability of younger and older participants to discriminate curvature (the thresholds were 0.58 & 0.59/m for the younger and older participants, respectively). The results of the current study demonstrate that while older adults can accurately discriminate surface curvature from dynamic touch, they possess significant impairments for static touch.

Aging and Curvature Discrimination from Static and Dynamic Touch

PubMed Central

Norman, J. Farley; Kappers, Astrid M. L.; Cheeseman, Jacob R.; Ronning, Cecilia; Thomason, Kelsey E.; Baxter, Michael W.; Calloway, Autum B.; Lamirande, Davora N.

2013-01-01

Two experiments evaluated the ability of 30 older and younger adults to discriminate the curvature of simple object surfaces from static and dynamic touch. The ages of the older adults ranged from 66 to 85 years, while those of the younger adults ranged from 20 to 29 years. For each participant in both experiments, the minimum curvature magnitude needed to reliably discriminate between convex and concave surfaces was determined. In Experiment 1, participants used static touch to make their judgments of curvature, while dynamic touch was used in Experiment 2. When static touch was used to discriminate curvature, a large effect of age occurred (the thresholds were 0.67 & 1.11/m for the younger and older participants, respectively). However, when participants used dynamic touch, there was no significant difference between the ability of younger and older participants to discriminate curvature (the thresholds were 0.58 & 0.59/m for the younger and older participants, respectively). The results of the current study demonstrate that while older adults can accurately discriminate surface curvature from dynamic touch, they possess significant impairments for static touch. PMID:23844224

Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

Northeast Artificial Intelligence Consortium Annual Report. Volume 7. 1988 Research in Automated Photointerpretation

DTIC Science & Technology

1989-10-01

weight based on how powerful the corresponding feature is for object recognition and discrimination. For example, consider an arbitrary weight, denoted...quality of the segmentation, how powerful the features and spatial constraints in the knowledge base are (as far as object recognition is concern...that are powerful for object recognition and discrimination. At this point, this selection is performed heuristically through trial-and-error. As a

Automated palpation for breast tissue discrimination based on viscoelastic biomechanical properties.

PubMed

Tsukune, Mariko; Kobayashi, Yo; Miyashita, Tomoyuki; Fujie, G Masakatsu

2015-05-01

Accurate, noninvasive methods are sought for breast tumor detection and diagnosis. In particular, a need for noninvasive techniques that measure both the nonlinear elastic and viscoelastic properties of breast tissue has been identified. For diagnostic purposes, it is important to select a nonlinear viscoelastic model with a small number of parameters that highly correlate with histological structure. However, the combination of conventional viscoelastic models with nonlinear elastic models requires a large number of parameters. A nonlinear viscoelastic model of breast tissue based on a simple equation with few parameters was developed and tested. The nonlinear viscoelastic properties of soft tissues in porcine breast were measured experimentally using fresh ex vivo samples. Robotic palpation was used for measurements employed in a finite element model. These measurements were used to calculate nonlinear viscoelastic parameters for fat, fibroglandular breast parenchyma and muscle. The ability of these parameters to distinguish the tissue types was evaluated in a two-step statistical analysis that included Holm's pairwise [Formula: see text] test. The discrimination error rate of a set of parameters was evaluated by the Mahalanobis distance. Ex vivo testing in porcine breast revealed significant differences in the nonlinear viscoelastic parameters among combinations of three tissue types. The discrimination error rate was low among all tested combinations of three tissue types. Although tissue discrimination was not achieved using only a single nonlinear viscoelastic parameter, a set of four nonlinear viscoelastic parameters were able to reliably and accurately discriminate fat, breast fibroglandular tissue and muscle.

Ligand Shaping in Induced Fit Docking of MraY Inhibitors. Polynomial Discriminant and Laplacian Operator as Biological Activity Descriptors.

PubMed

Lungu, Claudiu N; Diudea, Mircea V; Putz, Mihai V

2017-06-27

Docking-i.e., interaction of a small molecule (ligand) with a proteic structure (receptor)-represents the ground of drug action mechanism of the vast majority of bioactive chemicals. Ligand and receptor accommodate their geometry and energy, within this interaction, in the benefit of receptor-ligand complex. In an induced fit docking, the structure of ligand is most susceptible to changes in topology and energy, comparative to the receptor. These changes can be described by manifold hypersurfaces, in terms of polynomial discriminant and Laplacian operator. Such topological surfaces were represented for each MraY (phospho-MurNAc-pentapeptide translocase) inhibitor, studied before and after docking with MraY. Binding affinities of all ligands were calculated by this procedure. For each ligand, Laplacian and polynomial discriminant were correlated with the ligand minimum inhibitory concentration (MIC) retrieved from literature. It was observed that MIC is correlated with Laplacian and polynomial discriminant.

Appliance Efficiency Standards and Price Discrimination

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

Spurlock, Cecily Anna

2013-05-08

I explore the effects of two simultaneous changes in minimum energy efficiency and ENERGY STAR standards for clothes washers. Adapting the Mussa and Rosen (1978) and Ronnen (1991) second-degree price discrimination model, I demonstrate that clothes washer prices and menus adjusted to the new standards in patterns consistent with a market in which firms had been price discriminating. In particular, I show evidence of discontinuous price drops at the time the standards were imposed, driven largely by mid-low efficiency segments of the market. The price discrimination model predicts this result. On the other hand, in a perfectly competition market, pricesmore » should increase for these market segments. Additionally, new models proliferated in the highest efficiency market segment following the standard changes. Finally, I show that firms appeared to use different adaptation strategies at the two instances of the standards changing.« less

Ethnicity- and sex-based discrimination and the maintenance of self-esteem.

PubMed

Lönnqvist, Jan-Erik; Hennig-Schmidt, Heike; Walkowitz, Gari

2015-01-01

The psychological underpinnings of labor market discrimination were investigated by having participants from Israel, the West Bank and Germany (N = 205) act as employers in a stylized employment task in which they ranked, set wages, and imposed a minimum effort level on applicants. State self-esteem was measured before and after the employment task, in which applicant ethnicity and sex were salient. The applicants were real people and all behavior was monetarily incentivized. Supporting the full self-esteem hypothesis of the social identity approach, low self-esteem in women was associated with assigning higher wages to women than to men, and such behavior was related to the maintenance of self-esteem. The narrower hypothesis that successful intergroup discrimination serves to protect self-esteem received broader support. Across all participants, both ethnicity- and sex-based discrimination of out-groups were associated with the maintenance of self-esteem, with the former showing a stronger association than the latter.

Optimum measurement for unambiguously discriminating two mixed states: General considerations and special cases

NASA Astrophysics Data System (ADS)

Herzog, Ulrike; Bergou, János A.

2006-04-01

Based on our previous publication [U. Herzog and J. A. Bergou, Phys. Rev. A 71, 050301(R)(2005)] we investigate the optimum measurement for the unambiguous discrimination of two mixed quantum states that occur with given prior probabilities. Unambiguous discrimination of nonorthogonal states is possible in a probabilistic way, at the expense of a nonzero probability of inconclusive results, where the measurement fails. Along with a discussion of the general problem, we give an example illustrating our method of solution. We also provide general inequalities for the minimum achievable failure probability and discuss in more detail the necessary conditions that must be fulfilled when its absolute lower bound, proportional to the fidelity of the states, can be reached.

Asymptotic state discrimination and a strict hierarchy in distinguishability norms

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

Chitambar, Eric; Hsieh, Min-Hsiu

2014-11-15

In this paper, we consider the problem of discriminating quantum states by local operations and classical communication (LOCC) when an arbitrarily small amount of error is permitted. This paradigm is known as asymptotic state discrimination, and we derive necessary conditions for when two multipartite states of any size can be discriminated perfectly by asymptotic LOCC. We use this new criterion to prove a gap in the LOCC and separable distinguishability norms. We then turn to the operational advantage of using two-way classical communication over one-way communication in LOCC processing. With a simple two-qubit product state ensemble, we demonstrate a strictmore » majorization of the two-way LOCC norm over the one-way norm.« less

Short version of the Depression Anxiety Stress Scale-21: is it valid for Brazilian adolescents?

PubMed Central

da Silva, Hítalo Andrade; dos Passos, Muana Hiandra Pereira; de Oliveira, Valéria Mayaly Alves; Palmeira, Aline Cabral; Pitangui, Ana Carolina Rodarti; de Araújo, Rodrigo Cappato

2016-01-01

ABSTRACT Objective To evaluate the interday reproducibility, agreement and validity of the construct of short version of the Depression Anxiety Stress Scale-21 applied to adolescents. Methods The sample consisted of adolescents of both sexes, aged between 10 and 19 years, who were recruited from schools and sports centers. The validity of the construct was performed by exploratory factor analysis, and reliability was calculated for each construct using the intraclass correlation coefficient, standard error of measurement and the minimum detectable change. Results The factor analysis combining the items corresponding to anxiety and stress in a single factor, and depression in a second factor, showed a better match of all 21 items, with higher factor loadings in their respective constructs. The reproducibility values for depression were intraclass correlation coefficient with 0.86, standard error of measurement with 0.80, and minimum detectable change with 2.22; and, for anxiety/stress: intraclass correlation coefficient with 0.82, standard error of measurement with 1.80, and minimum detectable change with 4.99. Conclusion The short version of the Depression Anxiety Stress Scale-21 showed excellent values of reliability, and strong internal consistency. The two-factor model with condensation of the constructs anxiety and stress in a single factor was the most acceptable for the adolescent population. PMID:28076595

An intersecting chord method for minimum circumscribed sphere and maximum inscribed sphere evaluations of sphericity error

NASA Astrophysics Data System (ADS)

Liu, Fei; Xu, Guanghua; Zhang, Qing; Liang, Lin; Liu, Dan

2015-11-01

As one of the Geometrical Product Specifications that are widely applied in industrial manufacturing and measurement, sphericity error can synthetically scale a 3D structure and reflects the machining quality of a spherical workpiece. Following increasing demands in the high motion performance of spherical parts, sphericity error is becoming an indispensable component in the evaluation of form error. However, the evaluation of sphericity error is still considered to be a complex mathematical issue, and the related research studies on the development of available models are lacking. In this paper, an intersecting chord method is first proposed to solve the minimum circumscribed sphere and maximum inscribed sphere evaluations of sphericity error. This new modelling method leverages chord relationships to replace the characteristic points, thereby significantly reducing the computational complexity and improving the computational efficiency. Using the intersecting chords to generate a virtual centre, the reference sphere in two concentric spheres is simplified as a space intersecting structure. The position of the virtual centre on the space intersecting structure is determined by characteristic chords, which may reduce the deviation between the virtual centre and the centre of the reference sphere. In addition,two experiments are used to verify the effectiveness of the proposed method with real datasets from the Cartesian coordinates. The results indicate that the estimated errors are in perfect agreement with those of the published methods. Meanwhile, the computational efficiency is improved. For the evaluation of the sphericity error, the use of high performance computing is a remarkable change.

Brief Report: Investigating Uncertainty in the Minimum Mortality Temperature: Methods and Application to 52 Spanish Cities.

PubMed

Tobías, Aurelio; Armstrong, Ben; Gasparrini, Antonio

2017-01-01

The minimum mortality temperature from J- or U-shaped curves varies across cities with different climates. This variation conveys information on adaptation, but ability to characterize is limited by the absence of a method to describe uncertainty in estimated minimum mortality temperatures. We propose an approximate parametric bootstrap estimator of confidence interval (CI) and standard error (SE) for the minimum mortality temperature from a temperature-mortality shape estimated by splines. The coverage of the estimated CIs was close to nominal value (95%) in the datasets simulated, although SEs were slightly high. Applying the method to 52 Spanish provincial capital cities showed larger minimum mortality temperatures in hotter cities, rising almost exactly at the same rate as annual mean temperature. The method proposed for computing CIs and SEs for minimums from spline curves allows comparing minimum mortality temperatures in different cities and investigating their associations with climate properly, allowing for estimation uncertainty.

Protograph based LDPC codes with minimum distance linearly growing with block size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy

2005-01-01

We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.

Hand-movement-based in-vehicle driver/front-seat passenger discrimination for centre console controls

NASA Astrophysics Data System (ADS)

Herrmann, Enrico; Makrushin, Andrey; Dittmann, Jana; Vielhauer, Claus; Langnickel, Mirko; Kraetzer, Christian

2010-01-01

Successful user discrimination in a vehicle environment may yield a reduction of the number of switches, thus significantly reducing costs while increasing user convenience. The personalization of individual controls permits conditional passenger enable/driver disable and vice versa options which may yield safety improvement. The authors propose a prototypic optical sensing system based on hand movement segmentation in near-infrared image sequences implemented in an Audi A6 Avant. Analyzing the number of movements in special regions, the system recognizes the direction of the forearm and hand motion and decides whether driver or front-seat passenger touch a control. The experimental evaluation is performed independently for uniformly and non-uniformly illuminated video data as well as for the complete video data set which includes both subsets. The general test results in error rates of up to 14.41% FPR / 16.82% FNR and 17.61% FPR / 14.77% FNR for driver and passenger respectively. Finally, the authors discuss the causes of the most frequently occurring errors as well as the prospects and limitations of optical sensing for user discrimination in passenger compartments.

Type I Error Inflation in DIF Identification with Mantel-Haenszel: An Explanation and a Solution

ERIC Educational Resources Information Center

Magis, David; De Boeck, Paul

2014-01-01

It is known that sum score-based methods for the identification of differential item functioning (DIF), such as the Mantel-Haenszel (MH) approach, can be affected by Type I error inflation in the absence of any DIF effect. This may happen when the items differ in discrimination and when there is item impact. On the other hand, outlier DIF methods…

Effects of Test Level Discrimination and Difficulty on Answer-Copying Indices

ERIC Educational Resources Information Center

Sunbul, Onder; Yormaz, Seha

2018-01-01

In this study Type I Error and the power rates of omega (?) and GBT (generalized binomial test) indices were investigated for several nominal alpha levels and for 40 and 80-item test lengths with 10,000-examinee sample size under several test level restrictions. As a result, Type I error rates of both indices were found to be below the acceptable…

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

PubMed

Jarvis, Stuart; Kovacs, Caroline; Briggs, Jim; Meredith, Paul; Schmidt, Paul E; Featherstone, Peter I; Prytherch, David R; Smith, Gary B

2015-08-01

Although the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. We truncated 36 published 'standard' EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve--AUROC) of each standard EWS and its truncated 'binary' equivalent. The binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. The performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Discrimination of short-duration (two-pulse) flashes as a function of signal luminance and method of measurement.

DOT National Transportation Integrated Search

1971-11-01

The recent introduction of strobe lights for anticollision purposes raises the possibility of using temporal patterns of short duration flashes as information carrying signals. The current experiments are concerned with the detection of the minimum d...

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

[Discrimination of types of polyacrylamide based on near infrared spectroscopy coupled with least square support vector machine].

PubMed

Zhang, Hong-Guang; Yang, Qin-Min; Lu, Jian-Gang

2014-04-01

In this paper, a novel discriminant methodology based on near infrared spectroscopic analysis technique and least square support vector machine was proposed for rapid and nondestructive discrimination of different types of Polyacrylamide. The diffuse reflectance spectra of samples of Non-ionic Polyacrylamide, Anionic Polyacrylamide and Cationic Polyacrylamide were measured. Then principal component analysis method was applied to reduce the dimension of the spectral data and extract of the principal compnents. The first three principal components were used for cluster analysis of the three different types of Polyacrylamide. Then those principal components were also used as inputs of least square support vector machine model. The optimization of the parameters and the number of principal components used as inputs of least square support vector machine model was performed through cross validation based on grid search. 60 samples of each type of Polyacrylamide were collected. Thus a total of 180 samples were obtained. 135 samples, 45 samples for each type of Polyacrylamide, were randomly split into a training set to build calibration model and the rest 45 samples were used as test set to evaluate the performance of the developed model. In addition, 5 Cationic Polyacrylamide samples and 5 Anionic Polyacrylamide samples adulterated with different proportion of Non-ionic Polyacrylamide were also prepared to show the feasibilty of the proposed method to discriminate the adulterated Polyacrylamide samples. The prediction error threshold for each type of Polyacrylamide was determined by F statistical significance test method based on the prediction error of the training set of corresponding type of Polyacrylamide in cross validation. The discrimination accuracy of the built model was 100% for prediction of the test set. The prediction of the model for the 10 mixing samples was also presented, and all mixing samples were accurately discriminated as adulterated samples. The overall results demonstrate that the discrimination method proposed in the present paper can rapidly and nondestructively discriminate the different types of Polyacrylamide and the adulterated Polyacrylamide samples, and offered a new approach to discriminate the types of Polyacrylamide.

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

PubMed Central

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km2. The lake area decreased by -9.3% at an annual rate of -53.7 km2 yr-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability. PMID:27007233

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI.

PubMed

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km(2). The lake area decreased by -9.3% at an annual rate of -53.7 km(2) yr(-1) during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.

A Matched Project Evaluation of Modern Programming Practices. Volume II. Scientific Report on the ASTROS Plan.

DTIC Science & Technology

1980-02-01

formula for predictinq the number of errors during system testing. The equation he presents is B V/ ECRIT where B is the number of 19 ’R , errors...expected, V is the volume, and ECRIT is "the mean number of elementary discriminations between potential errors in programming" (p. 85). E CRIT can also...prediction of delivered bugs is: "V VX 2 B = V/ ECRIT -3- 13,824 2.3 McCabe’s Complexity Metric Thomas McCabe (1976) defined complexity in relation to

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Security of two-state and four-state practical quantum bit-commitment protocols

NASA Astrophysics Data System (ADS)

Loura, Ricardo; Arsenović, Dušan; Paunković, Nikola; Popović, Duška B.; Prvanović, Slobodan

2016-12-01

We study cheating strategies against a practical four-state quantum bit-commitment protocol [A. Danan and L. Vaidman, Quant. Info. Proc. 11, 769 (2012)], 10.1007/s11128-011-0284-4 and its two-state variant [R. Loura et al., Phys. Rev. A 89, 052336 (2014)], 10.1103/PhysRevA.89.052336 when the underlying quantum channels are noisy and the cheating party is constrained to using single-qubit measurements only. We show that simply inferring the transmitted photons' states by using the Breidbart basis, optimal for ambiguous (minimum-error) state discrimination, does not directly produce an optimal cheating strategy for this bit-commitment protocol. We introduce a strategy, based on certain postmeasurement processes and show it to have better chances at cheating than the direct approach. We also study to what extent sending forged geographical coordinates helps a dishonest party in breaking the binding security requirement. Finally, we investigate the impact of imperfect single-photon sources in the protocols. Our study shows that, in terms of the resources used, the four-state protocol is advantageous over the two-state version. The analysis performed can be straightforwardly generalized to any finite-qubit measurement, with the same qualitative results.

Influence of Time-Pickoff Circuit Parameters on LiDAR Range Precision

PubMed Central

Wang, Hongming; Yang, Bingwei; Huyan, Jiayue; Xu, Lijun

2017-01-01

A pulsed time-of-flight (TOF) measurement-based Light Detection and Ranging (LiDAR) system is more effective for medium-long range distances. As a key ranging unit, a time-pickoff circuit based on automatic gain control (AGC) and constant fraction discriminator (CFD) is designed to reduce the walk error and the timing jitter for obtaining the accurate time interval. Compared with Cramer–Rao lower bound (CRLB) and the estimation of the timing jitter, four parameters-based Monte Carlo simulations are established to show how the range precision is influenced by the parameters, including pulse amplitude, pulse width, attenuation fraction and delay time of the CFD. Experiments were carried out to verify the relationship between the range precision and three of the parameters, exclusing pulse width. It can be concluded that two parameters of the ranging circuit (attenuation fraction and delay time) were selected according to the ranging performance of the minimum pulse amplitude. The attenuation fraction should be selected in the range from 0.2 to 0.6 to achieve high range precision. The selection criterion of the time-pickoff circuit parameters is helpful for the ranging circuit design of TOF LiDAR system. PMID:29039772

RFI in hybrid loops - Simulation and experimental results.

NASA Technical Reports Server (NTRS)

Ziemer, R. E.; Nelson, D. R.; Raghavan, H. R.

1972-01-01

A digital simulation of an imperfect second-order hybrid phase-locked loop (HPLL) operating in radio frequency interference (RFI) is described. Its performance is characterized in terms of phase error variance and phase error probability density function (PDF). Monte-Carlo simulation is used to show that the HPLL can be superior to the conventional phase-locked loops in RFI backgrounds when minimum phase error variance is the goodness criterion. Similar experimentally obtained data are given in support of the simulation data.

Colour discrimination, colour naming and colour preferences among individuals with Alzheimer's disease.

PubMed

Wijk, H; Berg, S; Sivik, L; Steen, B

1999-12-01

To study the ability of colour naming, colour discrimination and colour preference in Alzheimer's disease (AD). Descriptive, consecutive sample. Fifty subjects >65 years with AD. Testing colour discrimination, colour naming and colour preferences. Ability to detect colour differences in the yellow, red, blue and green areas, ability to assign a name to 22 colour samples, ability to rank seven colours in order of preference. Discrimination ability was significantly better in the yellow and red area and for lightness variations. Cognitive decline had a significant impact on naming mixed colours and using elaborate colour names. Severity of dementia did not affect the preference rank order of colours. Ability to discriminate is affected in AD, with most errors in the blue and green area. Naming colours shows a cognitive decline. Preferences for colour are stable despite the disease. Copyright 1999 John Wiley & Sons, Ltd.

The effect of appropriate and inappropriate stimulus color on odor discrimination.

PubMed

Stevenson, Richard J; Oaten, Megan

2008-05-01

Color can strongly affect participants' self-report of an odor's qualities. In Experiment 1, we examined whether color influences a more objective measure of odor quality, discrimination. Odor pairs, presented in their appropriate color (e.g., strawberry and cherry in red water), an inappropriate color (e.g., strawberry and cherry in green water), or uncolored water were presented for discrimination. Participants made significantly more errors when odors were discriminated in an inappropriate color. In Experiment 2, the same design was utilized, but with an articulatory suppression task (AST), to examine whether the effect of color was mediated by identification or by a more direct effect on the percept. Here, the AST significantly improved discrimination for the inappropriate color condition, relative to Experiment 1. Although color does affect a more objective measure of odor quality, this is mediated by conceptual, rather than perceptual, means.

12 CFR 1207.2 - Policy, purpose, and scope.

Code of Federal Regulations, 2014 CFR

2014-01-01

... INCLUSION General § 1207.2 Policy, purpose, and scope. (a) General policy. FHFA's policy is to promote non-discrimination, diversity and, at a minimum, the inclusion of women, minorities, and individuals with... balance with financially safe and sound business practices, the inclusion and utilization of minorities...

12 CFR 1207.2 - Policy, purpose, and scope.

Code of Federal Regulations, 2013 CFR

2013-01-01

... INCLUSION General § 1207.2 Policy, purpose, and scope. (a) General policy. FHFA's policy is to promote non-discrimination, diversity and, at a minimum, the inclusion of women, minorities, and individuals with... balance with financially safe and sound business practices, the inclusion and utilization of minorities...

12 CFR 1207.2 - Policy, purpose, and scope.

Code of Federal Regulations, 2012 CFR

2012-01-01

... INCLUSION General § 1207.2 Policy, purpose, and scope. (a) General policy. FHFA's policy is to promote non-discrimination, diversity and, at a minimum, the inclusion of women, minorities, and individuals with... balance with financially safe and sound business practices, the inclusion and utilization of minorities...

Development and Implementation of Minimum Hiring Specifications

ERIC Educational Resources Information Center

Herbstritt, Michael R.

1978-01-01

Specifications were developed to avoid possible discrimination and confusion in the hiring practices at a large southeastern university. They were developed through job analysis and a systematic file search designed to find the education and prior related work experience possessed by each incumbent. The specifications were validated as…

Pseudo-Equivalent Groups and Linking

ERIC Educational Resources Information Center

Haberman, Shelby J.

2015-01-01

Adjustment by minimum discriminant information provides an approach to linking test forms in the case of a nonequivalent groups design with no satisfactory common items. This approach employs background information on individual examinees in each administration so that weighted samples of examinees form pseudo-equivalent groups in the sense that…

Discriminating quantum-optical beam-splitter channels with number-diagonal signal states: Applications to quantum reading and target detection

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

Nair, Ranjith

2011-09-15

We consider the problem of distinguishing, with minimum probability of error, two optical beam-splitter channels with unequal complex-valued reflectivities using general quantum probe states entangled over M signal and M' idler mode pairs of which the signal modes are bounced off the beam splitter while the idler modes are retained losslessly. We obtain a lower bound on the output state fidelity valid for any pure input state. We define number-diagonal signal (NDS) states to be input states whose density operator in the signal modes is diagonal in the multimode number basis. For such input states, we derive series formulas formore » the optimal error probability, the output state fidelity, and the Chernoff-type upper bounds on the error probability. For the special cases of quantum reading of a classical digital memory and target detection (for which the reflectivities are real valued), we show that for a given input signal photon probability distribution, the fidelity is minimized by the NDS states with that distribution and that for a given average total signal energy N{sub s}, the fidelity is minimized by any multimode Fock state with N{sub s} total signal photons. For reading of an ideal memory, it is shown that Fock state inputs minimize the Chernoff bound. For target detection under high-loss conditions, a no-go result showing the lack of appreciable quantum advantage over coherent state transmitters is derived. A comparison of the error probability performance for quantum reading of number state and two-mode squeezed vacuum state (or EPR state) transmitters relative to coherent state transmitters is presented for various values of the reflectances. While the nonclassical states in general perform better than the coherent state, the quantitative performance gains differ depending on the values of the reflectances. The experimental outlook for realizing nonclassical gains from number state transmitters with current technology at moderate to high values of the reflectances is argued to be good.« less

Probablilistic evaluation of earthquake detection and location capability for Illinois, Indiana, Kentucky, Ohio, and West Virginia

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

Mauk, F.J.; Christensen, D.H.

1980-09-01

Probabilistic estimations of earthquake detection and location capabilities for the states of Illinois, Indiana, Kentucky, Ohio and West Virginia are presented in this document. The algorithm used in these epicentrality and minimum-magnitude estimations is a version of the program NETWORTH by Wirth, Blandford, and Husted (DARPA Order No. 2551, 1978) which was modified for local array evaluation at the University of Michigan Seismological Observatory. Estimations of earthquake detection capability for the years 1970 and 1980 are presented in four regional minimum m/sub b/ magnitude contour maps. Regional 90% confidence error ellipsoids are included for m/sub b/ magnitude events from 2.0more » through 5.0 at 0.5 m/sub b/ unit increments. The close agreement between these predicted epicentral 90% confidence estimates and the calculated error ellipses associated with actual earthquakes within the studied region suggest that these error determinations can be used to estimate the reliability of epicenter location. 8 refs., 14 figs., 2 tabs.« less

Acceptance threshold theory can explain occurrence of homosexual behaviour.

PubMed

Engel, Katharina C; Männer, Lisa; Ayasse, Manfred; Steiger, Sandra

2015-01-01

Same-sex sexual behaviour (SSB) has been documented in a wide range of animals, but its evolutionary causes are not well understood. Here, we investigated SSB in the light of Reeve's acceptance threshold theory. When recognition is not error-proof, the acceptance threshold used by males to recognize potential mating partners should be flexibly adjusted to maximize the fitness pay-off between the costs of erroneously accepting males and the benefits of accepting females. By manipulating male burying beetles' search time for females and their reproductive potential, we influenced their perceived costs of making an acceptance or rejection error. As predicted, when the costs of rejecting females increased, males exhibited more permissive discrimination decisions and showed high levels of SSB; when the costs of accepting males increased, males were more restrictive and showed low levels of SSB. Our results support the idea that in animal species, in which the recognition cues of females and males overlap to a certain degree, SSB is a consequence of an adaptive discrimination strategy to avoid the costs of making rejection errors. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U.

PubMed

Ishii, K; Shinohara, K; Ishikawa, M; Baba, M; Isobe, M; Okamoto, A; Kitajima, S; Sasao, M

2010-10-01

A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-γ pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and γ-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the γ-ray contamination in most of the beam heating phase was negligible compared with the statistical error with 10 ms time resolution.

Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U

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

Ishii, K.; Okamoto, A.; Kitajima, S.

2010-10-15

A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-{gamma} pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and {gamma}-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the {gamma}-ray contamination in most of themore » beam heating phase was negligible compared with the statistical error with 10 ms time resolution.« less

Videopanorama Frame Rate Requirements Derived from Visual Discrimination of Deceleration During Simulated Aircraft Landing

NASA Technical Reports Server (NTRS)

Furnstenau, Norbert; Ellis, Stephen R.

2015-01-01

In order to determine the required visual frame rate (FR) for minimizing prediction errors with out-the-window video displays at remote/virtual airport towers, thirteen active air traffic controllers viewed high dynamic fidelity simulations of landing aircraft and decided whether aircraft would stop as if to be able to make a turnoff or whether a runway excursion would be expected. The viewing conditions and simulation dynamics replicated visual rates and environments of transport aircraft landing at small commercial airports. The required frame rate was estimated using Bayes inference on prediction errors by linear FRextrapolation of event probabilities conditional on predictions (stop, no-stop). Furthermore estimates were obtained from exponential model fits to the parametric and non-parametric perceptual discriminabilities d' and A (average area under ROC-curves) as dependent on FR. Decision errors are biased towards preference of overshoot and appear due to illusionary increase in speed at low frames rates. Both Bayes and A - extrapolations yield a framerate requirement of 35 < FRmin < 40 Hz. When comparing with published results [12] on shooter game scores the model based d'(FR)-extrapolation exhibits the best agreement and indicates even higher FRmin > 40 Hz for minimizing decision errors. Definitive recommendations require further experiments with FR > 30 Hz.

A validation procedure for a LADAR system radiometric simulation model

NASA Astrophysics Data System (ADS)

Leishman, Brad; Budge, Scott; Pack, Robert

2007-04-01

The USU LadarSIM software package is a ladar system engineering tool that has recently been enhanced to include the modeling of the radiometry of Ladar beam footprints. This paper will discuss our validation of the radiometric model and present a practical approach to future validation work. In order to validate complicated and interrelated factors affecting radiometry, a systematic approach had to be developed. Data for known parameters were first gathered then unknown parameters of the system were determined from simulation test scenarios. This was done in a way to isolate as many unknown variables as possible, then build on the previously obtained results. First, the appropriate voltage threshold levels of the discrimination electronics were set by analyzing the number of false alarms seen in actual data sets. With this threshold set, the system noise was then adjusted to achieve the appropriate number of dropouts. Once a suitable noise level was found, the range errors of the simulated and actual data sets were compared and studied. Predicted errors in range measurements were analyzed using two methods: first by examining the range error of a surface with known reflectivity and second by examining the range errors for specific detectors with known responsivities. This provided insight into the discrimination method and receiver electronics used in the actual system.

In Search of Grid Converged Solutions

NASA Technical Reports Server (NTRS)

Lockard, David P.

2010-01-01

Assessing solution error continues to be a formidable task when numerically solving practical flow problems. Currently, grid refinement is the primary method used for error assessment. The minimum grid spacing requirements to achieve design order accuracy for a structured-grid scheme are determined for several simple examples using truncation error evaluations on a sequence of meshes. For certain methods and classes of problems, obtaining design order may not be sufficient to guarantee low error. Furthermore, some schemes can require much finer meshes to obtain design order than would be needed to reduce the error to acceptable levels. Results are then presented from realistic problems that further demonstrate the challenges associated with using grid refinement studies to assess solution accuracy.

Floating-point system quantization errors in digital control systems

NASA Technical Reports Server (NTRS)

Phillips, C. L.

1973-01-01

The results are reported of research into the effects on system operation of signal quantization in a digital control system. The investigation considered digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. An error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. As an output the program gives the programing form required for minimum system quantization errors (either maximum of rms errors), and the maximum and rms errors that appear in the system output for a given bit configuration. The program can be integrated into existing digital simulations of a system.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Interaction-free measurement as quantum channel discrimination

NASA Astrophysics Data System (ADS)

Zhou, You; Yung, Man-Hong

2017-12-01

Interaction-free measurement is a quantum process where, in the ideal situation, an object can be detected as if no interaction took place with the probing photon. Here we show that the problem of interaction-free measurement can be regarded as a problem of quantum-channel discrimination. In particular, we look for the optimal photonic states that can minimize the detection error and the photon loss in detecting the presence or absence of the object, which is taken to be semitransparent, and the number of the interrogation cycle is assumed to be finite. Furthermore, we also investigated the possibility of minimizing the detection error through the use of entangled photons, which is essentially a setting of quantum illumination. However, our results indicate that entanglement does not exhibit a clear advantage; the same performance can be achieved with unentangled photonic states.

Authentication of the botanical origin of honey by near-infrared spectroscopy.

PubMed

Ruoff, Kaspar; Luginbühl, Werner; Bogdanov, Stefan; Bosset, Jacques Olivier; Estermann, Barbara; Ziolko, Thomas; Amado, Renato

2006-09-06

Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated for the authentication of eight unifloral and polyfloral honey types (n = 364 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis. The corresponding error rates were calculated according to Bayes' theorem. NIR spectroscopy enabled a reliable discrimination of acacia, chestnut, and fir honeydew honey from the other unifloral and polyfloral honey types studied. The error rates ranged from <0.1 to 6.3% depending on the honey type. NIR proved also to be useful for the classification of blossom and honeydew honeys. The results demonstrate that near-infrared spectrometry is a valuable, rapid, and nondestructive tool for the authentication of the above-mentioned honeys, but not for all varieties studied.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Man-portable Vector Time Domain EMI Sensor and Discrimination Processing

DTIC Science & Technology

2012-04-16

points of each winding are coincident. Each receiver coil is wound helically on a set of 10 grooves etched on the surface of the cube; 36- gauge wire...subset of the data, and inject various levels of noise into the position of the MPV in order to gauge the robustness of the discrimination results...as possible. The quantity φ also provides a metric to gauge goodness of fit, being essentially an average percent error: Benjamin Barrowes, Kevin

Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

Measurement uncertainty evaluation of conicity error inspected on CMM

NASA Astrophysics Data System (ADS)

Wang, Dongxia; Song, Aiguo; Wen, Xiulan; Xu, Youxiong; Qiao, Guifang

2016-01-01

The cone is widely used in mechanical design for rotation, centering and fixing. Whether the conicity error can be measured and evaluated accurately will directly influence its assembly accuracy and working performance. According to the new generation geometrical product specification(GPS), the error and its measurement uncertainty should be evaluated together. The mathematical model of the minimum zone conicity error is established and an improved immune evolutionary algorithm(IIEA) is proposed to search for the conicity error. In the IIEA, initial antibodies are firstly generated by using quasi-random sequences and two kinds of affinities are calculated. Then, each antibody clone is generated and they are self-adaptively mutated so as to maintain diversity. Similar antibody is suppressed and new random antibody is generated. Because the mathematical model of conicity error is strongly nonlinear and the input quantities are not independent, it is difficult to use Guide to the expression of uncertainty in the measurement(GUM) method to evaluate measurement uncertainty. Adaptive Monte Carlo method(AMCM) is proposed to estimate measurement uncertainty in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. The cone parts was machined on lathe CK6140 and measured on Miracle NC 454 Coordinate Measuring Machine(CMM). The experiment results confirm that the proposed method not only can search for the approximate solution of the minimum zone conicity error(MZCE) rapidly and precisely, but also can evaluate measurement uncertainty and give control variables with an expected numerical tolerance. The conicity errors computed by the proposed method are 20%-40% less than those computed by NC454 CMM software and the evaluation accuracy improves significantly.

Correcting AUC for Measurement Error.

PubMed

Rosner, Bernard; Tworoger, Shelley; Qiu, Weiliang

2015-12-01

Diagnostic biomarkers are used frequently in epidemiologic and clinical work. The ability of a diagnostic biomarker to discriminate between subjects who develop disease (cases) and subjects who do not (controls) is often measured by the area under the receiver operating characteristic curve (AUC). The diagnostic biomarkers are usually measured with error. Ignoring measurement error can cause biased estimation of AUC, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Several methods have been proposed to correct AUC for measurement error, most of which required the normality assumption for the distributions of diagnostic biomarkers. In this article, we propose a new method to correct AUC for measurement error and derive approximate confidence limits for the corrected AUC. The proposed method does not require the normality assumption. Both real data analyses and simulation studies show good performance of the proposed measurement error correction method.

45 CFR 148.180 - Prohibition of discrimination based on genetic information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... minimum amount of information necessary to make a decision regarding payment. Because the results of the... making a determination regarding the medical appropriateness of a claim if the genetic information is... information. 148.180 Section 148.180 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS...

12 CFR 1207.2 - Policy, purpose, and scope.

Code of Federal Regulations, 2011 CFR

2011-01-01

... INCLUSION (Eff. Jan. 27, 2011) General § 1207.2 Policy, purpose, and scope. (a) General policy. FHFA's policy is to promote non-discrimination, diversity and, at a minimum, the inclusion of women, minorities... maximum extent possible in balance with financially safe and sound business practices, the inclusion and...

Job Inequities Persist for Women.

ERIC Educational Resources Information Center

Smith, Barbara Ellen

1987-01-01

Women earn only 64 cents for every dollar earned by men. Five and a half million women number among the "working poor." The following are suggested for change: (1) raise the minimum wage; (2) institute gender- and race-blind pay scales; (3) establish child care centers; and (4) enforce anti-discrimination laws. (PS)

Experimental study on an FBG strain sensor

NASA Astrophysics Data System (ADS)

Liu, Hong-lin; Zhu, Zheng-wei; Zheng, Yong; Liu, Bang; Xiao, Feng

2018-01-01

Landslides and other geological disasters occur frequently and often cause high financial and humanitarian cost. The real-time, early-warning monitoring of landslides has important significance in reducing casualties and property losses. In this paper, by taking the high initial precision and high sensitivity advantage of FBG, an FBG strain sensor is designed combining FBGs with inclinometer. The sensor was regarded as a cantilever beam with one end fixed. According to the anisotropic material properties of the inclinometer, a theoretical formula between the FBG wavelength and the deflection of the sensor was established using the elastic mechanics principle. Accuracy of the formula established had been verified through laboratory calibration testing and model slope monitoring experiments. The displacement of landslide could be calculated by the established theoretical formula using the changing values of FBG central wavelength obtained by the demodulation instrument remotely. Results showed that the maximum error at different heights was 9.09%; the average of the maximum error was 6.35%, and its corresponding variance was 2.12; the minimum error was 4.18%; the average of the minimum error was 5.99%, and its corresponding variance was 0.50. The maximum error of the theoretical and the measured displacement decrease gradually, and the variance of the error also decreases gradually. This indicates that the theoretical results are more and more reliable. It also shows that the sensor and the theoretical formula established in this paper can be used for remote, real-time, high precision and early warning monitoring of the slope.

Human detection and discrimination of tactile repeatability, mechanical backlash, and temporal delay in a combined tactile-kinesthetic haptic display system.

PubMed

Doxon, Andrew J; Johnson, David E; Tan, Hong Z; Provancher, William R

2013-01-01

Many of the devices used in haptics research are over-engineered for the task and are designed with capabilities that go far beyond human perception levels. Designing devices that more closely match the limits of human perception will make them smaller, less expensive, and more useful. However, many device-centric perception thresholds have yet to be evaluated. To this end, three experiments were conducted, using one degree-of-freedom contact location feedback device in combination with a kinesthetic display, to provide a more explicit set of specifications for similar tactile-kinesthetic haptic devices. The first of these experiments evaluated the ability of humans to repeatedly localize tactile cues across the fingerpad. Subjects could localize cues to within 1.3 mm and showed bias toward the center of the fingerpad. The second experiment evaluated the minimum perceptible difference of backlash at the tactile element. Subjects were able to discriminate device backlash in excess of 0.46 mm on low-curvature models and 0.93 mm on high-curvature models. The last experiment evaluated the minimum perceptible difference of system delay between user action and device reaction. Subjects were able to discriminate delays in excess of 61 ms. The results from these studies can serve as the maximum (i.e., most demanding) device specifications for most tactile-kinesthetic haptic systems.

A solar cycle dependence of nonlinearity in magnetospheric activity

NASA Astrophysics Data System (ADS)

Johnson, Jay R.; Wing, Simon

2005-04-01

The nonlinear dependencies inherent to the historical Kp data stream (1932-2003) are examined using mutual information and cumulant-based cost as discriminating statistics. The discriminating statistics are compared with surrogate data streams that are constructed using the corrected amplitude adjustment Fourier transform (CAAFT) method and capture the linear properties of the original Kp data. Differences are regularly seen in the discriminating statistics a few years prior to solar minima, while no differences are apparent at the time of solar maxima. These results suggest that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solar minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to 1 week. Because the solar wind driver variables, VBs, and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities, the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current relaxation. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics, suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that may be related to increased solar wind speed.

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

Ford, S R; Walter, W R

The behavior of aftershock sequences around the Nevada Test Site in the southern Great Basin is characterized as a potential discriminant between explosions and earthquakes. The aftershock model designed by Reasenberg and Jones (1989, 1994) allows for a probabilistic statement of earthquake-like aftershock behavior at any time after the mainshock. We use this model to define two types of aftershock discriminants. The first defines M{sub X}, or the minimum magnitude of an aftershock expected within a given duration after the mainshock with probability X. Of the 67 earthquakes with M > 4 in the study region, 63 of them producemore » an aftershock greater than M{sub 99} within the first seven days after a mainshock. This is contrasted with only six of 93 explosions with M > 4 that produce an aftershock greater than M{sub 99} for the same period. If the aftershock magnitude threshold is lowered and the M{sub 90} criteria is used, then no explosions produce an aftershock greater than M{sub 90} for durations that end more than 17 days after the mainshock. The other discriminant defines N{sub X}, or the minimum cumulative number of aftershocks expected for given time after the mainshock with probability X. Similar to the aftershock magnitude discriminant, five earthquakes do not produce more aftershocks than N{sub 99} within 7 days after the mainshock. However, within the same period all but one explosion produce less aftershocks then N{sub 99}. One explosion is added if the duration is shortened to two days after than mainshock. The cumulative number aftershock discriminant is more reliable, especially at short durations, but requires a low magnitude of completeness for the given earthquake catalog. These results at NTS are quite promising and should be evaluated at other nuclear test sites to understand the effects of differences in the geologic setting and nuclear testing practices on its performance.« less

A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

PubMed

Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

2014-07-31

In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly.

A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Method for normalization

NASA Astrophysics Data System (ADS)

Harudin, N.; Jamaludin, K. R.; Muhtazaruddin, M. Nabil; Ramlie, F.; Muhamad, Wan Zuki Azman Wan

2018-03-01

T-Method is one of the techniques governed under Mahalanobis Taguchi System that developed specifically for multivariate data predictions. Prediction using T-Method is always possible even with very limited sample size. The user of T-Method required to clearly understanding the population data trend since this method is not considering the effect of outliers within it. Outliers may cause apparent non-normality and the entire classical methods breakdown. There exist robust parameter estimate that provide satisfactory results when the data contain outliers, as well as when the data are free of them. The robust parameter estimates of location and scale measure called Shamos Bickel (SB) and Hodges Lehman (HL) which are used as a comparable method to calculate the mean and standard deviation of classical statistic is part of it. Embedding these into T-Method normalize stage feasibly help in enhancing the accuracy of the T-Method as well as analysing the robustness of T-method itself. However, the result of higher sample size case study shows that T-method is having lowest average error percentages (3.09%) on data with extreme outliers. HL and SB is having lowest error percentages (4.67%) for data without extreme outliers with minimum error differences compared to T-Method. The error percentages prediction trend is vice versa for lower sample size case study. The result shows that with minimum sample size, which outliers always be at low risk, T-Method is much better on that, while higher sample size with extreme outliers, T-Method as well show better prediction compared to others. For the case studies conducted in this research, it shows that normalization of T-Method is showing satisfactory results and it is not feasible to adapt HL and SB or normal mean and standard deviation into it since it’s only provide minimum effect of percentages errors. Normalization using T-method is still considered having lower risk towards outlier’s effect.

Multiple-rule bias in the comparison of classification rules

PubMed Central

Yousefi, Mohammadmahdi R.; Hua, Jianping; Dougherty, Edward R.

2011-01-01

Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of reported results. Two approaches contributing to overoptimism in classification are (i) the reporting of results on datasets for which a proposed classification rule performs well and (ii) the comparison of multiple classification rules on a single dataset that purports to show the advantage of a certain rule. Results: This article provides a careful probabilistic analysis of the second issue and the ‘multiple-rule bias’, resulting from choosing a classification rule having minimum estimated error on the dataset. It quantifies this bias corresponding to estimating the expected true error of the classification rule possessing minimum estimated error and it characterizes the bias from estimating the true comparative advantage of the chosen classification rule relative to the others by the estimated comparative advantage on the dataset. The analysis is applied to both synthetic and real data using a number of classification rules and error estimators. Availability: We have implemented in C code the synthetic data distribution model, classification rules, feature selection routines and error estimation methods. The code for multiple-rule analysis is implemented in MATLAB. The source code is available at http://gsp.tamu.edu/Publications/supplementary/yousefi11a/. Supplementary simulation results are also included. Contact: edward@ece.tamu.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21546390

Coherent errors in quantum error correction

NASA Astrophysics Data System (ADS)

Greenbaum, Daniel; Dutton, Zachary

Analysis of quantum error correcting (QEC) codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. We present analytic results for the logical error as a function of concatenation level and code distance for coherent errors under the repetition code. For data-only coherent errors, we find that the logical error is partially coherent and therefore non-Pauli. However, the coherent part of the error is negligible after two or more concatenation levels or at fewer than ɛ - (d - 1) error correction cycles. Here ɛ << 1 is the rotation angle error per cycle for a single physical qubit and d is the code distance. These results support the validity of modeling coherent errors using a Pauli channel under some minimum requirements for code distance and/or concatenation. We discuss extensions to imperfect syndrome extraction and implications for general QEC.

Void Growth and Coalescence Simulations

DTIC Science & Technology

2013-08-01

distortion and damage, minimum time step, and appropriate material model parameters. Further, a temporal and spatial convergence study was used to...estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we use a Gurson model with Johnson-Cook...spatial convergence study was used to estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we

Neural self-tuning adaptive control of non-minimum phase system

NASA Technical Reports Server (NTRS)

Ho, Long T.; Bialasiewicz, Jan T.; Ho, Hai T.

1993-01-01

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity, if not unstable, closed-loop behavior. Therefore, a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

Estimates of the absolute error and a scheme for an approximate solution to scheduling problems

NASA Astrophysics Data System (ADS)

Lazarev, A. A.

2009-02-01

An approach is proposed for estimating absolute errors and finding approximate solutions to classical NP-hard scheduling problems of minimizing the maximum lateness for one or many machines and makespan is minimized. The concept of a metric (distance) between instances of the problem is introduced. The idea behind the approach is, given the problem instance, to construct another instance for which an optimal or approximate solution can be found at the minimum distance from the initial instance in the metric introduced. Instead of solving the original problem (instance), a set of approximating polynomially/pseudopolynomially solvable problems (instances) are considered, an instance at the minimum distance from the given one is chosen, and the resulting schedule is then applied to the original instance.

Ethnicity- and Sex-Based Discrimination and the Maintenance of Self-Esteem

PubMed Central

2015-01-01

The psychological underpinnings of labor market discrimination were investigated by having participants from Israel, the West Bank and Germany (N = 205) act as employers in a stylized employment task in which they ranked, set wages, and imposed a minimum effort level on applicants. State self-esteem was measured before and after the employment task, in which applicant ethnicity and sex were salient. The applicants were real people and all behavior was monetarily incentivized. Supporting the full self-esteem hypothesis of the social identity approach, low self-esteem in women was associated with assigning higher wages to women than to men, and such behavior was related to the maintenance of self-esteem. The narrower hypothesis that successful intergroup discrimination serves to protect self-esteem received broader support. Across all participants, both ethnicity- and sex-based discrimination of out-groups were associated with the maintenance of self-esteem, with the former showing a stronger association than the latter. PMID:25978646

Ligand Shaping in Induced Fit Docking of MraY Inhibitors. Polynomial Discriminant and Laplacian Operator as Biological Activity Descriptors

PubMed Central

Diudea, Mircea V.; Putz, Mihai V.

2017-01-01

Docking—i.e., interaction of a small molecule (ligand) with a proteic structure (receptor)—represents the ground of drug action mechanism of the vast majority of bioactive chemicals. Ligand and receptor accommodate their geometry and energy, within this interaction, in the benefit of receptor–ligand complex. In an induced fit docking, the structure of ligand is most susceptible to changes in topology and energy, comparative to the receptor. These changes can be described by manifold hypersurfaces, in terms of polynomial discriminant and Laplacian operator. Such topological surfaces were represented for each MraY (phospho-MurNAc-pentapeptide translocase) inhibitor, studied before and after docking with MraY. Binding affinities of all ligands were calculated by this procedure. For each ligand, Laplacian and polynomial discriminant were correlated with the ligand minimum inhibitory concentration (MIC) retrieved from literature. It was observed that MIC is correlated with Laplacian and polynomial discriminant. PMID:28653980

A recoil-proton spectrometer based on a p-i-n diode implementing pulse-shape discrimination.

PubMed

Agosteo, S; D'Angelo, G; Fazzi, A; Foglio Para, A; Pola, A; Ventura, L; Zotto, P

2004-01-01

A recoil-proton spectrometer was created by coupling a p-i-n diode with a polyethylene converter. The maximum detectable energy, imposed by the thickness of the totally depleted layer, is approximately 6 MeV. The minimum detectable energy is limited by the contribution of secondary electrons generated by photons in the detector assembly. This limit is approximately 1.5 MeV at full-depletion voltage and was decreased using pulse-shape discrimination. The diode was set up in the 'reverse-injection' configuration (i.e. with the N+ layer adjacent to the converter). This configuration provides longer collection times for the electron-hole pairs generated by the recoil-protons. The pulse-shape discrimination was based on the zero-crossing time of bipolar signals from a (CR)2-(RC)2 filter. The detector was characterised using monoenergetic neutrons generated in the Van De Graaff CN accelerator at the INFN-Laboratori Nazionali di Legnaro. The energy limit for discrimination proved to be approximately 900 keV.

A simple randomisation procedure for validating discriminant analysis: a methodological note.

PubMed

Wastell, D G

1987-04-01

Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.

Bilevel Model-Based Discriminative Dictionary Learning for Recognition.

PubMed

Zhou, Pan; Zhang, Chao; Lin, Zhouchen

2017-03-01

Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the l 0 or l 1 norm to encode each datum independently, limiting the performance of the learnt dictionaries. We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks. The upper level directly minimizes the classification error, while the lower level uses the sparsity term and the Laplacian term to characterize the intrinsic data structure. The lower level is subordinate to the upper level. Therefore, our model achieves an overall optimality for recognition in that the learnt dictionary is directly tailored for recognition. Moreover, the sparse codes learning models in the training and the testing phases can be the same. We further propose a novel method to solve our bilevel optimization problem. It first replaces the lower level with its Karush-Kuhn-Tucker conditions and then applies the alternating direction method of multipliers to solve the equivalent problem. Extensive experiments demonstrate the effectiveness and robustness of our method.

The impact of registration accuracy on imaging validation study design: A novel statistical power calculation.

PubMed

Gibson, Eli; Fenster, Aaron; Ward, Aaron D

2013-10-01

Novel imaging modalities are pushing the boundaries of what is possible in medical imaging, but their signal properties are not always well understood. The evaluation of these novel imaging modalities is critical to achieving their research and clinical potential. Image registration of novel modalities to accepted reference standard modalities is an important part of characterizing the modalities and elucidating the effect of underlying focal disease on the imaging signal. The strengths of the conclusions drawn from these analyses are limited by statistical power. Based on the observation that in this context, statistical power depends in part on uncertainty arising from registration error, we derive a power calculation formula relating registration error, number of subjects, and the minimum detectable difference between normal and pathologic regions on imaging, for an imaging validation study design that accommodates signal correlations within image regions. Monte Carlo simulations were used to evaluate the derived models and test the strength of their assumptions, showing that the model yielded predictions of the power, the number of subjects, and the minimum detectable difference of simulated experiments accurate to within a maximum error of 1% when the assumptions of the derivation were met, and characterizing sensitivities of the model to violations of the assumptions. The use of these formulae is illustrated through a calculation of the number of subjects required for a case study, modeled closely after a prostate cancer imaging validation study currently taking place at our institution. The power calculation formulae address three central questions in the design of imaging validation studies: (1) What is the maximum acceptable registration error? (2) How many subjects are needed? (3) What is the minimum detectable difference between normal and pathologic image regions? Copyright © 2013 Elsevier B.V. All rights reserved.

Near optimal discrimination of binary coherent signals via atom–light interaction

NASA Astrophysics Data System (ADS)

Han, Rui; Bergou, János A.; Leuchs, Gerd

2018-04-01

We study the discrimination of weak coherent states of light with significant overlaps by nondestructive measurements on the light states through measuring atomic states that are entangled to the coherent states via dipole coupling. In this way, the problem of measuring and discriminating coherent light states is shifted to finding the appropriate atom–light interaction and atomic measurements. We show that this scheme allows us to attain a probability of error extremely close to the Helstrom bound, the ultimate quantum limit for discriminating binary quantum states, through the simple Jaynes–Cummings interaction between the field and ancilla with optimized light–atom coupling and projective measurements on the atomic states. Moreover, since the measurement is nondestructive on the light state, information that is not detected by one measurement can be extracted from the post-measurement light states through subsequent measurements.

Optimization of multimagnetometer systems on a spacecraft

NASA Technical Reports Server (NTRS)

Neubauer, F. M.

1975-01-01

The problem of optimizing the position of magnetometers along a boom of given length to yield a minimized total error is investigated. The discussion is limited to at most four magnetometers, which seems to be a practical limit due to weight, power, and financial considerations. The outlined error analysis is applied to some illustrative cases. The optimal magnetometer locations, for which the total error is minimum, are computed for given boom length, instrument errors, and very conservative magnetic field models characteristic for spacecraft with only a restricted or ineffective magnetic cleanliness program. It is shown that the error contribution by the magnetometer inaccuracy is increased as the number of magnetometers is increased, whereas the spacecraft field uncertainty is diminished by an appreciably larger amount.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

PubMed

Sirgo, Gonzalo; Esteban, Federico; Gómez, Josep; Moreno, Gerard; Rodríguez, Alejandro; Blanch, Lluis; Guardiola, Juan José; Gracia, Rafael; De Haro, Lluis; Bodí, María

2018-04-01

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors. Copyright © 2018 Elsevier B.V. All rights reserved.

Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

PubMed

Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

2016-12-01

This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that the performance of the proposed system is comparative to that of state-of-the-art classification models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Forest/non-forest stratification in Georgia with Landsat Thematic Mapper data

Treesearch

William H. Cooke

2000-01-01

Geographically accurate Forest Inventory and Analysis (FIA) data may be useful for training, classification, and accuracy assessment of Landsat Thematic Mapper (TM) data. Minimum expectation for maps derived from Landsat data is accurate discrimination of several land cover classes. Landsat TM costs have decreased dramatically, but acquiring cloud-free scenes at...

Education Act Extends Sex Discrimination and Minimum Wage Provisions. Legislative Series 2.

ERIC Educational Resources Information Center

Employment Standards Administration (DOL), Washington, DC. Women's Bureau.

This brief presents highlights from the recently enacted Education Amendments which include comprehensive higher education provisions, authorization for greatly increased funding, and limitations on court-ordered busing. The act also establishes within HEW a National Institute of Education, whose prime purpose is to find ways to make educational…

Threshold dose for discrimination of nicotine via cigarette smoking.

PubMed

Perkins, Kenneth A; Kunkle, Nicole; Karelitz, Joshua L; Michael, Valerie C; Donny, Eric C

2016-06-01

The lowest nicotine threshold "dose" in cigarettes discriminated from a cigarette containing virtually no nicotine may help inform the minimum dose maintaining dependence. Spectrum research cigarettes (from NIDA) differing in nicotine content were used to evaluate a procedure to determine discrimination thresholds. Dependent smokers (n = 18; 13 M, 5 F) were tested on ability to discriminate cigarettes with nicotine contents of 11, 5, 2.4, and 1.3 mg/g, one per session, from the "ultralow" cigarette with 0.4 mg/g, after having discriminated 16 mg/g from 0.4 mg/g (all had 9-10 mg "tar"). Exposure to each was limited to 4 puffs/trial. All subjects were abstinent from smoking overnight prior to each session, and the number of sessions was determined by the participant's success in discrimination behavior on >80 % of trials. Subjective perceptions and behavioral choice between cigarettes were also assessed and related to discrimination behavior. The median threshold was 11 mg/g, but the range was 2.4 to 16 mg/g, suggesting wide variability in discrimination threshold. Compared to the ultralow, puff choice was greater for the subject's threshold dose but only marginal for the subthreshold (next lowest nicotine) cigarette. Threshold and subthreshold also differed on subjective perceptions but not withdrawal relief. Under these testing conditions, threshold content for discriminating nicotine via cigarettes may be 11 mg/g or greater for most smokers, but some can discriminate nicotine contents one-half or one-quarter this amount. Further study with other procedures and cigarette exposure amounts may identify systematic differences in nicotine discrimination thresholds.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Watson, Andrew B.

1994-01-01

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Analysis of the PLL phase error in presence of simulated ionospheric scintillation events

NASA Astrophysics Data System (ADS)

Forte, B.

2012-01-01

The functioning of standard phase locked loops (PLL), including those used to track radio signals from Global Navigation Satellite Systems (GNSS), is based on a linear approximation which holds in presence of small phase errors. Such an approximation represents a reasonable assumption in most of the propagation channels. However, in presence of a fading channel the phase error may become large, making the linear approximation no longer valid. The PLL is then expected to operate in a non-linear regime. As PLLs are generally designed and expected to operate in their linear regime, whenever the non-linear regime comes into play, they will experience a serious limitation in their capability to track the corresponding signals. The phase error and the performance of a typical PLL embedded into a commercial multiconstellation GNSS receiver were analyzed in presence of simulated ionospheric scintillation. Large phase errors occurred during scintillation-induced signal fluctuations although cycle slips only occurred during the signal re-acquisition after a loss of lock. Losses of lock occurred whenever the signal faded below the minimumC/N0threshold allowed for tracking. The simulations were performed for different signals (GPS L1C/A, GPS L2C, GPS L5 and Galileo L1). L5 and L2C proved to be weaker than L1. It appeared evident that the conditions driving the PLL phase error in the specific case of GPS receivers in presence of scintillation-induced signal perturbations need to be evaluated in terms of the combination of the minimumC/N0 tracking threshold, lock detector thresholds, possible cycle slips in the tracking PLL and accuracy of the observables (i.e. the error propagation onto the observables stage).

14 CFR 29.1323 - Airspeed indicating system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... minimum practicable instrument calibration error when the corresponding pitot and static pressures are... pitot tube or an equivalent means of preventing malfunction due to icing. [Doc. No. 5084, 29 FR 16150...

Integration time for the perception of depth from motion parallax.

PubMed

Nawrot, Mark; Stroyan, Keith

2012-04-15

The perception of depth from relative motion is believed to be a slow process that "builds-up" over a period of observation. However, in the case of motion parallax, the potential accuracy of the depth estimate suffers as the observer translates during the viewing period. Our recent quantitative model for the perception of depth from motion parallax proposes that relative object depth (d) can be determined from retinal image motion (dθ/dt), pursuit eye movement (dα/dt), and fixation distance (f) by the formula: d/f≈dθ/dα. Given the model's dynamics, it is important to know the integration time required by the visual system to recover dα and dθ, and then estimate d. Knowing the minimum integration time reveals the incumbent error in this process. A depth-phase discrimination task was used to determine the time necessary to perceive depth-sign from motion parallax. Observers remained stationary and viewed a briefly translating random-dot motion parallax stimulus. Stimulus duration varied between trials. Fixation on the translating stimulus was monitored and enforced with an eye-tracker. The study found that relative depth discrimination can be performed with presentations as brief as 16.6 ms, with only two stimulus frames providing both retinal image motion and the stimulus window motion for pursuit (mean range=16.6-33.2 ms). This was found for conditions in which, prior to stimulus presentation, the eye was engaged in ongoing pursuit or the eye was stationary. A large high-contrast masking stimulus disrupted depth-discrimination for stimulus presentations less than 70-75 ms in both pursuit and stationary conditions. This interval might be linked to ocular-following response eye-movement latencies. We conclude that neural mechanisms serving depth from motion parallax generate a depth estimate much more quickly than previously believed. We propose that additional sluggishness might be due to the visual system's attempt to determine the maximum dθ/dα ratio for a selection of points on a complicated stimulus. Copyright © 2012 Elsevier Ltd. All rights reserved.

Toward a fractal spectrum approach for neutron and gamma pulse shape discrimination

NASA Astrophysics Data System (ADS)

Liu, Ming-Zhe; Liu, Bing-Qi; Zuo, Zhuo; Wang, Lei; Zan, Gui-Bin; Tuo, Xian-Guo

2016-06-01

Accurately selecting neutron signals and discriminating γ signals from a mixed radiation field is a key research issue in neutron detection. This paper proposes a fractal spectrum discrimination approach by means of different spectral characteristics of neutrons and γ rays. Figure of merit and average discriminant error ratio are used together to evaluate the discrimination effects. Different neutron and γ signals with various noise and pulse pile-up are simulated according to real data in the literature. The proposed approach is compared with the digital charge integration and pulse gradient methods. It is found that the fractal approach exhibits the best discrimination performance, followed by the digital charge integration method and the pulse gradient method, respectively. The fractal spectrum approach is not sensitive to high frequency noise and pulse pile-up. This means that the proposed approach has superior performance for effective and efficient anti-noise and high discrimination in neutron detection. Supported by the National Natural Science Foundation of China (41274109), Sichuan Youth Science and Technology Innovation Research Team (2015TD0020), Scientific and Technological Support Program of Sichuan Province (2013FZ0022), and the Creative Team Program of Chengdu University of Technology.

Robustification and Optimization in Repetitive Control For Minimum Phase and Non-Minimum Phase Systems

NASA Astrophysics Data System (ADS)

Prasitmeeboon, Pitcha

Repetitive control (RC) is a control method that specifically aims to converge to zero tracking error of a control systems that execute a periodic command or have periodic disturbances of known period. It uses the error of one period back to adjust the command in the present period. In theory, RC can completely eliminate periodic disturbance effects. RC has applications in many fields such as high-precision manufacturing in robotics, computer disk drives, and active vibration isolation in spacecraft. The first topic treated in this dissertation develops several simple RC design methods that are somewhat analogous to PID controller design in classical control. From the early days of digital control, emulation methods were developed based on a Forward Rule, a Backward Rule, Tustin's Formula, a modification using prewarping, and a pole-zero mapping method. These allowed one to convert a candidate controller design to discrete time in a simple way. We investigate to what extent they can be used to simplify RC design. A particular design is developed from modification of the pole-zero mapping rules, which is simple and sheds light on the robustness of repetitive control designs. RC convergence requires less than 90 degree model phase error at all frequencies up to Nyquist. A zero-phase cutoff filter is normally used to robustify to high frequency model error when this limit is exceeded. The result is stabilization at the expense of failure to cancel errors above the cutoff. The second topic investigates a series of methods to use data to make real time updates of the frequency response model, allowing one to increase or eliminate the frequency cutoff. These include the use of a moving window employing a recursive discrete Fourier transform (DFT), and use of a real time projection algorithm from adaptive control for each frequency. The results can be used directly to make repetitive control corrections that cancel each error frequency, or they can be used to update a repetitive control FIR compensator. The aim is to reduce the final error level by using real time frequency response model updates to successively increase the cutoff frequency, each time creating the improved model needed to produce convergence zero error up to the higher cutoff. Non-minimum phase systems present a difficult design challenge to the sister field of Iterative Learning Control. The third topic investigates to what extent the same challenges appear in RC. One challenge is that the intrinsic non-minimum phase zero mapped from continuous time is close to the pole of repetitive controller at +1 creating behavior similar to pole-zero cancellation. The near pole-zero cancellation causes slow learning at DC and low frequencies. The Min-Max cost function over the learning rate is presented. The Min-Max can be reformulated as a Quadratically Constrained Linear Programming problem. This approach is shown to be an RC design approach that addresses the main challenge of non-minimum phase systems to have a reasonable learning rate at DC. Although it was illustrated that using the Min-Max objective improves learning at DC and low frequencies compared to other designs, the method requires model accuracy at high frequencies. In the real world, models usually have error at high frequencies. The fourth topic addresses how one can merge the quadratic penalty to the Min-Max cost function to increase robustness at high frequencies. The topic also considers limiting the Min-Max optimization to some frequencies interval and applying an FIR zero-phase low-pass filter to cutoff the learning for frequencies above that interval.

Bolus-dependent dosimetric effect of positioning errors for tangential scalp radiotherapy with helical tomotherapy

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

Lobb, Eric, E-mail: eclobb2@gmail.com

2014-04-01

The dosimetric effect of errors in patient position is studied on-phantom as a function of simulated bolus thickness to assess the need for bolus utilization in scalp radiotherapy with tomotherapy. A treatment plan is generated on a cylindrical phantom, mimicking a radiotherapy technique for the scalp utilizing primarily tangential beamlets. A planning target volume with embedded scalplike clinical target volumes (CTVs) is planned to a uniform dose of 200 cGy. Translational errors in phantom position are introduced in 1-mm increments and dose is recomputed from the original sinogram. For each error the maximum dose, minimum dose, clinical target dose homogeneitymore » index (HI), and dose-volume histogram (DVH) are presented for simulated bolus thicknesses from 0 to 10 mm. Baseline HI values for all bolus thicknesses were in the 5.5 to 7.0 range, increasing to a maximum of 18.0 to 30.5 for the largest positioning errors when 0 to 2 mm of bolus is used. Utilizing 5 mm of bolus resulted in a maximum HI value of 9.5 for the largest positioning errors. Using 0 to 2 mm of bolus resulted in minimum and maximum dose values of 85% to 94% and 118% to 125% of the prescription dose, respectively. When using 5 mm of bolus these values were 98.5% and 109.5%. DVHs showed minimal changes in CTV dose coverage when using 5 mm of bolus, even for the largest positioning errors. CTV dose homogeneity becomes increasingly sensitive to errors in patient position as bolus thickness decreases when treating the scalp with primarily tangential beamlets. Performing a radial expansion of the scalp CTV into 5 mm of bolus material minimizes dosimetric sensitivity to errors in patient position as large as 5 mm and is therefore recommended.« less

An effective biometric discretization approach to extract highly discriminative, informative, and privacy-protective binary representation

NASA Astrophysics Data System (ADS)

Lim, Meng-Hui; Teoh, Andrew Beng Jin

2011-12-01

Biometric discretization derives a binary string for each user based on an ordered set of biometric features. This representative string ought to be discriminative, informative, and privacy protective when it is employed as a cryptographic key in various security applications upon error correction. However, it is commonly believed that satisfying the first and the second criteria simultaneously is not feasible, and a tradeoff between them is always definite. In this article, we propose an effective fixed bit allocation-based discretization approach which involves discriminative feature extraction, discriminative feature selection, unsupervised quantization (quantization that does not utilize class information), and linearly separable subcode (LSSC)-based encoding to fulfill all the ideal properties of a binary representation extracted for cryptographic applications. In addition, we examine a number of discriminative feature-selection measures for discretization and identify the proper way of setting an important feature-selection parameter. Encouraging experimental results vindicate the feasibility of our approach.

The effect of covariate mean differences on the standard error and confidence interval for the comparison of treatment means.

PubMed

Liu, Xiaofeng Steven

2011-05-01

The use of covariates is commonly believed to reduce the unexplained error variance and the standard error for the comparison of treatment means, but the reduction in the standard error is neither guaranteed nor uniform over different sample sizes. The covariate mean differences between the treatment conditions can inflate the standard error of the covariate-adjusted mean difference and can actually produce a larger standard error for the adjusted mean difference than that for the unadjusted mean difference. When the covariate observations are conceived of as randomly varying from one study to another, the covariate mean differences can be related to a Hotelling's T(2) . Using this Hotelling's T(2) statistic, one can always find a minimum sample size to achieve a high probability of reducing the standard error and confidence interval width for the adjusted mean difference. ©2010 The British Psychological Society.

Cutting the Cord: Discrimination and Command Responsibility in Autonomous Lethal Weapons

DTIC Science & Technology

2014-02-13

machine responses to identical stimuli, and it was the job of a third party human “witness” to determine which participant was man and which was...machines may be error free, but there are potential benefits to be gained through autonomy if machines can meet or exceed human performance in...lieu of human operators and reap the benefits that autonomy provides. Human and Machine Error It would be foolish to assert that either humans

A Comparison between Discrimination Indices and Item-Response Theory Using the Rasch Model in a Clinical Course Written Examination of a Medical School.

PubMed

Park, Jong Cook; Kim, Kwang Sig

2012-03-01

The reliability of test is determined by each items' characteristics. Item analysis is achieved by classical test theory and item response theory. The purpose of the study was to compare the discrimination indices with item response theory using the Rasch model. Thirty-one 4th-year medical school students participated in the clinical course written examination, which included 22 A-type items and 3 R-type items. Point biserial correlation coefficient (C(pbs)) was compared to method of extreme group (D), biserial correlation coefficient (C(bs)), item-total correlation coefficient (C(it)), and corrected item-total correlation coeffcient (C(cit)). Rasch model was applied to estimate item difficulty and examinee's ability and to calculate item fit statistics using joint maximum likelihood. Explanatory power (r2) of Cpbs is decreased in the following order: C(cit) (1.00), C(it) (0.99), C(bs) (0.94), and D (0.45). The ranges of difficulty logit and standard error and ability logit and standard error were -0.82 to 0.80 and 0.37 to 0.76, -3.69 to 3.19 and 0.45 to 1.03, respectively. Item 9 and 23 have outfit > or =1.3. Student 1, 5, 7, 18, 26, 30, and 32 have fit > or =1.3. C(pbs), C(cit), and C(it) are good discrimination parameters. Rasch model can estimate item difficulty parameter and examinee's ability parameter with standard error. The fit statistics can identify bad items and unpredictable examinee's responses.

A novel method for assessing contrast sensitivity in the beagle dog is sensitive to age and an antioxidant enriched food.

PubMed

de Rivera, Christina; Boutet, Isabelle; Zicker, Steven C; Milgram, Norton W

2005-03-01

Tasks requiring visual discrimination are commonly used in assessment of canine cognitive function. However, little is known about canine visual processing, and virtually nothing is known about the effects of age on canine visual function. This study describes a novel behavioural method developed to assess one aspect of canine visual function, namely contrast sensitivity. Four age groups (young, middle aged, old, and senior) were studied. We also included a group of middle aged to old animals that had been maintained for at least 4 years on a specially formulated food containing a broad spectrum of antioxidants and mitochondrial cofactors. Performance of this group was compared with a group in the same age range maintained on a control diet. In the first phase, all animals were trained to discriminate between two high contrast shapes. In the second phase, contrast was progressively reduced by increasing the luminance of the shapes. Performance decreased as a function of age, but the differences did not achieve statistical significance, possibly because of a small sample size in the young group. All age groups were able to acquire the initial discrimination, although the two older age groups showed slower learning. Errors increased with decreasing contrast with the maximal number of errors for the 1% contrast shape. Also, all animals on the antioxidant diet learned the task and had significantly fewer errors at the high contrast compared with the animals on the control diet. The initial results suggest that contrast sensitivity deteriorates with age in the canine while form perception is largely unaffected by age.

Impact of Compounding Error on Strategies for Subtyping Pathogenic Bacteria

PubMed Central

Orfe, Lisa; Davis, Margaret A.; Lafrentz, Stacey; Kang, Min-Su

2008-01-01

Abstract Comparative-omics will identify a multitude of markers that can be used for intraspecific discrimination between strains of bacteria. It seems intuitive that with this plethora of markers we can construct higher resolution subtyping assays using discrete markers to define strain “barcodes.” Unfortunately, with each new marker added to an assay, overall assay robustness declines because errors are compounded exponentially. For example, the difference in accuracy of strain classification for an assay with 60 markers will change from 99.9% to 54.7% when average probe accuracy declines from 99.999% to 99.0%. To illustrate this effect empirically, we constructed a 19 probe bead-array for subtyping Listeria monocytogenes and showed that despite seemingly reliable individual probe accuracy (>97%), our best classification results at the strain level were <75%. A more robust strategy would use as few markers as possible to achieve strain discrimination. Consequently, we developed two variable number of tandem repeat (VNTR) assays (Vibrio parahaemolyticus and L. monocytogenes) and demonstrate that these assays along with a published assay (Salmonella enterica) produce robust results when products were machine scored. The discriminatory ability with four to seven VNTR loci was comparable to pulsed-field gel electrophoresis. Passage experiments showed some instability with ca. 5% of passaged lines showing evidence for new alleles within 30 days (V. parahaemolyticus and S. enterica). Changes were limited to a single locus and allele so conservative rules can be used to determine strain matching. Most importantly, VNTRs appear robust and portable and can clearly discriminate between strains with relatively few loci thereby limiting effects of compounding error. PMID:18713065

'Sorry, I meant the patient's left side': impact of distraction on left-right discrimination.

PubMed

McKinley, John; Dempster, Martin; Gormley, Gerard J

2015-04-01

Medical students can have difficulty in distinguishing left from right. Many infamous medical errors have occurred when a procedure has been performed on the wrong side, such as in the removal of the wrong kidney. Clinicians encounter many distractions during their work. There is limited information on how these affect performance. Using a neuropsychological paradigm, we aim to elucidate the impacts of different types of distraction on left-right (LR) discrimination ability. Medical students were recruited to a study with four arms: (i) control arm (no distraction); (ii) auditory distraction arm (continuous ambient ward noise); (iii) cognitive distraction arm (interruptions with clinical cognitive tasks), and (iv) auditory and cognitive distraction arm. Participants' LR discrimination ability was measured using the validated Bergen Left-Right Discrimination Test (BLRDT). Multivariate analysis of variance was used to analyse the impacts of the different forms of distraction on participants' performance on the BLRDT. Additional analyses looked at effects of demographics on performance and correlated participants' self-perceived LR discrimination ability and their actual performance. A total of 234 students were recruited. Cognitive distraction had a greater negative impact on BLRDT performance than auditory distraction. Combined auditory and cognitive distraction had a negative impact on performance, but only in the most difficult LR task was this negative impact found to be significantly greater than that of cognitive distraction alone. There was a significant medium-sized correlation between perceived LR discrimination ability and actual overall BLRDT performance. Distraction has a significant impact on performance and multifaceted approaches are required to reduce LR errors. Educationally, greater emphasis on the linking of theory and clinical application is required to support patient safety and human factor training in medical school curricula. Distraction has the potential to impair an individual's ability to make accurate LR decisions and students should be trained from undergraduate level to be mindful of this. © 2015 John Wiley & Sons Ltd.

Computer program to minimize prediction error in models from experiments with 16 hypercube points and 0 to 6 center points

NASA Technical Reports Server (NTRS)

Holms, A. G.

1982-01-01

A previous report described a backward deletion procedure of model selection that was optimized for minimum prediction error and which used a multiparameter combination of the F - distribution and an order statistics distribution of Cochran's. A computer program is described that applies the previously optimized procedure to real data. The use of the program is illustrated by examples.

Predictive momentum management for a space station measurement and computation requirements

NASA Technical Reports Server (NTRS)

Adams, John Carl

1986-01-01

An analysis is made of the effects of errors and uncertainties in the predicting of disturbance torques on the peak momentum buildup on a space station. Models of the disturbance torques acting on a space station in low Earth orbit are presented, to estimate how accurately they can be predicted. An analysis of the torque and momentum buildup about the pitch axis of the Dual Keel space station configuration is formulated, and a derivation of the Average Torque Equilibrium Attitude (ATEA) is presented, for the case of no MRMS (Mobile Remote Manipulation System) motion, Y vehicle axis MRMS motion, and Z vehicle axis MRMS motion. Results showed the peak momentum buildup to be approximately 20000 N-m-s and to be relatively insensitive to errors in the predicting torque models, for Z axis motion of the MRMS was found to vary significantly with model errors, but not exceed a value of approximately 15000 N-m-s for the Y axis MRMS motion with 1 deg attitude hold error. Minimum peak disturbance momentum was found not to occur at the ATEA angle, but at a slightly smaller angle. However, this minimum peak momentum attitude was found to produce significant disturbance momentum at the end of the predicting time interval.

Construction of type-II QC-LDPC codes with fast encoding based on perfect cyclic difference sets

NASA Astrophysics Data System (ADS)

Li, Ling-xiang; Li, Hai-bing; Li, Ji-bi; Jiang, Hua

2017-09-01

In view of the problems that the encoding complexity of quasi-cyclic low-density parity-check (QC-LDPC) codes is high and the minimum distance is not large enough which leads to the degradation of the error-correction performance, the new irregular type-II QC-LDPC codes based on perfect cyclic difference sets (CDSs) are constructed. The parity check matrices of these type-II QC-LDPC codes consist of the zero matrices with weight of 0, the circulant permutation matrices (CPMs) with weight of 1 and the circulant matrices with weight of 2 (W2CMs). The introduction of W2CMs in parity check matrices makes it possible to achieve the larger minimum distance which can improve the error- correction performance of the codes. The Tanner graphs of these codes have no girth-4, thus they have the excellent decoding convergence characteristics. In addition, because the parity check matrices have the quasi-dual diagonal structure, the fast encoding algorithm can reduce the encoding complexity effectively. Simulation results show that the new type-II QC-LDPC codes can achieve a more excellent error-correction performance and have no error floor phenomenon over the additive white Gaussian noise (AWGN) channel with sum-product algorithm (SPA) iterative decoding.

Cost-effectiveness of the stream-gaging program in North Carolina

USGS Publications Warehouse

Mason, R.R.; Jackson, N.M.

1985-01-01

This report documents the results of a study of the cost-effectiveness of the stream-gaging program in North Carolina. Data uses and funding sources are identified for the 146 gaging stations currently operated in North Carolina with a budget of $777,600 (1984). As a result of the study, eleven stations are nominated for discontinuance and five for conversion from recording to partial-record status. Large parts of North Carolina 's Coastal Plain are identified as having sparse streamflow data. This sparsity should be remedied as funds become available. Efforts should also be directed toward defining the efforts of drainage improvements on local hydrology and streamflow characteristics. The average standard error of streamflow records in North Carolina is 18.6 percent. This level of accuracy could be improved without increasing cost by increasing the frequency of field visits and streamflow measurements at stations with high standard errors and reducing the frequency at stations with low standard errors. A minimum budget of $762,000 is required to operate the 146-gage program. A budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, and with the optimum allocation of field visits, the average standard error is 17.6 percent.

Cost effectiveness of the US Geological Survey's stream-gaging programs in New Hampshire and Vermont

USGS Publications Warehouse

Smath, J.A.; Blackey, F.E.

1986-01-01

Data uses and funding sources were identified for the 73 continuous stream gages currently (1984) being operated. Eight stream gages were identified as having insufficient reason to continue their operation. Parts of New Hampshire and Vermont were identified as needing additional hydrologic data. New gages should be established in these regions as funds become available. Alternative methods for providing hydrologic data at the stream gaging stations currently being operated were found to lack the accuracy that is required for their intended use. The current policy for operation of the stream gages requires a net budget of $297,000/yr. The average standard error of estimation of the streamflow records is 17.9%. This overall level of accuracy could be maintained with a budget of $285,000 if resources were redistributed among gages. Cost-effective analysis indicates that with the present budget, the average standard error could be reduced to 16.6%. A minimum budget of $278,000 is required to operate the present stream gaging program. Below this level, the gages and recorders would not receive the proper service and maintenance. At the minimum budget, the average standard error would be 20.4%. The loss of correlative data is a significant component of the error in streamflow records, especially at lower budgetary levels. (Author 's abstract)

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Force-Time Entropy of Isometric Impulse.

PubMed

Hsieh, Tsung-Yu; Newell, Karl M

2016-01-01

The relation between force and temporal variability in discrete impulse production has been viewed as independent (R. A. Schmidt, H. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979 ) or dependent on the rate of force (L. G. Carlton & K. M. Newell, 1993 ). Two experiments in an isometric single finger force task investigated the joint force-time entropy with (a) fixed time to peak force and different percentages of force level and (b) fixed percentage of force level and different times to peak force. The results showed that the peak force variability increased either with the increment of force level or through a shorter time to peak force that also reduced timing error variability. The peak force entropy and entropy of time to peak force increased on the respective dimension as the parameter conditions approached either maximum force or a minimum rate of force production. The findings show that force error and timing error are dependent but complementary when considered in the same framework with the joint force-time entropy at a minimum in the middle parameter range of discrete impulse.

Geological Carbon Sequestration: A New Approach for Near-Surface Assurance Monitoring

PubMed Central

Wielopolski, Lucian

2011-01-01

There are two distinct objectives in monitoring geological carbon sequestration (GCS): Deep monitoring of the reservoir’s integrity and plume movement and near-surface monitoring (NSM) to ensure public health and the safety of the environment. However, the minimum detection limits of the current instrumentation for NSM is too high for detecting weak signals that are embedded in the background levels of the natural variations, and the data obtained represents point measurements in space and time. A new approach for NSM, based on gamma-ray spectroscopy induced by inelastic neutron scatterings (INS), offers novel and unique characteristics providing the following: (1) High sensitivity with a reducible error of measurement and detection limits, and, (2) temporal- and spatial-integration of carbon in soil that results from underground CO2 seepage. Preliminary field results validated this approach showing carbon suppression of 14% in the first year and 7% in the second year. In addition the temporal behavior of the error propagation is presented and it is shown that for a signal at the level of the minimum detection level the error asymptotically approaches 47%. PMID:21556180

Music Recognition in Frontotemporal Lobar Degeneration and Alzheimer Disease

PubMed Central

Johnson, Julene K; Chang, Chiung-Chih; Brambati, Simona M; Migliaccio, Raffaella; Gorno-Tempini, Maria Luisa; Miller, Bruce L; Janata, Petr

2013-01-01

Objective To compare music recognition in patients with frontotemporal dementia, semantic dementia, Alzheimer disease, and controls and to evaluate the relationship between music recognition and brain volume. Background Recognition of familiar music depends on several levels of processing. There are few studies about how patients with dementia recognize familiar music. Methods Subjects were administered tasks that assess pitch and melody discrimination, detection of pitch errors in familiar melodies, and naming of familiar melodies. Results There were no group differences on pitch and melody discrimination tasks. However, patients with semantic dementia had considerable difficulty naming familiar melodies and also scored the lowest when asked to identify pitch errors in the same melodies. Naming familiar melodies, but not other music tasks, was strongly related to measures of semantic memory. Voxel-based morphometry analysis of brain MRI showed that difficulty in naming songs was associated with the bilateral temporal lobes and inferior frontal gyrus, whereas difficulty in identifying pitch errors in familiar melodies correlated with primarily the right temporal lobe. Conclusions The results support a view that the anterior temporal lobes play a role in familiar melody recognition, and that musical functions are affected differentially across forms of dementia. PMID:21617528

Multiple Cognitive Control Effects of Error Likelihood and Conflict

PubMed Central

Brown, Joshua W.

2010-01-01

Recent work on cognitive control has suggested a variety of performance monitoring functions of the anterior cingulate cortex, such as errors, conflict, error likelihood, and others. Given the variety of monitoring effects, a corresponding variety of control effects on behavior might be expected. This paper explores whether conflict and error likelihood produce distinct cognitive control effects on behavior, as measured by response time. A change signal task (Brown & Braver, 2005) was modified to include conditions of likely errors due to tardy as well as premature responses, in conditions with and without conflict. The results discriminate between competing hypotheses of independent vs. interacting conflict and error likelihood control effects. Specifically, the results suggest that the likelihood of premature vs. tardy response errors can lead to multiple distinct control effects, which are independent of cognitive control effects driven by response conflict. As a whole, the results point to the existence of multiple distinct cognitive control mechanisms and challenge existing models of cognitive control that incorporate only a single control signal. PMID:19030873

General linear codes for fault-tolerant matrix operations on processor arrays

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Abraham, J. A.

1988-01-01

Various checksum codes have been suggested for fault-tolerant matrix computations on processor arrays. Use of these codes is limited due to potential roundoff and overflow errors. Numerical errors may also be misconstrued as errors due to physical faults in the system. In this a set of linear codes is identified which can be used for fault-tolerant matrix operations such as matrix addition, multiplication, transposition, and LU-decomposition, with minimum numerical error. Encoding schemes are given for some of the example codes which fall under the general set of codes. With the help of experiments, a rule of thumb for the selection of a particular code for a given application is derived.

Determination of vigabatrin in plasma by reversed-phase high-performance liquid chromatography.

PubMed

Tsanaclis, L M; Wicks, J; Williams, J; Richens, A

1991-05-01

A method is described for the determination of vigabatrin in 50 microliters of plasma by isocratic high-performance liquid chromatography using fluorescence detection. The procedure involves protein precipitation with methanol followed by precolumn derivatisation with o-phthaldialdehyde reagent. Separation of the derivatised vigabatrin was achieved on a Microsorb C18 column using a mobile phase of 10 mM orthophosphoric acid:acetonitrile:methanol (6:3:1) at a flow rate of 2.0 ml/min. Assay time is 15 min and chromatograms show no interference from commonly coadministered anticonvulsant drugs. The total analytical error within the range of 0.85-85 micrograms/ml was found to be 7.6% with the within-replicates error of 2.76%. The minimum detection limit was 0.08 micrograms/ml and the minimum quantitation limit was 0.54 micrograms/ml.

Metameric MIMO-OOK transmission scheme using multiple RGB LEDs.

PubMed

Bui, Thai-Chien; Cusani, Roberto; Scarano, Gaetano; Biagi, Mauro

2018-05-28

In this work, we propose a novel visible light communication (VLC) scheme utilizing multiple different red green and blue triplets each with a different emission spectrum of red, green and blue for mitigating the effect of interference due to different colors using spatial multiplexing. On-off keying modulation is considered and its effect on light emission in terms of flickering, dimming and color rendering is discussed so as to demonstrate how metameric properties have been considered. At the receiver, multiple photodiodes with color filter-tuned on each transmit light emitting diode (LED) are employed. Three different detection mechanisms of color zero forcing, minimum mean square error estimation and minimum mean square error equalization are then proposed. The system performance of the proposed scheme is evaluated both with computer simulations and tests with an Arduino board implementation.

A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

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

Romero, Louis A; Mason, John J.

We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, themore » problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.« less

Discriminative power of visual attributes in dermatology.

PubMed

Giotis, Ioannis; Visser, Margaretha; Jonkman, Marcel; Petkov, Nicolai

2013-02-01

Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach. We estimate the probability of occurrence of each attribute as a function of the skin diseases. We use the distribution of this probability across the studied diseases and its entropy to define the discriminative power of the attribute. The discriminative power has a maximum value for attributes that occur (or do not occur) for only one disease and a minimum value for those which are equally likely to be observed among all diseases. Verrucous surface, red and brown colors, and the presence of more than 10 lesions are among the most informative attributes. A ranking of attributes is also carried out and used together with a naive Bayesian classifier, yielding results that confirm the soundness of the proposed method. proposed measure is proven to be a reliable way of assessing the discriminative power of dermatological attributes, and it also helps generate a condensed dermatological lexicon. Therefore, it can be of added value to the manual or computer-aided diagnostic process. © 2012 John Wiley & Sons A/S.

SU-G-BRB-11: On the Sensitivity of An EPID-Based 3D Dose Verification System to Detect Delivery Errors in VMAT Treatments

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

Gonzalez, P; Olaciregui-Ruiz, I; Mijnheer, B

2016-06-15

Purpose: To investigate the sensitivity of an EPID-based 3D dose verification system to detect delivery errors in VMAT treatments. Methods: For this study 41 EPID-reconstructed 3D in vivo dose distributions of 15 different VMAT plans (H&N, lung, prostate and rectum) were selected. To simulate the effect of delivery errors, their TPS plans were modified by: 1) scaling of the monitor units by ±3% and ±6% and 2) systematic shifting of leaf bank positions by ±1mm, ±2mm and ±5mm. The 3D in vivo dose distributions where then compared to the unmodified and modified treatment plans. To determine the detectability of themore » various delivery errors, we made use of a receiver operator characteristic (ROC) methodology. True positive and false positive rates were calculated as a function of the γ-parameters γmean, γ1% (near-maximum γ) and the PTV dose parameter ΔD{sub 50} (i.e. D{sub 50}(EPID)-D{sub 50}(TPS)). The ROC curve is constructed by plotting the true positive rate vs. the false positive rate. The area under the ROC curve (AUC) then serves as a measure of the performance of the EPID dosimetry system in detecting a particular error; an ideal system has AUC=1. Results: The AUC ranges for the machine output errors and systematic leaf position errors were [0.64 – 0.93] and [0.48 – 0.92] respectively using γmean, [0.57 – 0.79] and [0.46 – 0.85] using γ1% and [0.61 – 0.77] and [ 0.48 – 0.62] using ΔD{sub 50}. Conclusion: For the verification of VMAT deliveries, the parameter γmean is the best discriminator for the detection of systematic leaf position errors and monitor unit scaling errors. Compared to γmean and γ1%, the parameter ΔD{sub 50} performs worse as a discriminator in all cases.« less

Cost effectiveness of the stream-gaging program in South Carolina

USGS Publications Warehouse

Barker, A.C.; Wright, B.C.; Bennett, C.S.

1985-01-01

The cost effectiveness of the stream-gaging program in South Carolina was documented for the 1983 water yr. Data uses and funding sources were identified for the 76 continuous stream gages currently being operated in South Carolina. The budget of $422,200 for collecting and analyzing streamflow data also includes the cost of operating stage-only and crest-stage stations. The streamflow records for one stream gage can be determined by alternate, less costly methods, and should be discontinued. The remaining 75 stations should be maintained in the program for the foreseeable future. The current policy for the operation of the 75 stations including the crest-stage and stage-only stations would require a budget of $417,200/yr. The average standard error of estimation of streamflow records is 16.9% for the present budget with missing record included. However, the standard error of estimation would decrease to 8.5% if complete streamflow records could be obtained. It was shown that the average standard error of estimation of 16.9% could be obtained at the 75 sites with a budget of approximately $395,000 if the gaging resources were redistributed among the gages. A minimum budget of $383,500 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, the average standard error is 18.6%. The maximum budget analyzed was $850,000, which resulted in an average standard error of 7.6 %. (Author 's abstract)

Application of multispectral reflectance for early detection of tomato disease

NASA Astrophysics Data System (ADS)

Xu, Huirong; Zhu, Shengpan; Ying, Yibin; Jiang, Huanyu

2006-10-01

Automatic diagnosis of plant disease is important for plant management and environmental preservation in the future. The objective of this study is to use multispectral reflectance measurements to make an early discrimination between the healthy and infected plants by the strain of tobacco mosaic virus (TMV-U1) infection. There were reflectance changes in the visible (VIS) and near infrared spectroscopy (NIR) between the healthy and infected plants. Discriminant models were developed using discriminant partial least squares (DPLS) and Mahalanobis distance (MD). The DPLS models had a root mean square error of calibration (RMSEC) of 0.397 and correlation coefficient (r) of 0.59 and the MD model correctly classified 86.7% healthy plants and up to 91.7% infected plants.

Effect of grid transparency and finite collector size on determining ion temperature and density by the retarding potential analyzer

NASA Technical Reports Server (NTRS)

Troy, B. E., Jr.; Maier, E. J.

1975-01-01

The effects of the grid transparency and finite collector size on the values of thermal ion density and temperature determined by the standard RPA (retarding potential analyzer) analysis method are investigated. The current-voltage curves calculated for varying RPA parameters and a given ion mass, temperature, and density are analyzed by the standard RPA method. It is found that only small errors in temperature and density are introduced for an RPA with typical dimensions, and that even when the density error is substantial for nontypical dimensions, the temperature error remains minimum.

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1990-01-01

An expurgated upper bound on the event error probability of trellis coded modulation is presented. This bound is used to derive a lower bound on the minimum achievable free Euclidean distance d sub (free) of trellis codes. It is shown that the dominant parameters for both bounds, the expurgated error exponent and the asymptotic d sub (free) growth rate, respectively, can be obtained from the cutoff-rate R sub O of the transmission channel by a simple geometric construction, making R sub O the central parameter for finding good trellis codes. Several constellations are optimized with respect to the bounds.

New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

Simplified Syndrome Decoding of (n, 1) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

A Solar Cycle Dependence of Nonlinearity in Magnetospheric Activity

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

Johnson, Jay R; Wing, Simon

2005-03-08

The nonlinear dependencies inherent to the historical K(sub)p data stream (1932-2003) are examined using mutual information and cumulant based cost as discriminating statistics. The discriminating statistics are compared with surrogate data streams that are constructed using the corrected amplitude adjustment Fourier transform (CAAFT) method and capture the linear properties of the original K(sub)p data. Differences are regularly seen in the discriminating statistics a few years prior to solar minima, while no differences are apparent at the time of solar maximum. These results suggest that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solarmore » minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to one week. Because the solar wind driver variables, VB(sub)s and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities, the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current relaxation. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that may be related to increased solar wind speed.« less

On the Discriminant Analysis in the 2-Populations Case

NASA Astrophysics Data System (ADS)

Rublík, František

2008-01-01

The empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule.

An MDI (Minimum Discrimination Information) Model and an Algorithm for Composite Hypotheses Testing and Estimation in Marketing. Revision 2.

DTIC Science & Technology

1982-09-01

considered to be Markovian and the fact that Ehrenberg has been openly critical of the use of first-order Markov processes in describing consumer ... behavior -/ disinclines us to treating these data in this manner. We Shall therefore interpret the p (i,i) as joint rather than conditional probabilities

A Working Woman's Guide To Her Job Rights. Leaflet 55.

ERIC Educational Resources Information Center

Women's Bureau (DOL), Washington, DC.

This leaflet presents general information about legislation that affects women when they are seeking a job, while they are on the job, and when they retire. Emphasis is on Federal laws as of November, 1978. Some of the topics include employment services, protection against sex and age discrimination, minimum wages and overtime pay, discrimination…

Automated identification and tracking of polar-cap plasma patches at solar minimum

NASA Astrophysics Data System (ADS)

Burston, R.; Hodges, K.; Astin, I.; Jayachandran, P. T.

2014-03-01

A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

Cryptographic robustness of a quantum cryptography system using phase-time coding

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

Molotkov, S. N.

2008-01-15

A cryptographic analysis is presented of a new quantum key distribution protocol using phase-time coding. An upper bound is obtained for the error rate that guarantees secure key distribution. It is shown that the maximum tolerable error rate for this protocol depends on the counting rate in the control time slot. When no counts are detected in the control time slot, the protocol guarantees secure key distribution if the bit error rate in the sifted key does not exceed 50%. This protocol partially discriminates between errors due to system defects (e.g., imbalance of a fiber-optic interferometer) and eavesdropping. In themore » absence of eavesdropping, the counts detected in the control time slot are not caused by interferometer imbalance, which reduces the requirements for interferometer stability.« less

General subspace learning with corrupted training data via graph embedding.

PubMed

Bao, Bing-Kun; Liu, Guangcan; Hong, Richang; Yan, Shuicheng; Xu, Changsheng

2013-11-01

We address the following subspace learning problem: supposing we are given a set of labeled, corrupted training data points, how to learn the underlying subspace, which contains three components: an intrinsic subspace that captures certain desired properties of a data set, a penalty subspace that fits the undesired properties of the data, and an error container that models the gross corruptions possibly existing in the data. Given a set of data points, these three components can be learned by solving a nuclear norm regularized optimization problem, which is convex and can be efficiently solved in polynomial time. Using the method as a tool, we propose a new discriminant analysis (i.e., supervised subspace learning) algorithm called Corruptions Tolerant Discriminant Analysis (CTDA), in which the intrinsic subspace is used to capture the features with high within-class similarity, the penalty subspace takes the role of modeling the undesired features with high between-class similarity, and the error container takes charge of fitting the possible corruptions in the data. We show that CTDA can well handle the gross corruptions possibly existing in the training data, whereas previous linear discriminant analysis algorithms arguably fail in such a setting. Extensive experiments conducted on two benchmark human face data sets and one object recognition data set show that CTDA outperforms the related algorithms.

Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy.

PubMed

de Almeida, Maurício Liberal; Saatkamp, Cassiano Junior; Fernandes, Adriana Barrinha; Pinheiro, Antonio Luiz Barbosa; Silveira, Landulfo

2016-09-01

Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.

Region of influence regression for estimating the 50-year flood at ungaged sites

USGS Publications Warehouse

Tasker, Gary D.; Hodge, S.A.; Barks, C.S.

1996-01-01

Five methods of developing regional regression models to estimate flood characteristics at ungaged sites in Arkansas are examined. The methods differ in the manner in which the State is divided into subrogions. Each successive method (A to E) is computationally more complex than the previous method. Method A makes no subdivision. Methods B and C define two and four geographic subrogions, respectively. Method D uses cluster/discriminant analysis to define subrogions on the basis of similarities in watershed characteristics. Method E, the new region of influence method, defines a unique subregion for each ungaged site. Split-sample results indicate that, in terms of root-mean-square error, method E (38 percent error) is best. Methods C and D (42 and 41 percent error) were in a virtual tie for second, and methods B (44 percent error) and A (49 percent error) were fourth and fifth best.

Bootstrap Methods: A Very Leisurely Look.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Winstead, Wayland H.

The Bootstrap method, a computer-intensive statistical method of estimation, is illustrated using a simple and efficient Statistical Analysis System (SAS) routine. The utility of the method for generating unknown parameters, including standard errors for simple statistics, regression coefficients, discriminant function coefficients, and factor…

L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

PubMed

Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

2014-04-01

A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.

Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF.

PubMed

Liu, Chao; Gu, Jinwei

2014-01-01

Classifying raw, unpainted materials--metal, plastic, ceramic, fabric, and so on--is an important yet challenging task for computer vision. Previous works measure subsets of surface spectral reflectance as features for classification. However, acquiring the full spectral reflectance is time consuming and error-prone. In this paper, we propose to use coded illumination to directly measure discriminative features for material classification. Optimal illumination patterns--which we call "discriminative illumination"--are learned from training samples, after projecting to which the spectral reflectance of different materials are maximally separated. This projection is automatically realized by the integration of incident light for surface reflection. While a single discriminative illumination is capable of linear, two-class classification, we show that multiple discriminative illuminations can be used for nonlinear and multiclass classification. We also show theoretically that the proposed method has higher signal-to-noise ratio than previous methods due to light multiplexing. Finally, we construct an LED-based multispectral dome and use the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy, steel, stainless steel, brass, and copper), plastic, ceramic, fabric, and wood. Experimental results demonstrate its effectiveness.

Cost-effectiveness of the Federal stream-gaging program in Virginia

USGS Publications Warehouse

Carpenter, D.H.

1985-01-01

Data uses and funding sources were identified for the 77 continuous stream gages currently being operated in Virginia by the U.S. Geological Survey with a budget of $446,000. Two stream gages were identified as not being used sufficiently to warrant continuing their operation. Operation of these stations should be considered for discontinuation. Data collected at two other stations were identified as having uses primarily related to short-term studies; these stations should also be considered for discontinuation at the end of the data collection phases of the studies. The remaining 73 stations should be kept in the program for the foreseeable future. The current policy for operation of the 77-station program requires a budget of $446,000/yr. The average standard error of estimation of streamflow records is 10.1%. It was shown that this overall level of accuracy at the 77 sites could be maintained with a budget of $430,500 if resources were redistributed among the gages. A minimum budget of $428,500 is required to operate the 77-gage program; a smaller budget would not permit proper service and maintenance of the gages and recorders. At the minimum budget, with optimized operation, the average standard error would be 10.4%. The maximum budget analyzed was $650,000, which resulted in an average standard error of 5.5%. The study indicates that a major component of error is caused by lost or missing data. If perfect equipment were available, the standard error for the current program and budget could be reduced to 7.6%. This also can be interpreted to mean that the streamflow data have a standard error of this magnitude during times when the equipment is operating properly. (Author 's abstract)

Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors

PubMed Central

Kassabian, Nazelie; Presti, Letizia Lo; Rispoli, Francesco

2014-01-01

Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS) signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE) algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs). This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs) distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold. PMID:24922454

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

NASA Astrophysics Data System (ADS)

Lobit, P.; López Pérez, L.; Lhomme, J. P.; Gómez Tagle, A.

2017-07-01

This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = -0.07 kPa). The applicability of the method to other environments is discussed.

Measurement of the lowest dosage of phenobarbital that can produce drug discrimination in rats

PubMed Central

Overton, Donald A.; Stanwood, Gregg D.; Patel, Bhavesh N.; Pragada, Sreenivasa R.; Gordon, M. Kathleen

2009-01-01

Rationale Accurate measurement of the threshold dosage of phenobarbital that can produce drug discrimination (DD) may improve our understanding of the mechanisms and properties of such discrimination. Objectives Compare three methods for determining the threshold dosage for phenobarbital (D) versus no drug (N) DD. Methods Rats learned a D versus N DD in 2-lever operant training chambers. A titration scheme was employed to increase or decrease dosage at the end of each 18-day block of sessions depending on whether the rat had achieved criterion accuracy during the sessions just completed. Three criterion rules were employed, all based on average percent drug lever responses during initial links of the last 6 D and 6 N sessions of a block. The criteria were: D%>66 and N%<33; D%>50 and N%<50; (D%-N%)>33. Two squads of rats were trained, one immediately after the other. Results All rats discriminated drug versus no drug. In most rats, dosage decreased to low levels and then oscillated near the minimum level required to maintain criterion performance. The lowest discriminated dosage significantly differed under the three criterion rules. The squad that was trained 2nd may have benefited by partially duplicating the lever choices of the previous squad. Conclusions The lowest discriminated dosage is influenced by the criterion of discriminative control that is employed, and is higher than the absolute threshold at which discrimination entirely disappears. Threshold estimations closer to absolute threshold can be obtained when criteria are employed that are permissive, and that allow rats to maintain lever preferences. PMID:19082992

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

PubMed

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Discrimination-related health inequality and role of social capital among marriage migrant women in South Korea.

PubMed

Kim, Chang-O

2016-10-26

This study aimed to evaluate whether social capital could alleviate health inequality against racial discrimination and identify the critical nature of social capital that generates health inequality differences within the social context of South Korea. Using the data of the 2009 National Survey of Multicultural Families, a nationally representative sample in which 40,430 foreign wives participated, the concentration index (CI) was used to measure the discrimination-related inequalities in self-rated health and was decomposed into contributing factors. The results showed a significant concentration of poor self-rated health unfavorable to foreign wives who were highly discriminated (CI 0.023, standard error [SE] 0.001, p < .001). However, when the CIs were assessed among the subgroups of different social capital, no discrimination-related inequality in health was observed among the group of linking social capital (CI 0.008, SE 0.008, p .332). The total differential decomposition method showed two major factors that generate differences in health inequality between the groups of non-linking and linking social capital: protest against discrimination (35.8 %); experiences of discrimination (28.3 %). The present results indicated that linking social capital can be a useful resource of health resilience factor that equalizes discrimination-related health inequality among marriage migrant women in South Korea. This study provides additional evidence that social capital needs to be placed in its political context.

The protective role of racial identity and Africentric worldview in the association between racial discrimination and blood pressure.

PubMed

Neblett, Enrique W; Carter, Sierra E

2012-06-01

To examine the protective effects of racial identity and Africentric worldview on the association between racial discrimination and blood pressure (BP). Two hundred ten African American young adults completed questionnaires assessing demographic characteristics, prior racial discrimination experiences, racial identity, and Africentric worldview. Resting BP was assessed before and after completion of the study measures. Racial discrimination was unrelated to BP in the overall sample (systolic BP, p = .444; diastolic BP [DBP], p = .915; mean arterial pressure, p = .774). However, racial identity and Africentric worldview moderated the association between racial discrimination and BP. Racial discrimination was negatively related to DBP for participants who felt that others viewed African Americans less favorably and who endorsed the uniqueness of the African American experience (B = -2.59, standard error [SE] = 1.29, p = .046). These individuals also had the lowest DBP at high levels of racial discrimination. Racial discrimination was positively associated with DBP for individuals with low levels of Africentric orientation (B = 1.43, SE = 0.72, p = .048) but was unrelated to DBP at moderate (B = 0.24, SE = 0.65, p = .718) and high (B = -0.96, SE = 1.01, p = .341) levels of Africentric worldview. Racial and cultural personal characteristics such as racial identity and Africentric orientation may serve an important protective function for BP in African American young adults.

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Quantizing and sampling considerations in digital phased-locked loops

NASA Technical Reports Server (NTRS)

Hurst, G. T.; Gupta, S. C.

1974-01-01

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

78 FR 17155 - Standards for the Growing, Harvesting, Packing, and Holding of Produce for Human Consumption...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

...The Food and Drug Administration (FDA or we) is correcting the preamble to a proposed rule that published in the Federal Register of January 16, 2013. That proposed rule would establish science-based minimum standards for the safe growing, harvesting, packing, and holding of produce, meaning fruits and vegetables grown for human consumption. FDA proposed these standards as part of our implementation of the FDA Food Safety Modernization Act. The document published with several technical errors, including some errors in cross references, as well as several errors in reference numbers cited throughout the document. This document corrects those errors. We are also placing a corrected copy of the proposed rule in the docket.

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

Prenatal betamethasone exposure has sex specific effects in reversal learning and attention in juvenile baboons

PubMed Central

RODRIGUEZ, Jesse S.; ZÜRCHER, Nicole R.; KEENAN, Kathryn E.; BARTLETT, Thad Q.; NATHANIELSZ, Peter W.; NIJLAND, Mark J.

2011-01-01

Objective We investigated effects of three weekly courses of fetal betamethasone (βM) exposure on motivation and cognition in juvenile baboon offspring utilizing the Cambridge Neuropsychological Test Automated Battery. Study design Pregnant baboons (Papio sp.) received two injections of saline control (C) or 175 μg/kg βM 24h apart at 0.6, 0.65 and 0.7 gestation. Offspring [Female (FC), n = 7 and Male (MC), n = 6; Female (FβM), n = 7 and Male (MβM), n = 5] were studied at 2.6–3.2 years with a progressive ratio test for motivation, simple discriminations (SD) and reversals (SR) for associative learning and rule change plasticity, and an intra-dimensional/extra-dimensional (IDED) set-shifting test for attention allocation. Results βM exposure decreased motivation in both sexes. In IDED testing, FβM made more errors in the SR [mean difference of errors (FβM minus MβM) = 20.2 ± 9.9; P≤0.05], compound discrimination [mean difference of errors = 36.3 ± 17.4; P≤0.05] and compound reversal [mean difference of errors = 58 ± 23.6; P<0.05] stages as compared to the MβM offspring. Conclusion This central nervous system developmental programming adds growing concerns of long-term effects of repeated fetal synthetic glucocorticoid exposure. In summary, behavioral effects observed show sex specific differences in resilience to multiple fetal βM exposures. PMID:21411054

The Caledonian face test: A new test of face discrimination.

PubMed

Logan, Andrew J; Wilkinson, Frances; Wilson, Hugh R; Gordon, Gael E; Loffler, Gunter

2016-02-01

This study aimed to develop a clinical test of face perception which is applicable to a wide range of patients and can capture normal variability. The Caledonian face test utilises synthetic faces which combine simplicity with sufficient realism to permit individual identification. Face discrimination thresholds (i.e. minimum difference between faces required for accurate discrimination) were determined in an "odd-one-out" task. The difference between faces was controlled by an adaptive QUEST procedure. A broad range of face discrimination sensitivity was determined from a group (N=52) of young adults (mean 5.75%; SD 1.18; range 3.33-8.84%). The test is fast (3-4 min), repeatable (test-re-test r(2)=0.795) and demonstrates a significant inversion effect. The potential to identify impairments of face discrimination was evaluated by testing LM who reported a lifelong difficulty with face perception. While LM's impairment for two established face tests was close to the criterion for significance (Z-scores of -2.20 and -2.27) for the Caledonian face test, her Z-score was -7.26, implying a more than threefold higher sensitivity. The new face test provides a quantifiable and repeatable assessment of face discrimination ability. The enhanced sensitivity suggests that the Caledonian face test may be capable of detecting more subtle impairments of face perception than available tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Growth Simulation and Discrimination of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum Using Hyperspectral Reflectance Imaging

PubMed Central

Gu, Xinzhe; Wang, Zhenjie; Huang, Yangmin; Wei, Yingying; Zhang, Miaomiao; Tu, Kang

2015-01-01

This research aimed to develop a rapid and nondestructive method to model the growth and discrimination of spoilage fungi, like Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum, based on hyperspectral imaging system (HIS). A hyperspectral imaging system was used to measure the spectral response of fungi inoculated on potato dextrose agar plates and stored at 28°C and 85% RH. The fungi were analyzed every 12 h over two days during growth, and optimal simulation models were built based on HIS parameters. The results showed that the coefficients of determination (R2) of simulation models for testing datasets were 0.7223 to 0.9914, and the sum square error (SSE) and root mean square error (RMSE) were in a range of 2.03–53.40×10−4 and 0.011–0.756, respectively. The correlation coefficients between the HIS parameters and colony forming units of fungi were high from 0.887 to 0.957. In addition, fungi species was discriminated by partial least squares discrimination analysis (PLSDA), with the classification accuracy of 97.5% for the test dataset at 36 h. The application of this method in real food has been addressed through the analysis of Botrytis cinerea, Rhizopus stolonifer and Colletotrichum acutatum inoculated in peaches, demonstrating that the HIS technique was effective for simulation of fungal infection in real food. This paper supplied a new technique and useful information for further study into modeling the growth of fungi and detecting fruit spoilage caused by fungi based on HIS. PMID:26642054

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis.

PubMed

Garcia, E; Klaas, I; Amigo, J M; Bro, R; Enevoldsen, C

2014-12-01

Lameness causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods. Eighty variables retrieved from AMS were summarized week-wise and used to predict 2 defined classes: nonlame and clinically lame cows. Variables were represented with 2 transformations of the week summarized variables, using 2-wk data blocks before gait scoring, totaling 320 variables (2 × 2 × 80). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3 or 4/4) or not lame (score 1/4). Both models achieved sensitivity and specificity values around 80%, both in calibration and cross-validation. At the optimum values in the receiver operating characteristic curve, the false-positive rate was 28% in the parity 1 model, whereas in the parity 2 model it was about half (16%), which makes it more suitable for practical application; the model error rates were, 23 and 19%, respectively. Based on data registered automatically from one AMS farm, we were able to discriminate nonlame and lame cows, where partial least squares discriminant analysis achieved similar performance to the reference method. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Change deafness for real spatialized environmental scenes.

PubMed

Gaston, Jeremy; Dickerson, Kelly; Hipp, Daniel; Gerhardstein, Peter

2017-01-01

The everyday auditory environment is complex and dynamic; often, multiple sounds co-occur and compete for a listener's cognitive resources. 'Change deafness', framed as the auditory analog to the well-documented phenomenon of 'change blindness', describes the finding that changes presented within complex environments are often missed. The present study examines a number of stimulus factors that may influence change deafness under real-world listening conditions. Specifically, an AX (same-different) discrimination task was used to examine the effects of both spatial separation over a loudspeaker array and the type of change (sound source additions and removals) on discrimination of changes embedded in complex backgrounds. Results using signal detection theory and accuracy analyses indicated that, under most conditions, errors were significantly reduced for spatially distributed relative to non-spatial scenes. A second goal of the present study was to evaluate a possible link between memory for scene contents and change discrimination. Memory was evaluated by presenting a cued recall test following each trial of the discrimination task. Results using signal detection theory and accuracy analyses indicated that recall ability was similar in terms of accuracy, but there were reductions in sensitivity compared to previous reports. Finally, the present study used a large and representative sample of outdoor, urban, and environmental sounds, presented in unique combinations of nearly 1000 trials per participant. This enabled the exploration of the relationship between change perception and the perceptual similarity between change targets and background scene sounds. These (post hoc) analyses suggest both a categorical and a stimulus-level relationship between scene similarity and the magnitude of change errors.

Guyana dolphins (Sotalia guianensis) from Costa Rica emit whistles that vary with surface behaviors.

PubMed

May-Collado, Laura J

2013-10-01

Guyana dolphins show remarkable intraspecific whistle variation. This variation has been largely explained in terms of distance among populations; however, other factors such as behavior may also be important. A broadband recording system recorded the whistles of Guyana dolphins under three behavioral states. A discriminant analysis found that during social and travel events, dolphins emit whistles with high delta and minimum frequency, respectively. Whistle duration was also important in discriminating behaviors. This study indicates that behavior is an important factor contributing to whistle variation of Guyana dolphins. Understanding how dolphin whistles vary with behavioral context will advance our understanding of dolphin communication and enable appropriate comparative studies.

Discriminative Multi-View Interactive Image Re-Ranking.

PubMed

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Human listeners provide insights into echo features used by dolphins (Tursiops truncatus) to discriminate among objects.

PubMed

Delong, Caroline M; Au, Whitlow W L; Harley, Heidi E; Roitblat, Herbert L; Pytka, Lisa

2007-08-01

Echolocating bottlenose dolphins (Tursiops truncatus) discriminate between objects on the basis of the echoes reflected by the objects. However, it is not clear which echo features are important for object discrimination. To gain insight into the salient features, the authors had a dolphin perform a match-to-sample task and then presented human listeners with echoes from the same objects used in the dolphin's task. In 2 experiments, human listeners performed as well or better than the dolphin at discriminating objects, and they reported the salient acoustic cues. The error patterns of the humans and the dolphin were compared to determine which acoustic features were likely to have been used by the dolphin. The results indicate that the dolphin did not appear to use overall echo amplitude, but that it attended to the pattern of changes in the echoes across different object orientations. Human listeners can quickly identify salient combinations of echo features that permit object discrimination, which can be used to generate hypotheses that can be tested using dolphins as subjects.

Spatial and temporal variability of the overall error of National Atmospheric Deposition Program measurements determined by the USGS collocated-sampler program, water years 1989-2001

USGS Publications Warehouse

Wetherbee, G.A.; Latysh, N.E.; Gordon, J.D.

2005-01-01

Data from the U.S. Geological Survey (USGS) collocated-sampler program for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) are used to estimate the overall error of NADP/NTN measurements. Absolute errors are estimated by comparison of paired measurements from collocated instruments. Spatial and temporal differences in absolute error were identified and are consistent with longitudinal distributions of NADP/NTN measurements and spatial differences in precipitation characteristics. The magnitude of error for calcium, magnesium, ammonium, nitrate, and sulfate concentrations, specific conductance, and sample volume is of minor environmental significance to data users. Data collected after a 1994 sample-handling protocol change are prone to less absolute error than data collected prior to 1994. Absolute errors are smaller during non-winter months than during winter months for selected constituents at sites where frozen precipitation is common. Minimum resolvable differences are estimated for different regions of the USA to aid spatial and temporal watershed analyses.

Simulating a transmon implementation of the surface code, Part I

NASA Astrophysics Data System (ADS)

Tarasinski, Brian; O'Brien, Thomas; Rol, Adriaan; Bultink, Niels; Dicarlo, Leo

Current experimental efforts aim to realize Surface-17, a distance-3 surface-code logical qubit, using transmon qubits in a circuit QED architecture. Following experimental proposals for this device, and currently achieved fidelities on physical qubits, we define a detailed error model that takes experimentally relevant error sources into account, such as amplitude and phase damping, imperfect gate pulses, and coherent errors due to low-frequency flux noise. Using the GPU-accelerated software package 'quantumsim', we simulate the density matrix evolution of the logical qubit under this error model. Combining the simulation results with a minimum-weight matching decoder, we obtain predictions for the error rate of the resulting logical qubit when used as a quantum memory, and estimate the contribution of different error sources to the logical error budget. Research funded by the Foundation for Fundamental Research on Matter (FOM), the Netherlands Organization for Scientific Research (NWO/OCW), IARPA, an ERC Synergy Grant, the China Scholarship Council, and Intel Corporation.

New syndrome decoder for (n, 1) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

Optimum nonparametric estimation of population density based on ordered distances

USGS Publications Warehouse

Patil, S.A.; Kovner, J.L.; Burnham, Kenneth P.

1982-01-01

The asymptotic mean and error mean square are determined for the nonparametric estimator of plant density by distance sampling proposed by Patil, Burnham and Kovner (1979, Biometrics 35, 597-604. On the basis of these formulae, a bias-reduced version of this estimator is given, and its specific form is determined which gives minimum mean square error under varying assumptions about the true probability density function of the sampled data. Extension is given to line-transect sampling.

Minimum savings requirements in shared savings provider payment.

PubMed

Pope, Gregory C; Kautter, John

2012-11-01

Payer (insurer) sharing of savings is a way of motivating providers of medical services to reduce cost growth. A Medicare shared savings program is established for accountable care organizations in the 2010 Patient Protection and Affordable Care Act. However, savings created by providers cannot be distinguished from the normal (random) variation in medical claims costs, setting up a classic principal-agent problem. To lessen the likelihood of paying undeserved bonuses, payers may pay bonuses only if observed savings exceed minimum levels. We study the trade-off between two types of errors in setting minimum savings requirements: paying bonuses when providers do not create savings and not paying bonuses when providers create savings. Copyright © 2011 John Wiley & Sons, Ltd.

LOOP- SIMULATION OF THE AUTOMATIC FREQUENCY CONTROL SUBSYSTEM OF A DIFFERENTIAL MINIMUM SHIFT KEYING RECEIVER

NASA Technical Reports Server (NTRS)

Davarian, F.

1994-01-01

The LOOP computer program was written to simulate the Automatic Frequency Control (AFC) subsystem of a Differential Minimum Shift Keying (DMSK) receiver with a bit rate of 2400 baud. The AFC simulated by LOOP is a first order loop configuration with a first order R-C filter. NASA has been investigating the concept of mobile communications based on low-cost, low-power terminals linked via geostationary satellites. Studies have indicated that low bit rate transmission is suitable for this application, particularly from the frequency and power conservation point of view. A bit rate of 2400 BPS is attractive due to its applicability to the linear predictive coding of speech. Input to LOOP includes the following: 1) the initial frequency error; 2) the double-sided loop noise bandwidth; 3) the filter time constants; 4) the amount of intersymbol interference; and 5) the bit energy to noise spectral density. LOOP output includes: 1) the bit number and the frequency error of that bit; 2) the computed mean of the frequency error; and 3) the standard deviation of the frequency error. LOOP is written in MS SuperSoft FORTRAN 77 for interactive execution and has been implemented on an IBM PC operating under PC DOS with a memory requirement of approximately 40K of 8 bit bytes. This program was developed in 1986.

Improving estimates of streamflow characteristics by using Landsat-1 imagery

USGS Publications Warehouse

Hollyday, Este F.

1976-01-01

Imagery from the first Earth Resources Technology Satellite (renamed Landsat-1) was used to discriminate physical features of drainage basins in an effort to improve equations used to estimate streamflow characteristics at gaged and ungaged sites. Records of 20 gaged basins in the Delmarva Peninsula of Maryland, Delaware, and Virginia were analyzed for 40 statistical streamflow characteristics. Equations relating these characteristics to basin characteristics were obtained by a technique of multiple linear regression. A control group of equations contains basin characteristics derived from maps. An experimental group of equations contains basin characteristics derived from maps and imagery. Characteristics from imagery were forest, riparian (streambank) vegetation, water, and combined agricultural and urban land use. These basin characteristics were isolated photographically by techniques of film-density discrimination. The area of each characteristic in each basin was measured photometrically. Comparison of equations in the control group with corresponding equations in the experimental group reveals that for 12 out of 40 equations the standard error of estimate was reduced by more than 10 percent. As an example, the standard error of estimate of the equation for the 5-year recurrence-interval flood peak was reduced from 46 to 32 percent. Similarly, the standard error of the equation for the mean monthly flow for September was reduced from 32 to 24 percent, the standard error for the 7-day, 2-year recurrence low flow was reduced from 136 to 102 percent, and the standard error for the 3-day, 2-year flood volume was reduced from 30 to 12 percent. It is concluded that data from Landsat imagery can substantially improve the accuracy of estimates of some streamflow characteristics at sites in the Delmarva Peninsula.

Characterization of Signal Quality Monitoring Techniques for Multipath Detection in GNSS Applications.

PubMed

Pirsiavash, Ali; Broumandan, Ali; Lachapelle, Gérard

2017-07-05

The performance of Signal Quality Monitoring (SQM) techniques under different multipath scenarios is analyzed. First, SQM variation profiles are investigated as critical requirements in evaluating the theoretical performance of SQM metrics. The sensitivity and effectiveness of SQM approaches for multipath detection and mitigation are then defined and analyzed by comparing SQM profiles and multipath error envelopes for different discriminators. Analytical discussions includes two discriminator strategies, namely narrow and high resolution correlator techniques for BPSK(1), and BOC(1,1) signaling schemes. Data analysis is also carried out for static and kinematic scenarios to validate the SQM profiles and examine SQM performance in actual multipath environments. Results show that although SQM is sensitive to medium and long-delay multipath, its effectiveness in mitigating these ranges of multipath errors varies based on tracking strategy and signaling scheme. For short-delay multipath scenarios, the multipath effect on pseudorange measurements remains mostly undetected due to the low sensitivity of SQM metrics.

Authentication of the botanical and geographical origin of honey by mid-infrared spectroscopy.

PubMed

Ruoff, Kaspar; Luginbühl, Werner; Künzli, Raphael; Iglesias, María Teresa; Bogdanov, Stefan; Bosset, Jacques Olivier; von der Ohe, Katharina; von der Ohe, Werner; Amado, Renato

2006-09-06

The potential of Fourier transform mid-infrared spectroscopy (FT-MIR) using an attenuated total reflectance (ATR) cell was evaluated for the authentication of 11 unifloral (acacia, alpine rose, chestnut, dandelion, heather, lime, rape, fir honeydew, metcalfa honeydew, oak honeydew) and polyfloral honey types (n = 411 samples) previously classified with traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis, the error rates of the discriminant models being calculated by using Bayes' theorem. The error rates ranged from <0.1% (polyfloral and heather honeys as well as honeydew honeys from metcalfa, oak, and fir) to 8.3% (alpine rose honey) in both jackknife classification and validation, depending on the honey type considered. This study indicates that ATR-MIR spectroscopy is a valuable tool for the authentication of the botanical origin and quality control and may also be useful for the determination of the geographical origin of honey.

Sex differences in discriminative power of volleyball game-related statistics.

PubMed

João, Paulo Vicente; Leite, Nuno; Mesquita, Isabel; Sampaio, Jaime

2010-12-01

To identify sex differences in volleyball game-related statistics, the game-related statistics of several World Championships in 2007 (N=132) were analyzed using the software VIS from the International Volleyball Federation. Discriminant analysis was used to identify the game-related statistics which better discriminated performances by sex. Analysis yielded an emphasis on fault serves (SC = -.40), shot spikes (SC = .40), and reception digs (SC = .31). Specific robust numbers represent that considerable variability was evident in the game-related statistics profile, as men's volleyball games were better associated with terminal actions (errors of service), and women's volleyball games were characterized by continuous actions (in defense and attack). These differences may be related to the anthropometric and physiological differences between women and men and their influence on performance profiles.

Joint Transmitter and Receiver Power Allocation under Minimax MSE Criterion with Perfect and Imperfect CSI for MC-CDMA Transmissions

NASA Astrophysics Data System (ADS)

Kotchasarn, Chirawat; Saengudomlert, Poompat

We investigate the problem of joint transmitter and receiver power allocation with the minimax mean square error (MSE) criterion for uplink transmissions in a multi-carrier code division multiple access (MC-CDMA) system. The objective of power allocation is to minimize the maximum MSE among all users each of which has limited transmit power. This problem is a nonlinear optimization problem. Using the Lagrange multiplier method, we derive the Karush-Kuhn-Tucker (KKT) conditions which are necessary for a power allocation to be optimal. Numerical results indicate that, compared to the minimum total MSE criterion, the minimax MSE criterion yields a higher total MSE but provides a fairer treatment across the users. The advantages of the minimax MSE criterion are more evident when we consider the bit error rate (BER) estimates. Numerical results show that the minimax MSE criterion yields a lower maximum BER and a lower average BER. We also observe that, with the minimax MSE criterion, some users do not transmit at full power. For comparison, with the minimum total MSE criterion, all users transmit at full power. In addition, we investigate robust joint transmitter and receiver power allocation where the channel state information (CSI) is not perfect. The CSI error is assumed to be unknown but bounded by a deterministic value. This problem is formulated as a semidefinite programming (SDP) problem with bilinear matrix inequality (BMI) constraints. Numerical results show that, with imperfect CSI, the minimax MSE criterion also outperforms the minimum total MSE criterion in terms of the maximum and average BERs.

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects.

PubMed

Sollmann, Nico; Hauck, Theresa; Tussis, Lorena; Ille, Sebastian; Maurer, Stefanie; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-10-24

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated. Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7-30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0-26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9-27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0-24.2 mm) were measured. According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

Cost effective stream-gaging strategies for the Lower Colorado River basin; the Blythe field office operations

USGS Publications Warehouse

Moss, Marshall E.; Gilroy, Edward J.

1980-01-01

This report describes the theoretical developments and illustrates the applications of techniques that recently have been assembled to analyze the cost-effectiveness of federally funded stream-gaging activities in support of the Colorado River compact and subsequent adjudications. The cost effectiveness of 19 stream gages in terms of minimizing the sum of the variances of the errors of estimation of annual mean discharge is explored by means of a sequential-search optimization scheme. The search is conducted over a set of decision variables that describes the number of times that each gaging route is traveled in a year. A gage route is defined as the most expeditious circuit that is made from a field office to visit one or more stream gages and return to the office. The error variance is defined as a function of the frequency of visits to a gage by using optimal estimation theory. Currently a minimum of 12 visits per year is made to any gage. By changing to a six-visit minimum, the same total error variance can be attained for the 19 stations with a budget of 10% less than the current one. Other strategies are also explored. (USGS)

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error☆☆☆

PubMed Central

Stenroos, Matti; Hauk, Olaf

2013-01-01

The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG + EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation. We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics. The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG + EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG + EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only. PMID:23639259

Macular Ganglion Cell and Retinal Nerve Fiber Layer Thickness in Children With Refractive Errors-An Optical Coherence Tomography Study.

PubMed

Goh, Jody P; Koh, Victor; Chan, Yiong Huak; Ngo, Cheryl

2017-07-01

To study the distribution of macular ganglion cell-inner plexiform layer (GC-IPL) thickness and peripapillary retinal nerve fiber layer (RNFL) thickness in children with refractive errors. Two hundred forty-three healthy eyes from 139 children with refractive error ranging from -10.00 to +5.00 D were recruited from the National University Hospital Eye Surgery outpatient clinic. After a comprehensive ocular examination, refraction, and axial length (AL) measurement (IOLMaster), macular GC-IPL and RNFL thickness values were obtained with a spectral domain Cirrus high definition optical coherence tomography system (Carl Zeiss Meditec Inc.). Only scans with signal strength of >6/10 were included. Correlation between variables was calculated using the Pearson correlation coefficient. A multivariate analysis using mixed models was done to adjust for confounders. The mean spherical equivalent refraction was -3.20±3.51 D and mean AL was 24.39±1.72 mm. Average, minimum, superior, and inferior GC-IPL were 82.59±6.29, 77.17±9.65, 83.68±6.96, and 81.64±6.70 μm, respectively. Average, superior, and inferior peripapillary RNFL were 99.00±11.45, 123.20±25.81, and 124.24±22.23 μm, respectively. Average, superior, and inferior GC-IPL were correlated with AL (β=-2.056, P-value 0.000; β=-2.383, P-value 0.000; β=-1.721, P-value 0.000), but minimum GC-IPL was not (β=-1.056, P-value 0.115). None of the RNFL parameters were correlated with AL. This study establishes normative macular GC-IPL and RNFL thickness in children with refractive errors. Our results suggest that high definition optical coherence tomography RNFL parameters and minimum GC-IPL are not affected by AL or myopia in children, and therefore warrants further evaluation in pediatric glaucoma patients.

Performance optimization of dense-array concentrator photovoltaic system considering effects of circumsolar radiation and slope error.

PubMed

Wong, Chee-Woon; Chong, Kok-Keong; Tan, Ming-Hui

2015-07-27

This paper presents an approach to optimize the electrical performance of dense-array concentrator photovoltaic system comprised of non-imaging dish concentrator by considering the circumsolar radiation and slope error effects. Based on the simulated flux distribution, a systematic methodology to optimize the layout configuration of solar cells interconnection circuit in dense array concentrator photovoltaic module has been proposed by minimizing the current mismatch caused by non-uniformity of concentrated sunlight. An optimized layout of interconnection solar cells circuit with minimum electrical power loss of 6.5% can be achieved by minimizing the effects of both circumsolar radiation and slope error.

New syndrome decoding techniques for the (n, k) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

Soft-decision decoding techniques for linear block codes and their error performance analysis

NASA Technical Reports Server (NTRS)

Lin, Shu

1996-01-01

The first paper presents a new minimum-weight trellis-based soft-decision iterative decoding algorithm for binary linear block codes. The second paper derives an upper bound on the probability of block error for multilevel concatenated codes (MLCC). The bound evaluates difference in performance for different decompositions of some codes. The third paper investigates the bit error probability code for maximum likelihood decoding of binary linear codes. The fourth and final paper included in this report is concerns itself with the construction of multilevel concatenated block modulation codes using a multilevel concatenation scheme for the frequency non-selective Rayleigh fading channel.

Wechsler Adult Intelligence Scale-Revised Block Design broken configuration errors in nonpenetrating traumatic brain injury.

PubMed

Wilde, M C; Boake, C; Sherer, M

2000-01-01

Final broken configuration errors on the Wechsler Adult Intelligence Scale-Revised (WAIS-R; Wechsler, 1981) Block Design subtest were examined in 50 moderate and severe nonpenetrating traumatically brain injured adults. Patients were divided into left (n = 15) and right hemisphere (n = 19) groups based on a history of unilateral craniotomy for treatment of an intracranial lesion and were compared to a group with diffuse or negative brain CT scan findings and no history of neurosurgery (n = 16). The percentage of final broken configuration errors was related to injury severity, Benton Visual Form Discrimination Test (VFD; Benton, Hamsher, Varney, & Spreen, 1983) total score and the number of VFD rotation and peripheral errors. The percentage of final broken configuration errors was higher in the patients with right craniotomies than in the left or no craniotomy groups, which did not differ. Broken configuration errors did not occur more frequently on designs without an embedded grid pattern. Right craniotomy patients did not show a greater percentage of broken configuration errors on nongrid designs as compared to grid designs.

Error-Monitoring in Response to Social Stimuli in Individuals with Higher-Functioning Autism Spectrum Disorder

PubMed Central

McMahon, Camilla M.; Henderson, Heather A.

2014-01-01

Error-monitoring, or the ability to recognize one's mistakes and implement behavioral changes to prevent further mistakes, may be impaired in individuals with Autism Spectrum Disorder (ASD). Children and adolescents (ages 9-19) with ASD (n = 42) and typical development (n = 42) completed two face processing tasks that required discrimination of either the gender or affect of standardized face stimuli. Post-error slowing and the difference in Error-Related Negativity amplitude between correct and incorrect responses (ERNdiff) were used to index error-monitoring ability. Overall, ERNdiff increased with age. On the Gender Task, individuals with ASD had a smaller ERNdiff than individuals with typical development; however, on the Affect Task, there were no significant diagnostic group differences on ERNdiff. Individuals with ASD may have ERN amplitudes similar to those observed in individuals with typical development in more social contexts compared to less social contexts due to greater consequences for errors, more effortful processing, and/or reduced processing efficiency in these contexts. Across all participants, more post-error slowing on the Affect Task was associated with better social cognitive skills. PMID:25066088

Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

PubMed

Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

2013-09-01

The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.

Optimization of traffic data collection for specific pavement design applications.

DOT National Transportation Integrated Search

2006-05-01

The objective of this study is to establish the minimum traffic data collection effort required for pavement design applications satisfying a maximum acceptable error under a prescribed confidence level. The approach consists of simulating the traffi...

Minimum probe length for unique identification of all open reading frames in a microbial genome

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

Sokhansanj, B A; Ng, J; Fitch, J P

2000-03-05

In this paper, we determine the minimum hybridization probe length to uniquely identify at least 95% of the open reading frame (ORF) in an organism. We analyze the whole genome sequences of 17 species, 11 bacteria, 4 archaea, and 2 eukaryotes. We also present a mathematical model for minimum probe length based on assuming that all ORFs are random, of constant length, and contain an equal distribution of bases. The model accurately predicts the minimum probe length for all species, but it incorrectly predicts that all ORFs may be uniquely identified. However, a probe length of just 9 bases ismore » adequate to identify over 95% of the ORFs for all 15 prokaryotic species we studied. Using a minimum probe length, while accepting that some ORFs may not be identified and that data will be lost due to hybridization error, may result in significant savings in microarray and oligonucleotide probe design.« less

Review of Research on Sight Word Instruction.

ERIC Educational Resources Information Center

Browder, Diane M.; Lalli, Joseph S.

1991-01-01

This review of 20 years of literature on sight word instruction for individuals with handicaps examines effectiveness data for procedures teaching word recognition and comprehension. Covered are "errorless procedures," prompt elimination, stimulus fading, time delay, easy to hard discrimination, and trial and error with feedback. Two tables…

Ability Self-Estimates and Self-Efficacy: Meaningfully Distinct?

ERIC Educational Resources Information Center

Bubany, Shawn T.; Hansen, Jo-Ida C.

2010-01-01

Conceptual differences between self-efficacy and ability self-estimate scores, used in vocational psychology and career counseling, were examined with confirmatory factor analysis, discriminate relations, and reliability analysis. Results suggest that empirical differences may be due to measurement error or scale content, rather than due to the…

Irradiation resistance of intravolume shading elements embedded in photomasks used for CD uniformity control by local intra-field transmission attenuation

NASA Astrophysics Data System (ADS)

Zait, Eitan; Ben-Zvi, Guy; Dmitriev, Vladimir; Oshemkov, Sergey; Pforr, Rainer; Hennig, Mario

2006-05-01

Intra-field CD variation is, besides OPC errors, a main contributor to the total CD variation budget in IC manufacturing. It is caused mainly by mask CD errors. In advanced memory device manufacturing the minimum features are close to the resolution limit resulting in large mask error enhancement factors hence large intra-field CD variations. Consequently tight CD Control (CDC) of the mask features is required, which results in increasing significantly the cost of mask and hence the litho process costs. Alternatively there is a search for such techniques (1) which will allow improving the intrafield CD control for a given moderate mask and scanner imaging performance. Currently a new technique (2) has been proposed which is based on correcting the printed CD by applying shading elements generated in the substrate bulk of the mask by ultrashort pulsed laser exposure. The blank transmittance across a feature is controlled by changing the density of light scattering pixels. The technique has been demonstrated to be very successful in correcting intra-field CD variations caused by the mask and the projection system (2). A key application criterion of this technique in device manufacturing is the stability of the absorbing pixels against DUV light irradiation being applied during mask projection in scanners. This paper describes the procedures and results of such an investigation. To do it with acceptable effort a special experimental setup has been chosen allowing an evaluation within reasonable time. A 193nm excimer laser with pulse duration of 25 ns has been used for blank irradiation. Accumulated dose equivalent to 100,000 300 mm wafer exposures has been applied to Half Tone PSM mask areas with and without CDC shadowing elements. This allows the discrimination of effects appearing in treated and untreated glass regions. Several intensities have been investigated to define an acceptable threshold intensity to avoid glass compaction or generation of color centers in the glass. The impact of the irradiation on the mask transmittance of both areas has been studied by measurements of the printed CD on wafer using a wafer scanner before and after DUV irradiation.

DNA barcode identification of Podocarpaceae--the second largest conifer family.

PubMed

Little, Damon P; Knopf, Patrick; Schulz, Christian

2013-01-01

We have generated matK, rbcL, and nrITS2 DNA barcodes for 320 specimens representing all 18 extant genera of the conifer family Podocarpaceae. The sample includes 145 of the 198 recognized species. Comparative analyses of sequence quality and species discrimination were conducted on the 159 individuals from which all three markers were recovered (representing 15 genera and 97 species). The vast majority of sequences were of high quality (B 30 = 0.596-0.989). Even the lowest quality sequences exceeded the minimum requirements of the BARCODE data standard. In the few instances that low quality sequences were generated, the responsible mechanism could not be discerned. There were no statistically significant differences in the discriminatory power of markers or marker combinations (p = 0.05). The discriminatory power of the barcode markers individually and in combination is low (56.7% of species at maximum). In some instances, species discrimination failed in spite of ostensibly useful variation being present (genotypes were shared among species), but in many cases there was simply an absence of sequence variation. Barcode gaps (maximum intraspecific p-distance > minimum interspecific p-distance) were observed in 50.5% of species when all three markers were considered simultaneously. The presence of a barcode gap was not predictive of discrimination success (p = 0.02) and there was no statistically significant difference in the frequency of barcode gaps among markers (p = 0.05). In addition, there was no correlation between number of individuals sampled per species and the presence of a barcode gap (p = 0.27).

Clinical Use of an Optical Coherence Tomography Linear Discriminant Function for Differentiating Glaucoma From Normal Eyes.

PubMed

Choi, Yun Jeong; Jeoung, Jin Wook; Park, Ki Ho; Kim, Dong Myung

2016-03-01

To determine and validate the diagnostic ability of a linear discriminant function (LDF) based on retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness obtained using high-definition optical coherence tomography (Cirrus HD-OCT) for discriminating between healthy controls and early glaucoma subjects. We prospectively selected 214 healthy controls and 152 glaucoma subjects (teaching set) and another independent sample of 86 healthy controls and 71 glaucoma subjects (validating set). Two scans, including 1 macular and 1 peripapillary RNFL scan, were obtained. After calculating the LDF in the teaching set using the binary logistic regression analysis, receiver operating characteristic curves were plotted and compared between the OCT-provided parameters and LDF in the validating set. The proposed LDF was 16.529-(0.132×superior RNFL)-(0.064×inferior RNFL)+(0.039×12 o'clock RNFL)+(0.038×1 o'clock RNFL)+(0.084×superior GCIPL)-(0.144×minimum GCIPL). The highest area under the receiver operating characteristic (AUROC) curve was obtained for LDF in both sets (AUROC=0.95 and 0.96). In the validating set, the LDF showed significantly higher AUROC than the best RNFL (inferior RNFL=0.91) and GCIPL parameter (minimum GCIPL=0.88). The LDF yielded a sensitivity of 93.0% at a fixed specificity of 85.0%. The LDF showed better diagnostic ability for differentiating between healthy and early glaucoma subjects than individual OCT parameters. A classification algorithm based on the LDF can be used in the OCT analysis for glaucoma diagnosis.

DNA Barcode Identification of Podocarpaceae—The Second Largest Conifer Family

PubMed Central

Little, Damon P.; Knopf, Patrick; Schulz, Christian

2013-01-01

We have generated matK, rbcL, and nrITS2 DNA barcodes for 320 specimens representing all 18 extant genera of the conifer family Podocarpaceae. The sample includes 145 of the 198 recognized species. Comparative analyses of sequence quality and species discrimination were conducted on the 159 individuals from which all three markers were recovered (representing 15 genera and 97 species). The vast majority of sequences were of high quality (B 30 = 0.596–0.989). Even the lowest quality sequences exceeded the minimum requirements of the BARCODE data standard. In the few instances that low quality sequences were generated, the responsible mechanism could not be discerned. There were no statistically significant differences in the discriminatory power of markers or marker combinations (p = 0.05). The discriminatory power of the barcode markers individually and in combination is low (56.7% of species at maximum). In some instances, species discrimination failed in spite of ostensibly useful variation being present (genotypes were shared among species), but in many cases there was simply an absence of sequence variation. Barcode gaps (maximum intraspecific p–distance > minimum interspecific p–distance) were observed in 50.5% of species when all three markers were considered simultaneously. The presence of a barcode gap was not predictive of discrimination success (p = 0.02) and there was no statistically significant difference in the frequency of barcode gaps among markers (p = 0.05). In addition, there was no correlation between number of individuals sampled per species and the presence of a barcode gap (p = 0.27). PMID:24312258

Sexing California Clapper Rails using morphological measurements

USGS Publications Warehouse

Overton, Cory T.; Casazza, Michael L.; Takekawa, John Y.; Rohmer, Tobias M.

2009-01-01

California Clapper Rails (Rallus longirostris obsoletus) have monomorphic plumage, a trait that makes identification of sex difficult without extensive behavioral observation or genetic testing. Using 31 Clapper Rails (22 females, 9 males), caught in south San Francisco Bay, CA, and using easily measurable morphological characteristics, we developed a discriminant function to distinguish sex. We then validated this function on 33 additional rails. Seven morphological measurements were considered, resulting in three which were selected in the discriminate function: culmen length, tarsometatarsus length, and flat wing length. We had no classification errors for the development or testing datasets either with resubstitution or cross-validation procedures. Male California Clapper Rails were 6-22% larger than females for individual morphological traits, and the largest difference was in body mass.  Variables in our discriminant function closely match variables developed for sexing Clapper Rails of Gulf Coast populations. However, a universal discriminant function to sex all Clapper Rail subspecies is not likely because of large and inconsistent differences in morphological traits among subspecies. 

Orientation perception in Williams Syndrome: discrimination and integration

PubMed Central

Palomares, Melanie; Landau, Barbara; Egeth, Howard

2009-01-01

Williams Syndrome (WS) is a rare neurodevelopmental disorder, which stems from a genetic deletion on chromosome 7 that causes a profound weakness in visuospatial cognition. Our current study explores how orientation perception may contribute to the visuospatial deficits in WS. In Experiment 1, we found that WS individuals and normal 3-4 year olds had similar orientation discrimination thresholds and had similar prevalence of mirror-reversal errors for diagonal targets (±45 deg). In Experiment 2, we asked whether this immaturity in orientation discrimination would also be reflected in a task requiring integration of oriented elements. We found that sensitivities of WS individuals for detecting orientation-defined contours were higher than sensitivities of normal 3-4 year olds, and were not significantly different from sensitivities of normal adults. Together, these results suggest that orientation discrimination and orientation integration have different maturational trajectories in normal development and different susceptibilities to damage in WS, which may reflect largely separate visuospatial mechanisms. PMID:19231058

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

On higher order discrete phase-locked loops.

NASA Technical Reports Server (NTRS)

Gill, G. S.; Gupta, S. C.

1972-01-01

An exact mathematical model is developed for a discrete loop of a general order particularly suitable for digital computation. The deterministic response of the loop to the phase step and the frequency step is investigated. The design of the digital filter for the second-order loop is considered. Use is made of the incremental phase plane to study the phase error behavior of the loop. The model of the noisy loop is derived and the optimization of the loop filter for minimum mean-square error is considered.

A high speed sequential decoder

NASA Technical Reports Server (NTRS)

Lum, H., Jr.

1972-01-01

The performance and theory of operation for the High Speed Hard Decision Sequential Decoder are delineated. The decoder is a forward error correction system which is capable of accepting data from binary-phase-shift-keyed and quadriphase-shift-keyed modems at input data rates up to 30 megabits per second. Test results show that the decoder is capable of maintaining a composite error rate of 0.00001 at an input E sub b/N sub o of 5.6 db. This performance has been obtained with minimum circuit complexity.

Propagation of stage measurement uncertainties to streamflow time series

NASA Astrophysics Data System (ADS)

Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary

2016-04-01

Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

Head repositioning accuracy to neutral: a comparative study of error calculation.

PubMed

Hill, Robert; Jensen, Pål; Baardsen, Tor; Kulvik, Kristian; Jull, Gwendolen; Treleaven, Julia

2009-02-01

Deficits in cervical proprioception have been identified in subjects with neck pain through the measure of head repositioning accuracy (HRA). Nevertheless there appears to be no general consensus regarding the construct of measurement of error used for calculating HRA. This study investigated four different mathematical methods of measurement of error to determine if there were any differences in their ability to discriminate between a control group and subjects with a whiplash associated disorder. The four methods for measuring cervical joint position error were calculated using a previous data set consisting of 50 subjects with whiplash complaining of dizziness (WAD D), 50 subjects with whiplash not complaining of dizziness (WAD ND) and 50 control subjects. The results indicated that no one measure of HRA uniquely detected or defined the differences between the whiplash and control groups. Constant error (CE) was significantly different between the whiplash and control groups from extension (p<0.05). Absolute errors (AEs) and root mean square errors (RMSEs) demonstrated differences between the two WAD groups in rotation trials (p<0.05). No differences were seen with variable error (VE). The results suggest that a combination of AE (or RMSE) and CE are probably the most suitable measures for analysis of HRA.

Reduced chromatic discrimination in children with autism spectrum disorders.

PubMed

Franklin, Anna; Sowden, Paul; Notman, Leslie; Gonzalez-Dixon, Melissa; West, Dorotea; Alexander, Iona; Loveday, Stephen; White, Alex

2010-01-01

Atypical perception in Autism Spectrum Disorders (ASD) is well documented (Dakin & Frith, 2005). However, relatively little is known about colour perception in ASD. Less accurate performance on certain colour tasks has led some to argue that chromatic discrimination is reduced in ASD relative to typical development (Franklin, Sowden, Burley, Notman & Alder, 2008). The current investigation assessed chromatic discrimination in children with high-functioning autism (HFA) and typically developing (TD) children matched on age and non-verbal cognitive ability, using the Farnsworth-Munsell 100 hue test (Experiment 1) and a threshold discrimination task (Experiment 2). In Experiment 1, more errors on the chromatic discrimination task were made by the HFA than the TD group. Comparison with test norms revealed that performance for the HFA group was at a similar level to typically developing children around 3 years younger. In Experiment 2, chromatic thresholds were elevated for the HFA group relative to the TD group. For both experiments, reduced chromatic discrimination in ASD was due to a general reduction in chromatic sensitivity rather than a specific difficulty with either red-green or blue-yellow subsystems of colour vision. The absence of group differences on control tasks ruled out an explanation in terms of general task ability rather than chromatic sensitivity. Theories to account for the reduction in chromatic discrimination in HFA are discussed, and findings are related to cortical models of perceptual processing in ASD.

Recent Studies of the Behavior of the Sun's White-Light Corona Over Time

NASA Technical Reports Server (NTRS)

SaintCyr, O. C.; Young, D. E.; Pesnell, W. D.; Lecinski, A.; Eddy, J.

2008-01-01

Predictions of upcoming solar cycles are often related to the nature and dynamics of the Sun's polar magnetic field and its influence on the corona. For the past 30 years we have a more-or-less continuous record of the Sun's white-light corona from groundbased and spacebased coronagraphs. Over that interval, the large scale features of the corona have varied in what we now consider a 'predictable' fashion--complex, showing multiple streamers at all latitudes during solar activity maximum; and a simple dipolar shape aligned with the rotational pole during solar minimum. Over the past three decades the white-light corona appears to be a better indicator of 'true' solar minimum than sunspot number since sunspots disappear for months (even years) at solar minimum. Since almost all predictions of the timing of the next solar maximum depend on the timing of solar minimum, the white-light corona is a potentially important observational discriminator for future predictors. In this contribution we describe recent work quantifying the large-scale appearance of the Sun's corona to correlate it with the sunspot record, especially around solar minimum. These three decades can be expanded with the HAO archive of eclipse photographs which, although sparse compared to the coronagraphic coverage, extends back to 1869. A more extensive understanding of this proxy would give researchers confidence in using the white-light corona as an indicator of solar minimum conditions.

Multiple-copy state discrimination: Thinking globally, acting locally

NASA Astrophysics Data System (ADS)

Higgins, B. L.; Doherty, A. C.; Bartlett, S. D.; Pryde, G. J.; Wiseman, H. M.

2011-05-01

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies N, and in the asymptotic limit as N→∞. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements, and globally optimal adaptive local measurements. Here an adaptive measurement is one in which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite N) and the scaling of this error in the asymptotic limit. In the asymptotic limit, it is known analytically (and we verify numerically) that adaptive schemes have no advantage over the optimal fixed local scheme. Here we show moreover that, in this limit, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme except for states with less than 2% mixture. For finite N, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme for any degree of mixture.

Multiple-copy state discrimination: Thinking globally, acting locally

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

Higgins, B. L.; Pryde, G. J.; Wiseman, H. M.

2011-05-15

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies N, and in the asymptotic limit as N{yields}{infinity}. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements,more » and globally optimal adaptive local measurements. Here an adaptive measurement is one in which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite N) and the scaling of this error in the asymptotic limit. In the asymptotic limit, it is known analytically (and we verify numerically) that adaptive schemes have no advantage over the optimal fixed local scheme. Here we show moreover that, in this limit, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme except for states with less than 2% mixture. For finite N, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme for any degree of mixture.« less

Single trial detection of hand poses in human ECoG using CSP based feature extraction.

PubMed

Kapeller, C; Schneider, C; Kamada, K; Ogawa, H; Kunii, N; Ortner, R; Pruckl, R; Guger, C

2014-01-01

Decoding brain activity of corresponding highlevel tasks may lead to an independent and intuitively controlled Brain-Computer Interface (BCI). Most of today's BCI research focuses on analyzing the electroencephalogram (EEG) which provides only limited spatial and temporal resolution. Derived electrocorticographic (ECoG) signals allow the investigation of spatially highly focused task-related activation within the high-gamma frequency band, making the discrimination of individual finger movements or complex grasping tasks possible. Common spatial patterns (CSP) are commonly used for BCI systems and provide a powerful tool for feature optimization and dimensionality reduction. This work focused on the discrimination of (i) three complex hand movements, as well as (ii) hand movement and idle state. Two subjects S1 and S2 performed single `open', `peace' and `fist' hand poses in multiple trials. Signals in the high-gamma frequency range between 100 and 500 Hz were spatially filtered based on a CSP algorithm for (i) and (ii). Additionally, a manual feature selection approach was tested for (i). A multi-class linear discriminant analysis (LDA) showed for (i) an error rate of 13.89 % / 7.22 % and 18.42 % / 1.17 % for S1 and S2 using manually / CSP selected features, where for (ii) a two class LDA lead to a classification error of 13.39 % and 2.33 % for S1 and S2, respectively.

Procedures for Testing Color Vision,

DTIC Science & Technology

1981-01-01

Chromatic Discriminative Ability, 8 Congenital Sex-Linked Color Vision Defects, 8 Anomalous Trichromats, 9 Dichromats, 10 Autosomal Dominant Tritan Defect...anomalous trichromats (see Chapter 3). AUTOSOMAL DOMINANT TRITAN DEFECT In addition to the X-chromosomal-linked color defects, there are some very rare... hereditary color defects. The tritan defect is one of these rare defects (minimum frequency estimated to be between 1/13,000 and 1/65,000 [Kalmus

Restaurant noise, hearing loss, and hearing aids.

PubMed Central

Lebo, C P; Smith, M F; Mosher, E R; Jelonek, S J; Schwind, D R; Decker, K E; Krusemark, H J; Kurz, P L

1994-01-01

Our multidisciplinary team obtained noise data in 27 San Francisco Bay Area restaurants. These data included typical minimum, peak, and average sound pressure levels; digital tape recordings; subjective noise ratings; and on-site unaided and aided speech discrimination tests. We report the details and implications of these noise measurements and provide basic information on selecting hearing aids and suggestions for coping with restaurant noise. Images PMID:7941506

Comparison of three PCR-based assays for SNP genotyping in sugar beet

USDA-ARS?s Scientific Manuscript database

Background: PCR allelic discrimination technologies have broad applications in the detection of single nucleotide polymorphisms (SNPs) in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeted SNP detection, but assay costs and error rates could be improved t...

Stimulus Equalization: Temporary Reduction of Stimulus Complexity to Facilitate Discrimination Learning.

ERIC Educational Resources Information Center

Hoko, J. Aaron; LeBlanc, Judith M.

1988-01-01

Because disabled learners may profit from procedures using gradual stimulus change, this study utilized a microcomputer to investigate the effectiveness of stimulus equalization, an error reduction procedure involving an abrupt but temporary reduction of dimensional complexity. The procedure was found to be generally effective and implications for…

Features and Feedback: Enhancing Metamnemonic Knowledge at Retrieval Reduces Source-Monitoring Errors

ERIC Educational Resources Information Center

Lane, Sean M.; Roussel, Cristine C.; Villa, Diane; Morita, Shelby K.

2007-01-01

Three experiments explored the issue of whether enhanced metamnemonic knowledge at retrieval can improve participants' ability to make difficult source discriminations in the context of the eyewitness suggestibility paradigm. The 1st experiment documented differences in phenomenal experience between veridical and false memories. Experiment 2…

VizieR Online Data Catalog: V and R CCD photometry of visual binaries (Abad+, 2004)

NASA Astrophysics Data System (ADS)

Abad, C.; Docobo, J. A.; Lanchares, V.; Lahulla, J. F.; Abelleira, P.; Blanco, J.; Alvarez, C.

2003-11-01

Table 1 gives relevant data for the visual binaries observed. Observations were carried out over a short period of time, therefore we assign the mean epoch (1998.58) for the totality of data. Data of individual stars are presented as average data with errors, by parameter, when various observations have been calculated, as well as the number of observations involved. Errors corresponding to astrometric relative positions between components are always present. For single observations, parameter fitting errors, specially for dx and dy parameters, have been calculated analysing the chi2 test around the minimum. Following the rules for error propagation, theta and rho errors can be estimated. Then, Table 1 shows single observation errors with an additional significant digit. When a star does not have known references, we include it in Table 2, where J2000 position and magnitudes are from the USNO-A2.0 catalogue (Monet et al., 1998, Cat. ). (2 data files).