A Laboratory Course for Teaching Laboratory Techniques, Experimental Design, Statistical Analysis, and Peer Review Process to Undergraduate Science Students

ERIC Educational Resources Information Center

Gliddon, C. M.; Rosengren, R. J.

2012-01-01

This article describes a 13-week laboratory course called Human Toxicology taught at the University of Otago, New Zealand. This course used a guided inquiry based laboratory coupled with formative assessment and collaborative learning to develop in undergraduate students the skills of problem solving/critical thinking, data interpretation and…

Statistical physics of vehicular traffic and some related systems

NASA Astrophysics Data System (ADS)

Chowdhury, Debashish; Santen, Ludger; Schadschneider, Andreas

2000-05-01

In the so-called “microscopic” models of vehicular traffic, attention is paid explicitly to each individual vehicle each of which is represented by a “particle”; the nature of the “interactions” among these particles is determined by the way the vehicles influence each others’ movement. Therefore, vehicular traffic, modeled as a system of interacting “particles” driven far from equilibrium, offers the possibility to study various fundamental aspects of truly nonequilibrium systems which are of current interest in statistical physics. Analytical as well as numerical techniques of statistical physics are being used to study these models to understand rich variety of physical phenomena exhibited by vehicular traffic. Some of these phenomena, observed in vehicular traffic under different circumstances, include transitions from one dynamical phase to another, criticality and self-organized criticality, metastability and hysteresis, phase-segregation, etc. In this critical review, written from the perspective of statistical physics, we explain the guiding principles behind all the main theoretical approaches. But we present detailed discussions on the results obtained mainly from the so-called “particle-hopping” models, particularly emphasizing those which have been formulated in recent years using the language of cellular automata.

METEOR - an artificial intelligence system for convective storm forecasting

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

Elio, R.; De haan, J.; Strong, G.S.

1987-03-01

An AI system called METEOR, which uses the meteorologist's heuristics, strategies, and statistical tools to forecast severe hailstorms in Alberta, is described, emphasizing the information and knowledge that METEOR uses to mimic the forecasting procedure of an expert meteorologist. METEOR is then discussed as an AI system, emphasizing the ways in which it is qualitatively different from algorithmic or statistical approaches to prediction. Some features of METEOR's design and the AI techniques for representing meteorological knowledge and for reasoning and inference are presented. Finally, some observations on designing and implementing intelligent consultants for meteorological applications are made. 7 references.

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Chroma intra prediction based on inter-channel correlation for HEVC.

PubMed

Zhang, Xingyu; Gisquet, Christophe; François, Edouard; Zou, Feng; Au, Oscar C

2014-01-01

In this paper, we investigate a new inter-channel coding mode called LM mode proposed for the next generation video coding standard called high efficiency video coding. This mode exploits inter-channel correlation using reconstructed luma to predict chroma linearly with parameters derived from neighboring reconstructed luma and chroma pixels at both encoder and decoder to avoid overhead signaling. In this paper, we analyze the LM mode and prove that the LM parameters for predicting original chroma and reconstructed chroma are statistically the same. We also analyze the error sensitivity of the LM parameters. We identify some LM mode problematic situations and propose three novel LM-like modes called LMA, LML, and LMO to address the situations. To limit the increase in complexity due to the LM-like modes, we propose some fast algorithms with the help of some new cost functions. We further identify some potentially-problematic conditions in the parameter estimation (including regression dilution problem) and introduce a novel model correction technique to detect and correct those conditions. Simulation results suggest that considerable BD-rate reduction can be achieved by the proposed LM-like modes and model correction technique. In addition, the performance gain of the two techniques appears to be essentially additive when combined.

Multiple signal classification algorithm for super-resolution fluorescence microscopy

PubMed Central

Agarwal, Krishna; Macháň, Radek

2016-01-01

Single-molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. Here we propose a statistical super-resolution technique of wide-field fluorescence microscopy we call the multiple signal classification algorithm which has several advantages. It provides resolution down to at least 50 nm, requires fewer frames and lower excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the timescale of the recording. The multiple signal classification algorithm shows comparable or better performance in comparison with single-molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in vitro actin filaments and other independently acquired experimental data sets. We also demonstrate super-resolution at timescales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers. PMID:27934858

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

Social Communication and Vocal Recognition in Free-Ranging Rhesus Monkeys

NASA Astrophysics Data System (ADS)

Rendall, Christopher Andrew

Kinship and individual identity are key determinants of primate sociality, and the capacity for vocal recognition of individuals and kin is hypothesized to be an important adaptation facilitating intra-group social communication. Research was conducted on adult female rhesus monkeys on Cayo Santiago, Puerto Rico to test this hypothesis for three acoustically distinct calls characterized by varying selective pressures on communicating identity: coos (contact calls), grunts (close range social calls), and noisy screams (agonistic recruitment calls). Vocalization playback experiments confirmed a capacity for both individual and kin recognition of coos, but not screams (grunts were not tested). Acoustic analyses, using traditional spectrographic methods as well as linear predictive coding techniques, indicated that coos (but not grunts or screams) were highly distinctive, and that the effects of vocal tract filtering--formants --contributed more to statistical discriminations of both individuals and kin groups than did temporal or laryngeal source features. Formants were identified from very short (23 ms.) segments of coos and were stable within calls, indicating that formant cues to individual and kin identity were available throughout a call. This aspect of formant cues is predicted to be an especially important design feature for signaling identity efficiently in complex acoustic environments. Results of playback experiments involving manipulated coo stimuli provided preliminary perceptual support for the statistical inference that formant cues take precedence in facilitating vocal recognition. The similarity of formants among female kin suggested a mechanism for the development of matrilineal vocal signatures from the genetic and environmental determinants of vocal tract morphology shared among relatives. The fact that screams --calls strongly expected to communicate identity--were not individually distinctive nor recognized suggested the possibility that their acoustic structure and role in signaling identity might be constrained by functional or morphological design requirements associated with their role in signaling submission.

A comparative analysis of the statistical properties of large mobile phone calling networks.

PubMed

Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

2014-05-30

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

NASA Astrophysics Data System (ADS)

Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

2010-10-01

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

Statistical Process Control Techniques for the Telecommunications Systems Manager

DTIC Science & Technology

1992-03-01

products that are out of 59 tolerance and bad designs. The third type of defect, mistakes, are remedied by Poka - Yoke methods that are 1 introduced later...based on total production costs plus quality costs. Once production is underway, interventions are determined by their impact on the QLF. F. POKA - YOKE ...Mistakes require process improvements called Poka Yoke or mistake proofing. Shiego Shingo developed Poka Yoke methods to incorporate 100% inspection at

Site specific passive acoustic detection and densities of humpback whale calls off the coast of California

NASA Astrophysics Data System (ADS)

Helble, Tyler Adam

Passive acoustic monitoring of marine mammal calls is an increasingly important method for assessing population numbers, distribution, and behavior. Automated methods are needed to aid in the analyses of the recorded data. When a mammal vocalizes in the marine environment, the received signal is a filtered version of the original waveform emitted by the marine mammal. The waveform is reduced in amplitude and distorted due to propagation effects that are influenced by the bathymetry and environment. It is important to account for these effects to determine a site-specific probability of detection for marine mammal calls in a given study area. A knowledge of that probability function over a range of environmental and ocean noise conditions allows vocalization statistics from recordings of single, fixed, omnidirectional sensors to be compared across sensors and at the same sensor over time with less bias and uncertainty in the results than direct comparison of the raw statistics. This dissertation focuses on both the development of new tools needed to automatically detect humpback whale vocalizations from single-fixed omnidirectional sensors as well as the determination of the site-specific probability of detection for monitoring sites off the coast of California. Using these tools, detected humpback calls are "calibrated" for environmental properties using the site-specific probability of detection values, and presented as call densities (calls per square kilometer per time). A two-year monitoring effort using these calibrated call densities reveals important biological and ecological information on migrating humpback whales off the coast of California. Call density trends are compared between the monitoring sites and at the same monitoring site over time. Call densities also are compared to several natural and human-influenced variables including season, time of day, lunar illumination, and ocean noise. The results reveal substantial differences in call densities between the two sites which were not noticeable using uncorrected (raw) call counts. Additionally, a Lombard effect was observed for humpback whale vocalizations in response to increasing ocean noise. The results presented in this thesis develop techniques to accurately measure marine mammal abundances from passive acoustic sensors.

X-ray ‘ghost images’ could cut radiation doses

NASA Astrophysics Data System (ADS)

Chen, Sophia

2018-03-01

On its own, a single-pixel camera captures pictures that are pretty dull: squares that are completely black, completely white, or some shade of gray in between. All it does, after all, is detect brightness. Yet by connecting a single-pixel camera to a patterned light source, a team of physicists in China has made detailed x-ray images using a statistical technique called ghost imaging, first pioneered 20 years ago in infrared and visible light. Researchers in the field say future versions of this system could take clear x-ray photographs with cheap cameras—no need for lenses and multipixel detectors—and less cancer-causing radiation than conventional techniques.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods.

PubMed

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J Sunil

2014-08-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called "Patient Recursive Survival Peeling" is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called "combined" cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called “Patient Recursive Survival Peeling” is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called “combined” cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication. PMID:26997922

Spectrophotometric methods for simultaneous determination of betamethasone valerate and fusidic acid in their binary mixture.

PubMed

Lotfy, Hayam Mahmoud; Salem, Hesham; Abdelkawy, Mohammad; Samir, Ahmed

2015-04-05

Five spectrophotometric methods were successfully developed and validated for the determination of betamethasone valerate and fusidic acid in their binary mixture. Those methods are isoabsorptive point method combined with the first derivative (ISO Point--D1) and the recently developed and well established methods namely ratio difference (RD) and constant center coupled with spectrum subtraction (CC) methods, in addition to derivative ratio (1DD) and mean centering of ratio spectra (MCR). New enrichment technique called spectrum addition technique was used instead of traditional spiking technique. The proposed spectrophotometric procedures do not require any separation steps. Accuracy, precision and linearity ranges of the proposed methods were determined and the specificity was assessed by analyzing synthetic mixtures of both drugs. They were applied to their pharmaceutical formulation and the results obtained were statistically compared to that of official methods. The statistical comparison showed that there is no significant difference between the proposed methods and the official ones regarding both accuracy and precision. Copyright © 2015 Elsevier B.V. All rights reserved.

Statistics based sampling for controller and estimator design

NASA Astrophysics Data System (ADS)

Tenne, Dirk

The purpose of this research is the development of statistical design tools for robust feed-forward/feedback controllers and nonlinear estimators. This dissertation is threefold and addresses the aforementioned topics nonlinear estimation, target tracking and robust control. To develop statistically robust controllers and nonlinear estimation algorithms, research has been performed to extend existing techniques, which propagate the statistics of the state, to achieve higher order accuracy. The so-called unscented transformation has been extended to capture higher order moments. Furthermore, higher order moment update algorithms based on a truncated power series have been developed. The proposed techniques are tested on various benchmark examples. Furthermore, the unscented transformation has been utilized to develop a three dimensional geometrically constrained target tracker. The proposed planar circular prediction algorithm has been developed in a local coordinate framework, which is amenable to extension of the tracking algorithm to three dimensional space. This tracker combines the predictions of a circular prediction algorithm and a constant velocity filter by utilizing the Covariance Intersection. This combined prediction can be updated with the subsequent measurement using a linear estimator. The proposed technique is illustrated on a 3D benchmark trajectory, which includes coordinated turns and straight line maneuvers. The third part of this dissertation addresses the design of controller which include knowledge of parametric uncertainties and their distributions. The parameter distributions are approximated by a finite set of points which are calculated by the unscented transformation. This set of points is used to design robust controllers which minimize a statistical performance of the plant over the domain of uncertainty consisting of a combination of the mean and variance. The proposed technique is illustrated on three benchmark problems. The first relates to the design of prefilters for a linear and nonlinear spring-mass-dashpot system and the second applies a feedback controller to a hovering helicopter. Lastly, the statistical robust controller design is devoted to a concurrent feed-forward/feedback controller structure for a high-speed low tension tape drive.

Ontogenetic variation of heritability and maternal effects in yellow-bellied marmot alarm calls.

PubMed

Blumstein, Daniel T; Nguyen, Kathy T; Martin, Julien G A

2013-05-07

Individuals of many species produce distinctive vocalizations that may relay potential information about the signaller. The alarm calls of some species have been reported to be individually specific, and this distinctiveness may allow individuals to access the reliability or kinship of callers. While not much is known generally about the heritability of mammalian vocalizations, if alarm calls were individually distinctive to permit kinship assessment, then call structure should be heritable. Here, we show conclusively for the first time that alarm call structure is heritable. We studied yellow-bellied marmots (Marmota flaviventris) and made nine quantitative measurements of their alarm calls. With a known genealogy, we used the animal model (a statistical technique) to estimate alarm call heritability. In juveniles, only one of the measured variables had heritability significantly different from zero; however, most variables had significant maternal environmental effects. By contrast, yearlings and adults had no significant maternal environmental effects, but the heritability of nearly all measured variables was significantly different from zero. Some, but not all of these heritable effects were significantly different across age classes. The presence of significantly non-zero maternal environmental effects in juveniles could reflect the impact of maternal environmental stresses on call structure. Regardless of this mechanism, maternal environmental effects could permit kinship recognition in juveniles. In older animals, the substantial genetic basis of alarm call structure suggests that calls could be used to assess kinship and, paradoxically, might also suggest a role of learning in call structure.

Ontogenetic variation of heritability and maternal effects in yellow-bellied marmot alarm calls

PubMed Central

Blumstein, Daniel T.; Nguyen, Kathy T.; Martin, Julien G. A.

2013-01-01

Individuals of many species produce distinctive vocalizations that may relay potential information about the signaller. The alarm calls of some species have been reported to be individually specific, and this distinctiveness may allow individuals to access the reliability or kinship of callers. While not much is known generally about the heritability of mammalian vocalizations, if alarm calls were individually distinctive to permit kinship assessment, then call structure should be heritable. Here, we show conclusively for the first time that alarm call structure is heritable. We studied yellow-bellied marmots (Marmota flaviventris) and made nine quantitative measurements of their alarm calls. With a known genealogy, we used the animal model (a statistical technique) to estimate alarm call heritability. In juveniles, only one of the measured variables had heritability significantly different from zero; however, most variables had significant maternal environmental effects. By contrast, yearlings and adults had no significant maternal environmental effects, but the heritability of nearly all measured variables was significantly different from zero. Some, but not all of these heritable effects were significantly different across age classes. The presence of significantly non-zero maternal environmental effects in juveniles could reflect the impact of maternal environmental stresses on call structure. Regardless of this mechanism, maternal environmental effects could permit kinship recognition in juveniles. In older animals, the substantial genetic basis of alarm call structure suggests that calls could be used to assess kinship and, paradoxically, might also suggest a role of learning in call structure. PMID:23466987

Inverse statistical physics of protein sequences: a key issues review.

PubMed

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

Inverse statistical physics of protein sequences: a key issues review

NASA Astrophysics Data System (ADS)

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

Development of the One-Sided Nonlinear Adaptive Doppler Shift Estimation

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.; Singh, Upendra N.; Kavaya, Michael J.; Serror, Judith A.

2009-01-01

The new development of a one-sided nonlinear adaptive shift estimation technique (NADSET) is introduced. The background of the algorithm and a brief overview of NADSET are presented. The new technique is applied to the wind parameter estimates from a 2-micron wavelength coherent Doppler lidar system called VALIDAR located in NASA Langley Research Center in Virginia. The new technique enhances wind parameters such as Doppler shift and power estimates in low Signal-To-Noise-Ratio (SNR) regimes using the estimates in high SNR regimes as the algorithm scans the range bins from low to high altitude. The original NADSET utilizes the statistics in both the lower and the higher range bins to refine the wind parameter estimates in between. The results of the two different approaches of NADSET are compared.

On statistical inference in time series analysis of the evolution of road safety.

PubMed

Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

2013-11-01

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dictionary-learning-based reconstruction method for electron tomography.

PubMed

Liu, Baodong; Yu, Hengyong; Verbridge, Scott S; Sun, Lizhi; Wang, Ge

2014-01-01

Electron tomography usually suffers from so-called “missing wedge” artifacts caused by limited tilt angle range. An equally sloped tomography (EST) acquisition scheme (which should be called the linogram sampling scheme) was recently applied to achieve 2.4-angstrom resolution. On the other hand, a compressive sensing inspired reconstruction algorithm, known as adaptive dictionary based statistical iterative reconstruction (ADSIR), has been reported for X-ray computed tomography. In this paper, we evaluate the EST, ADSIR, and an ordered-subset simultaneous algebraic reconstruction technique (OS-SART), and compare the ES and equally angled (EA) data acquisition modes. Our results show that OS-SART is comparable to EST, and the ADSIR outperforms EST and OS-SART. Furthermore, the equally sloped projection data acquisition mode has no advantage over the conventional equally angled mode in this context.

Northeast regional and state trends in anuran occupancy from calling survey data (2001-2011) from the North American Amphibian Monitoring Program

USGS Publications Warehouse

Weir, Linda A.; Royle, Andy; Gazenski, Kimberly D.; Villena Carpio, Oswaldo

2014-01-01

We present the first regional trends in anuran occupancy from North American Amphibian Monitoring Program (NAAMP) data from 11 northeastern states using an 11 years of data. NAAMP is a long-term monitoring program where observers collect data at assigned random roadside routes using a calling survey technique. We assessed occupancy trends for 17 species. Eight species had statistically significant regional trends, of these seven were negative (Anaxyrus fowleri, Acris crepitans, Pseudacris brachyphona, Pseudacris feriarum-kalmi complex, Lithobates palustris, Lithobates pipiens, and Lithobates sphenocephalus) and one was positive (Hyla versicolor-chrysoscelis complex). We also assessed state level trends for 101 species/state combinations, of these 29 showed a significant decline and nine showed a significant increase in occupancy.

STATISTICS OF THE VELOCITY GRADIENT TENSOR IN SPACE PLASMA TURBULENT FLOWS

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

Consolini, Giuseppe; Marcucci, Maria Federica; Pallocchia, Giuseppe

2015-10-10

In the last decade, significant advances have been presented for the theoretical characterization and experimental techniques used to measure and model all of the components of the velocity gradient tensor in the framework of fluid turbulence. Here, we attempt the evaluation of the small-scale velocity gradient tensor for a case study of space plasma turbulence, observed in the Earth's magnetosheath region by the CLUSTER mission. In detail, we investigate the joint statistics P(R, Q) of the velocity gradient geometric invariants R and Q, and find that this P(R, Q) is similar to that of the low end of the inertialmore » range for fluid turbulence, with a pronounced increase in the statistics along the so-called Vieillefosse tail. In the context of hydrodynamics, this result is referred to as the dissipation/dissipation-production due to vortex stretching.« less

Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

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

Ahmadi, Rouhollah, E-mail: rouhollahahmadi@yahoo.com; Khamehchi, Ehsan

Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks andmore » fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.« less

Automatic generation of efficient orderings of events for scheduling applications

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1994-01-01

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

PubMed

Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

The scale invariant generator technique for quantifying anisotropic scale invariance

NASA Astrophysics Data System (ADS)

Lewis, G. M.; Lovejoy, S.; Schertzer, D.; Pecknold, S.

1999-11-01

Scale invariance is rapidly becoming a new paradigm for geophysics. However, little attention has been paid to the anisotropy that is invariably present in geophysical fields in the form of differential stratification and rotation, texture and morphology. In order to account for scaling anisotropy, the formalism of generalized scale invariance (GSI) was developed. Until now there has existed only a single fairly ad hoc GSI analysis technique valid for studying differential rotation. In this paper, we use a two-dimensional representation of the linear approximation to generalized scale invariance, to obtain a much improved technique for quantifying anisotropic scale invariance called the scale invariant generator technique (SIG). The accuracy of the technique is tested using anisotropic multifractal simulations and error estimates are provided for the geophysically relevant range of parameters. It is found that the technique yields reasonable estimates for simulations with a diversity of anisotropic and statistical characteristics. The scale invariant generator technique can profitably be applied to the scale invariant study of vertical/horizontal and space/time cross-sections of geophysical fields as well as to the study of the texture/morphology of fields.

Statistical characterization of short wind waves from stereo images of the sea surface

NASA Astrophysics Data System (ADS)

Mironov, Alexey; Yurovskaya, Maria; Dulov, Vladimir; Hauser, Danièle; Guérin, Charles-Antoine

2013-04-01

We propose a methodology to extract short-scale statistical characteristics of the sea surface topography by means of stereo image reconstruction. The possibilities and limitations of the technique are discussed and tested on a data set acquired from an oceanographic platform at the Black Sea. The analysis shows that reconstruction of the topography based on stereo method is an efficient way to derive non-trivial statistical properties of surface short- and intermediate-waves (say from 1 centimer to 1 meter). Most technical issues pertaining to this type of datasets (limited range of scales, lacunarity of data or irregular sampling) can be partially overcome by appropriate processing of the available points. The proposed technique also allows one to avoid linear interpolation which dramatically corrupts properties of retrieved surfaces. The processing technique imposes that the field of elevation be polynomially detrended, which has the effect of filtering out the large scales. Hence the statistical analysis can only address the small-scale components of the sea surface. The precise cut-off wavelength, which is approximatively half the patch size, can be obtained by applying a high-pass frequency filter on the reference gauge time records. The results obtained for the one- and two-points statistics of small-scale elevations are shown consistent, at least in order of magnitude, with the corresponding gauge measurements as well as other experimental measurements available in the literature. The calculation of the structure functions provides a powerful tool to investigate spectral and statistical properties of the field of elevations. Experimental parametrization of the third-order structure function, the so-called skewness function, is one of the most important and original outcomes of this study. This function is of primary importance in analytical scattering models from the sea surface and was up to now unavailable in field conditions. Due to the lack of precise reference measurements for the small-scale wave field, we could not quantify exactly the accuracy of the retrieval technique. However, it appeared clearly that the obtained accuracy is good enough for the estimation of second-order statistical quantities (such as the correlation function), acceptable for third-order quantities (such as the skwewness function) and insufficient for fourth-order quantities (such as kurtosis). Therefore, the stereo technique in the present stage should not be thought as a self-contained universal tool to characterize the surface statistics. Instead, it should be used in conjunction with other well calibrated but sparse reference measurement (such as wave gauges) for cross-validation and calibration. It then completes the statistical analysis in as much as it provides a snapshot of the three-dimensional field and allows for the evaluation of higher-order spatial statistics.

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

On the Development of Turbulent Wakes from Vortex Streets

NASA Technical Reports Server (NTRS)

Roshko, Anatol

1954-01-01

Wake development behind circular cylinders at Reynolds numbers from 40 to 10,000 was investigated in a low-speed wind tunnel. Standard hot-wire techniques were used to study the velocity fluctuations. The Reynolds number range of periodic vortex shedding is divided into two distinct subranges. At r=40 to 150, called the stable range, regular vortex streets are formed and no turbulent velocity fluctuations accompany the periodic formation of vortices. The range r=150 to 300 is a transition range to a regime called the irregular range, in which turbulent velocity fluctuations accompany the periodic formation of vortices. The turbulence is initiated by laminar-turbulent transition in the free layers which spring from the separation points on the cylinder. The transition first occurs in the range r=150 to 300. Spectrum and statistical measurements were made to study the velocity fluctuations.

Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses

PubMed Central

Bayzid, Md Shamsuzzoha; Mirarab, Siavash; Boussau, Bastien; Warnow, Tandy

2015-01-01

Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically consistent under the multi-species coalescent model. New data used in this study are available at DOI: http://dx.doi.org/10.6084/m9.figshare.1411146, and the software is available at https://github.com/smirarab/binning. PMID:26086579

Bibliometric indexes, databases and impact factors in cardiology

PubMed Central

Bienert, Igor R C; de Oliveira, Rogério Carvalho; de Andrade, Pedro Beraldo; Caramori, Carlos Antonio

2015-01-01

Bibliometry is a quantitative statistical technique to measure levels of production and dissemination of knowledge, as well as a useful tool to track the development of an scientific area. The valuation of production required for recognition of researchers and magazines is accomplished through tools called bibliometricindexes, divided into quality indicators and scientific impact. Initially developed for monographs of statistical measures especially in libraries, today bibliometrics is mainly used to evaluate productivity of authors and citation repercussion. However, these tools have limitations and sometimes provoke controversies about indiscriminate application, leading to the development of newer indexes. It is important to know the most common search indexes and use it properly even acknowledging its limitations as it has a direct impact in their daily practice, reputation and funds achievement. PMID:26107458

Measurements of Turbulent Flow Field in Separate Flow Nozzles with Enhanced Mixing Devices - Test Report

NASA Technical Reports Server (NTRS)

Bridges, James

2002-01-01

As part of the Advanced Subsonic Technology Program, a series of experiments was conducted at NASA Glenn Research Center on the effect of mixing enhancement devices on the aeroacoustic performance of separate flow nozzles. Initial acoustic evaluations of the devices showed that they reduced jet noise significantly, while creating very little thrust loss. The explanation for the improvement required that turbulence measurements, namely single point mean and RMS statistics and two-point spatial correlations, be made to determine the change in the turbulence caused by the mixing enhancement devices that lead to the noise reduction. These measurements were made in the summer of 2000 in a test program called Separate Nozzle Flow Test 2000 (SFNT2K) supported by the Aeropropulsion Research Program at NASA Glenn Research Center. Given the hot high-speed flows representative of a contemporary bypass ratio 5 turbofan engine, unsteady flow field measurements required the use of an optical measurement method. To achieve the spatial correlations, the Particle Image Velocimetry technique was employed, acquiring high-density velocity maps of the flows from which the required statistics could be derived. This was the first successful use of this technique for such flows, and shows the utility of this technique for future experimental programs. The extensive statistics obtained were likewise unique and give great insight into the turbulence which produces noise and how the turbulence can be modified to reduce jet noise.

Persistence Mapping Using EUV Solar Imager Data

NASA Technical Reports Server (NTRS)

Thompson, B. J.; Young, C. A.

2016-01-01

We describe a simple image processing technique that is useful for the visualization and depiction of gradually evolving or intermittent structures in solar physics extreme-ultraviolet imagery. The technique is an application of image segmentation, which we call "Persistence Mapping," to isolate extreme values in a data set, and is particularly useful for the problem of capturing phenomena that are evolving in both space and time. While integration or "time-lapse" imaging uses the full sample (of size N ), Persistence Mapping rejects (N - 1)/N of the data set and identifies the most relevant 1/N values using the following rule: if a pixel reaches an extreme value, it retains that value until that value is exceeded. The simplest examples isolate minima and maxima, but any quantile or statistic can be used. This paper demonstrates how the technique has been used to extract the dynamics in long-term evolution of comet tails, erupting material, and EUV dimming regions.

The mediating effect of calling on the relationship between medical school students’ academic burnout and empathy

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Modeling, simulation, and estimation of optical turbulence

NASA Astrophysics Data System (ADS)

Formwalt, Byron Paul

This dissertation documents three new contributions to simulation and modeling of optical turbulence. The first contribution is the formalization, optimization, and validation of a modeling technique called successively conditioned rendering (SCR). The SCR technique is empirically validated by comparing the statistical error of random phase screens generated with the technique. The second contribution is the derivation of the covariance delineation theorem, which provides theoretical bounds on the error associated with SCR. It is shown empirically that the theoretical bound may be used to predict relative algorithm performance. Therefore, the covariance delineation theorem is a powerful tool for optimizing SCR algorithms. For the third contribution, we introduce a new method for passively estimating optical turbulence parameters, and demonstrate the method using experimental data. The technique was demonstrated experimentally, using a 100 m horizontal path at 1.25 m above sun-heated tarmac on a clear afternoon. For this experiment, we estimated C2n ≈ 6.01 · 10-9 m-23 , l0 ≈ 17.9 mm, and L0 ≈ 15.5 m.

Stabilization of Particle Discrimination Efficiencies for Neutron Spectrum Unfolding With Organic Scintillators

NASA Astrophysics Data System (ADS)

Lawrence, Chris C.; Polack, J. K.; Febbraro, Michael; Kolata, J. J.; Flaska, Marek; Pozzi, S. A.; Becchetti, F. D.

2017-02-01

The literature discussing pulse-shape discrimination (PSD) in organic scintillators dates back several decades. However, little has been written about PSD techniques that are optimized for neutron spectrum unfolding. Variation in n-γ misclassification rates and in γ/n ratio of incident fields can distort the neutron pulse-height response of scintillators and these distortions can in turn cause large errors in unfolded spectra. New applications in arms-control verification call for detection of lower-energy neutrons, for which PSD is particularly problematic. In this article, we propose techniques for removing distortions on pulse-height response that result from the merging of PSD distributions in the low-pulse-height region. These techniques take advantage of the repeatable shapes of PSD distributions that are governed by the counting statistics of scintillation-photon populations. We validate the proposed techniques using accelerator-based time-of-flight measurements and then demonstrate them by unfolding the Watt spectrum from measurement with a 252Cf neutron source.

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

Ghamarian, Iman, E-mail: imanghamarian@yahoo.com; Department of Materials Science and Engineering, University of North Texas, Denton, TX 76203; Samimi, Peyman

The presence and interaction of nanotwins, geometrically necessary dislocations, and grain boundaries play a key role in the mechanical properties of nanostructured crystalline materials. Therefore, it is vital to determine the orientation, width and distance of nanotwins, the angle and axis of grain boundary misorientations as well as the type and the distributions of dislocations in an automatic and statistically meaningful fashion in a relatively large area. In this paper, such details are provided using a transmission electron microscope-based orientation microscopy technique called ASTAR™/precession electron diffraction. The remarkable spatial resolution of this technique (~ 2 nm) enables highly detailed characterizationmore » of nanotwins, grain boundaries and the configuration of dislocations. This orientation microscopy technique provides the raw data required for the determination of these parameters. The procedures to post-process the ASTAR™/PED datasets in order to obtain the important (and currently largely hidden) details of nanotwins as well as quantifications of dislocation density distributions are described in this study. - Highlights: • EBSD cannot characterize defects such as dislocations, grain boundaries and nanotwins in severely deformed metals. • TEM based orientation microscopy technique called ASTAR™/PED was used to resolve the problem. • Locations and orientations of nanotwins, dislocation density distribution and grain boundary characters can be resolved. • This work provides the bases for further studies on the interactions between dislocations, grain boundaries and nanotwins. • The computation part is explained sufficiently which helps the readers to post process their own data.« less

Asteroid shape and spin statistics from convex models

NASA Astrophysics Data System (ADS)

Torppa, J.; Hentunen, V.-P.; Pääkkönen, P.; Kehusmaa, P.; Muinonen, K.

2008-11-01

We introduce techniques for characterizing convex shape models of asteroids with a small number of parameters, and apply these techniques to a set of 87 models from convex inversion. We present three different approaches for determining the overall dimensions of an asteroid. With the first technique, we measured the dimensions of the shapes in the direction of the rotation axis and in the equatorial plane and with the two other techniques, we derived the best-fit ellipsoid. We also computed the inertia matrix of the model shape to test how well it represents the target asteroid, i.e., to find indications of possible non-convex features or albedo variegation, which the convex shape model cannot reproduce. We used shape models for 87 asteroids to perform statistical analyses and to study dependencies between shape and rotation period, size, and taxonomic type. We detected correlations, but more data are required, especially on small and large objects, as well as slow and fast rotators, to reach a more thorough understanding about the dependencies. Results show, e.g., that convex models of asteroids are not that far from ellipsoids in root-mean-square sense, even though clearly irregular features are present. We also present new spin and shape solutions for Asteroids (31) Euphrosyne, (54) Alexandra, (79) Eurynome, (93) Minerva, (130) Elektra, (376) Geometria, (471) Papagena, and (776) Berbericia. We used a so-called semi-statistical approach to obtain a set of possible spin state solutions. The number of solutions depends on the abundancy of the data, which for Eurynome, Elektra, and Geometria was extensive enough for determining an unambiguous spin and shape solution. Data of Euphrosyne, on the other hand, provided a wide distribution of possible spin solutions, whereas the rest of the targets have two or three possible solutions.

Digital correlation detector for low-cost Omega navigation

NASA Technical Reports Server (NTRS)

Chamberlin, K. A.

1976-01-01

Techniques to lower the cost of using the Omega global navigation network with phase-locked loops (PLL) were developed. The technique that was accepted as being "optimal" is called the memory-aided phase-locked loop (MAPLL) since it allows operation on all eight Omega time slots with one PLL through the implementation of a random access memory. The receiver front-end and the signals that it transmits to the PLL were first described. A brief statistical analysis of these signals was then made to allow a rough comparison between the front-end presented in this work and a commercially available front-end to be made. The hardware and theory of application of the MAPLL were described, ending with an analysis of data taken with the MAPLL. Some conclusions and recommendations were also given.

CD process control through machine learning

NASA Astrophysics Data System (ADS)

Utzny, Clemens

2016-10-01

For the specific requirements of the 14nm and 20nm site applications a new CD map approach was developed at the AMTC. This approach relies on a well established machine learning technique called recursive partitioning. Recursive partitioning is a powerful technique which creates a decision tree by successively testing whether the quantity of interest can be explained by one of the supplied covariates. The test performed is generally a statistical test with a pre-supplied significance level. Once the test indicates significant association between the variable of interest and a covariate a split performed at a threshold value which minimizes the variation within the newly attained groups. This partitioning is recurred until either no significant association can be detected or the resulting sub group size falls below a pre-supplied level.

Performance Analysis of Garbage Collection and Dynamic Reordering in a Lisp System. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Llames, Rene Lim

1991-01-01

Generation based garbage collection and dynamic reordering of objects are two techniques for improving the efficiency of memory management in Lisp and similar dynamic language systems. An analysis of the effect of generation configuration is presented, focusing on the effect of a number of generations and generation capabilities. Analytic timing and survival models are used to represent garbage collection runtime and to derive structural results on its behavior. The survival model provides bounds on the age of objects surviving a garbage collection at a particular level. Empirical results show that execution time is most sensitive to the capacity of the youngest generation. A technique called scanning for transport statistics, for evaluating the effectiveness of reordering independent of main memory size, is presented.

From Wald to Savage: homo economicus becomes a Bayesian statistician.

PubMed

Giocoli, Nicola

2013-01-01

Bayesian rationality is the paradigm of rational behavior in neoclassical economics. An economic agent is deemed rational when she maximizes her subjective expected utility and consistently revises her beliefs according to Bayes's rule. The paper raises the question of how, when and why this characterization of rationality came to be endorsed by mainstream economists. Though no definitive answer is provided, it is argued that the question is of great historiographic importance. The story begins with Abraham Wald's behaviorist approach to statistics and culminates with Leonard J. Savage's elaboration of subjective expected utility theory in his 1954 classic The Foundations of Statistics. The latter's acknowledged fiasco to achieve a reinterpretation of traditional inference techniques along subjectivist and behaviorist lines raises the puzzle of how a failed project in statistics could turn into such a big success in economics. Possible answers call into play the emphasis on consistency requirements in neoclassical theory and the impact of the postwar transformation of U.S. business schools. © 2012 Wiley Periodicals, Inc.

Topological Cacti: Visualizing Contour-based Statistics

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

Weber, Gunther H.; Bremer, Peer-Timo; Pascucci, Valerio

2011-05-26

Contours, the connected components of level sets, play an important role in understanding the global structure of a scalar field. In particular their nestingbehavior and topology-often represented in form of a contour tree-have been used extensively for visualization and analysis. However, traditional contour trees onlyencode structural properties like number of contours or the nesting of contours, but little quantitative information such as volume or other statistics. Here we use thesegmentation implied by a contour tree to compute a large number of per-contour (interval) based statistics of both the function defining the contour tree as well asother co-located functions. We introducemore » a new visual metaphor for contour trees, called topological cacti, that extends the traditional toporrery display of acontour tree to display additional quantitative information as width of the cactus trunk and length of its spikes. We apply the new technique to scalar fields ofvarying dimension and different measures to demonstrate the effectiveness of the approach.« less

An improved numerical method to compute neutron/gamma deexcitation cascades starting from a high spin state

DOE PAGES

Regnier, D.; Litaize, O.; Serot, O.

2015-12-23

Numerous nuclear processes involve the deexcitation of a compound nucleus through the emission of several neutrons, gamma-rays and/or conversion electrons. The characteristics of such a deexcitation are commonly derived from a total statistical framework often called “Hauser–Feshbach” method. In this work, we highlight a numerical limitation of this kind of method in the case of the deexcitation of a high spin initial state. To circumvent this issue, an improved technique called the Fluctuating Structure Properties (FSP) method is presented. Two FSP algorithms are derived and benchmarked on the calculation of the total radiative width for a thermal neutron capture onmore » 238U. We compare the standard method with these FSP algorithms for the prediction of particle multiplicities in the deexcitation of a high spin level of 143Ba. The gamma multiplicity turns out to be very sensitive to the numerical method. The bias between the two techniques can reach 1.5 γγ/cascade. Lastly, the uncertainty of these calculations coming from the lack of knowledge on nuclear structure is estimated via the FSP method.« less

Influence of Synaptic Depression on Memory Storage Capacity

NASA Astrophysics Data System (ADS)

Otsubo, Yosuke; Nagata, Kenji; Oizumi, Masafumi; Okada, Masato

2011-08-01

Synaptic efficacy between neurons is known to change within a short time scale dynamically. Neurophysiological experiments show that high-frequency presynaptic inputs decrease synaptic efficacy between neurons. This phenomenon is called synaptic depression, a short term synaptic plasticity. Many researchers have investigated how the synaptic depression affects the memory storage capacity. However, the noise has not been taken into consideration in their analysis. By introducing ``temperature'', which controls the level of the noise, into an update rule of neurons, we investigate the effects of synaptic depression on the memory storage capacity in the presence of the noise. We analytically compute the storage capacity by using a statistical mechanics technique called Self Consistent Signal to Noise Analysis (SCSNA). We find that the synaptic depression decreases the storage capacity in the case of finite temperature in contrast to the case of the low temperature limit, where the storage capacity does not change.

Statistical physics in foreign exchange currency and stock markets

NASA Astrophysics Data System (ADS)

Ausloos, M.

2000-09-01

Problems in economy and finance have attracted the interest of statistical physicists all over the world. Fundamental problems pertain to the existence or not of long-, medium- or/and short-range power-law correlations in various economic systems, to the presence of financial cycles and on economic considerations, including economic policy. A method like the detrended fluctuation analysis is recalled emphasizing its value in sorting out correlation ranges, thereby leading to predictability at short horizon. The ( m, k)-Zipf method is presented for sorting out short-range correlations in the sign and amplitude of the fluctuations. A well-known financial analysis technique, the so-called moving average, is shown to raise questions to physicists about fractional Brownian motion properties. Among spectacular results, the possibility of crash predictions has been demonstrated through the log-periodicity of financial index oscillations.

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics

PubMed Central

Dowding, Irene; Haufe, Stefan

2018-01-01

Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This “naive” approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment. PMID:29615885

Automatic classification of animal vocalizations

NASA Astrophysics Data System (ADS)

Clemins, Patrick J.

2005-11-01

Bioacoustics, the study of animal vocalizations, has begun to use increasingly sophisticated analysis techniques in recent years. Some common tasks in bioacoustics are repertoire determination, call detection, individual identification, stress detection, and behavior correlation. Each research study, however, uses a wide variety of different measured variables, called features, and classification systems to accomplish these tasks. The well-established field of human speech processing has developed a number of different techniques to perform many of the aforementioned bioacoustics tasks. Melfrequency cepstral coefficients (MFCCs) and perceptual linear prediction (PLP) coefficients are two popular feature sets. The hidden Markov model (HMM), a statistical model similar to a finite autonoma machine, is the most commonly used supervised classification model and is capable of modeling both temporal and spectral variations. This research designs a framework that applies models from human speech processing for bioacoustic analysis tasks. The development of the generalized perceptual linear prediction (gPLP) feature extraction model is one of the more important novel contributions of the framework. Perceptual information from the species under study can be incorporated into the gPLP feature extraction model to represent the vocalizations as the animals might perceive them. By including this perceptual information and modifying parameters of the HMM classification system, this framework can be applied to a wide range of species. The effectiveness of the framework is shown by analyzing African elephant and beluga whale vocalizations. The features extracted from the African elephant data are used as input to a supervised classification system and compared to results from traditional statistical tests. The gPLP features extracted from the beluga whale data are used in an unsupervised classification system and the results are compared to labels assigned by experts. The development of a framework from which to build animal vocalization classifiers will provide bioacoustics researchers with a consistent platform to analyze and classify vocalizations. A common framework will also allow studies to compare results across species and institutions. In addition, the use of automated classification techniques can speed analysis and uncover behavioral correlations not readily apparent using traditional techniques.

Adaptive correction of ensemble forecasts

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Battista Chirico, Giovanni; Van den Bergh, Joris; Vannitsem, Stephane

2017-04-01

Forecasts from numerical weather prediction (NWP) models often suffer from both systematic and non-systematic errors. These are present in both deterministic and ensemble forecasts, and originate from various sources such as model error and subgrid variability. Statistical post-processing techniques can partly remove such errors, which is particularly important when NWP outputs concerning surface weather variables are employed for site specific applications. Many different post-processing techniques have been developed. For deterministic forecasts, adaptive methods such as the Kalman filter are often used, which sequentially post-process the forecasts by continuously updating the correction parameters as new ground observations become available. These methods are especially valuable when long training data sets do not exist. For ensemble forecasts, well-known techniques are ensemble model output statistics (EMOS), and so-called "member-by-member" approaches (MBM). Here, we introduce a new adaptive post-processing technique for ensemble predictions. The proposed method is a sequential Kalman filtering technique that fully exploits the information content of the ensemble. One correction equation is retrieved and applied to all members, however the parameters of the regression equations are retrieved by exploiting the second order statistics of the forecast ensemble. We compare our new method with two other techniques: a simple method that makes use of a running bias correction of the ensemble mean, and an MBM post-processing approach that rescales the ensemble mean and spread, based on minimization of the Continuous Ranked Probability Score (CRPS). We perform a verification study for the region of Campania in southern Italy. We use two years (2014-2015) of daily meteorological observations of 2-meter temperature and 10-meter wind speed from 18 ground-based automatic weather stations distributed across the region, comparing them with the corresponding COSMO-LEPS ensemble forecasts. Deterministic verification scores (e.g., mean absolute error, bias) and probabilistic scores (e.g., CRPS) are used to evaluate the post-processing techniques. We conclude that the new adaptive method outperforms the simpler running bias-correction. The proposed adaptive method often outperforms the MBM method in removing bias. The MBM method has the advantage of correcting the ensemble spread, although it needs more training data.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

21 CFR 820.250 - Statistical techniques.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Statistical techniques. 820.250 Section 820.250...) MEDICAL DEVICES QUALITY SYSTEM REGULATION Statistical Techniques § 820.250 Statistical techniques. (a... statistical techniques required for establishing, controlling, and verifying the acceptability of process...

21 CFR 820.250 - Statistical techniques.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Statistical techniques. 820.250 Section 820.250...) MEDICAL DEVICES QUALITY SYSTEM REGULATION Statistical Techniques § 820.250 Statistical techniques. (a... statistical techniques required for establishing, controlling, and verifying the acceptability of process...

Planetary mass function and planetary systems

NASA Astrophysics Data System (ADS)

Dominik, M.

2011-02-01

With planets orbiting stars, a planetary mass function should not be seen as a low-mass extension of the stellar mass function, but a proper formalism needs to take care of the fact that the statistical properties of planet populations are linked to the properties of their respective host stars. This can be accounted for by describing planet populations by means of a differential planetary mass-radius-orbit function, which together with the fraction of stars with given properties that are orbited by planets and the stellar mass function allows the derivation of all statistics for any considered sample. These fundamental functions provide a framework for comparing statistics that result from different observing techniques and campaigns which all have their very specific selection procedures and detection efficiencies. Moreover, recent results both from gravitational microlensing campaigns and radial-velocity surveys of stars indicate that planets tend to cluster in systems rather than being the lonely child of their respective parent star. While planetary multiplicity in an observed system becomes obvious with the detection of several planets, its quantitative assessment however comes with the challenge to exclude the presence of further planets. Current exoplanet samples begin to give us first hints at the population statistics, whereas pictures of planet parameter space in its full complexity call for samples that are 2-4 orders of magnitude larger. In order to derive meaningful statistics, however, planet detection campaigns need to be designed in such a way that well-defined fully deterministic target selection, monitoring and detection criteria are applied. The probabilistic nature of gravitational microlensing makes this technique an illustrative example of all the encountered challenges and uncertainties.

A Public Health Initiative for Preventing Family Violence.

ERIC Educational Resources Information Center

Hargens, Yvonne Marie

A community task force studying violence issues closely examined police statistics for domestic calls. Few records of referrals were made in response to these calls. Other statistics on child abuse and family violence reinforced the fact that family violence was a significant problem, making program response to family violence issues a top…

Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors.

PubMed Central

Small, J R

1993-01-01

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434

A fast and objective multidimensional kernel density estimation method: fastKDE

DOE PAGES

O'Brien, Travis A.; Kashinath, Karthik; Cavanaugh, Nicholas R.; ...

2016-03-07

Numerous facets of scientific research implicitly or explicitly call for the estimation of probability densities. Histograms and kernel density estimates (KDEs) are two commonly used techniques for estimating such information, with the KDE generally providing a higher fidelity representation of the probability density function (PDF). Both methods require specification of either a bin width or a kernel bandwidth. While techniques exist for choosing the kernel bandwidth optimally and objectively, they are computationally intensive, since they require repeated calculation of the KDE. A solution for objectively and optimally choosing both the kernel shape and width has recently been developed by Bernacchiamore » and Pigolotti (2011). While this solution theoretically applies to multidimensional KDEs, it has not been clear how to practically do so. A method for practically extending the Bernacchia-Pigolotti KDE to multidimensions is introduced. This multidimensional extension is combined with a recently-developed computational improvement to their method that makes it computationally efficient: a 2D KDE on 10 5 samples only takes 1 s on a modern workstation. This fast and objective KDE method, called the fastKDE method, retains the excellent statistical convergence properties that have been demonstrated for univariate samples. The fastKDE method exhibits statistical accuracy that is comparable to state-of-the-science KDE methods publicly available in R, and it produces kernel density estimates several orders of magnitude faster. The fastKDE method does an excellent job of encoding covariance information for bivariate samples. This property allows for direct calculation of conditional PDFs with fastKDE. It is demonstrated how this capability might be leveraged for detecting non-trivial relationships between quantities in physical systems, such as transitional behavior.« less

A new measure for gene expression biclustering based on non-parametric correlation.

PubMed

Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja

2013-12-01

One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

O'Brien, Travis A.; Kashinath, Karthik; Cavanaugh, Nicholas R.

Numerous facets of scientific research implicitly or explicitly call for the estimation of probability densities. Histograms and kernel density estimates (KDEs) are two commonly used techniques for estimating such information, with the KDE generally providing a higher fidelity representation of the probability density function (PDF). Both methods require specification of either a bin width or a kernel bandwidth. While techniques exist for choosing the kernel bandwidth optimally and objectively, they are computationally intensive, since they require repeated calculation of the KDE. A solution for objectively and optimally choosing both the kernel shape and width has recently been developed by Bernacchiamore » and Pigolotti (2011). While this solution theoretically applies to multidimensional KDEs, it has not been clear how to practically do so. A method for practically extending the Bernacchia-Pigolotti KDE to multidimensions is introduced. This multidimensional extension is combined with a recently-developed computational improvement to their method that makes it computationally efficient: a 2D KDE on 10 5 samples only takes 1 s on a modern workstation. This fast and objective KDE method, called the fastKDE method, retains the excellent statistical convergence properties that have been demonstrated for univariate samples. The fastKDE method exhibits statistical accuracy that is comparable to state-of-the-science KDE methods publicly available in R, and it produces kernel density estimates several orders of magnitude faster. The fastKDE method does an excellent job of encoding covariance information for bivariate samples. This property allows for direct calculation of conditional PDFs with fastKDE. It is demonstrated how this capability might be leveraged for detecting non-trivial relationships between quantities in physical systems, such as transitional behavior.« less

PERSISTENCE MAPPING USING EUV SOLAR IMAGER DATA

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

Thompson, B. J.; Young, C. A., E-mail: barbara.j.thompson@nasa.gov

We describe a simple image processing technique that is useful for the visualization and depiction of gradually evolving or intermittent structures in solar physics extreme-ultraviolet imagery. The technique is an application of image segmentation, which we call “Persistence Mapping,” to isolate extreme values in a data set, and is particularly useful for the problem of capturing phenomena that are evolving in both space and time. While integration or “time-lapse” imaging uses the full sample (of size N ), Persistence Mapping rejects ( N − 1)/ N of the data set and identifies the most relevant 1/ N values using themore » following rule: if a pixel reaches an extreme value, it retains that value until that value is exceeded. The simplest examples isolate minima and maxima, but any quantile or statistic can be used. This paper demonstrates how the technique has been used to extract the dynamics in long-term evolution of comet tails, erupting material, and EUV dimming regions.« less

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

2001-09-01

This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

Electroencephalography signatures of attention-deficit/hyperactivity disorder: clinical utility.

PubMed

Alba, Guzmán; Pereda, Ernesto; Mañas, Soledad; Méndez, Leopoldo D; González, Almudena; González, Julián J

2015-01-01

The techniques and the most important results on the use of electroencephalography (EEG) to extract different measures are reviewed in this work, which can be clinically useful to study subjects with attention-deficit/hyperactivity disorder (ADHD). First, we discuss briefly and in simple terms the EEG analysis and processing techniques most used in the context of ADHD. We review techniques that both analyze individual EEG channels (univariate measures) and study the statistical interdependence between different EEG channels (multivariate measures), the so-called functional brain connectivity. Among the former ones, we review the classical indices of absolute and relative spectral power and estimations of the complexity of the channels, such as the approximate entropy and the Lempel-Ziv complexity. Among the latter ones, we focus on the magnitude square coherence and on different measures based on the concept of generalized synchronization and its estimation in the state space. Second, from a historical point of view, we present the most important results achieved with these techniques and their clinical utility (sensitivity, specificity, and accuracy) to diagnose ADHD. Finally, we propose future research lines based on these results.

Disjunctive Normal Shape and Appearance Priors with Applications to Image Segmentation.

PubMed

Mesadi, Fitsum; Cetin, Mujdat; Tasdizen, Tolga

2015-10-01

The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. Active shape and appearance models require landmark points and assume unimodal shape and appearance distributions. Level set based shape priors are limited to global shape similarity. In this paper, we present a novel shape and appearance priors for image segmentation based on an implicit parametric shape representation called disjunctive normal shape model (DNSM). DNSM is formed by disjunction of conjunctions of half-spaces defined by discriminants. We learn shape and appearance statistics at varying spatial scales using nonparametric density estimation. Our method can generate a rich set of shape variations by locally combining training shapes. Additionally, by studying the intensity and texture statistics around each discriminant of our shape model, we construct a local appearance probability map. Experiments carried out on both medical and natural image datasets show the potential of the proposed method.

Bringing Clouds into Our Lab! - The Influence of Turbulence on the Early Stage Rain Droplets

NASA Astrophysics Data System (ADS)

Yavuz, Mehmet Altug; Kunnen, Rudie; Heijst, Gertjan; Clercx, Herman

2015-11-01

We are investigating a droplet-laden flow in an air-filled turbulence chamber, forced by speaker-driven air jets. The speakers are running in a random manner; yet they allow us to control and define the statistics of the turbulence. We study the motion of droplets with tunable size (Stokes numbers ~ 0.13 - 9) in a turbulent flow, mimicking the early stages of raindrop formation. 3D Particle Tracking Velocimetry (PTV) together with Laser Induced Fluorescence (LIF) methods are chosen as the experimental method to track the droplets and collect data for statistical analysis. Thereby it is possible to study the spatial distribution of the droplets in turbulence using the so-called Radial Distribution Function (RDF), a statistical measure to quantify the clustering of particles. Additionally, 3D-PTV technique allows us to measure velocity statistics of the droplets and the influence of the turbulence on droplet trajectories, both individually and collectively. In this contribution, we will present the clustering probability quantified by the RDF for different Stokes numbers. We will explain the physics underlying the influence of turbulence on droplet cluster behavior. This study supported by FOM/NWO Netherlands.

Statistics of Optical Coherence Tomography Data From Human Retina

PubMed Central

de Juan, Joaquín; Ferrone, Claudia; Giannini, Daniela; Huang, David; Koch, Giorgio; Russo, Valentina; Tan, Ou; Bruni, Carlo

2010-01-01

Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 µm. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages. PMID:20304733

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

Time-frequency and advanced frequency estimation techniques for the investigation of bat echolocation calls.

PubMed

Kopsinis, Yannis; Aboutanios, Elias; Waters, Dean A; McLaughlin, Steve

2010-02-01

In this paper, techniques for time-frequency analysis and investigation of bat echolocation calls are studied. Particularly, enhanced resolution techniques are developed and/or used in this specific context for the first time. When compared to traditional time-frequency representation methods, the proposed techniques are more capable of showing previously unseen features in the structure of bat echolocation calls. It should be emphasized that although the study is focused on bat echolocation recordings, the results are more general and applicable to many other types of signal.

New fluorescence techniques for high-throughput drug discovery.

PubMed

Jäger, S; Brand, L; Eggeling, C

2003-12-01

The rapid increase of compound libraries as well as new targets emerging from the Human Genome Project require constant progress in pharmaceutical research. An important tool is High-Throughput Screening (HTS), which has evolved as an indispensable instrument in the pre-clinical target-to-IND (Investigational New Drug) discovery process. HTS requires machinery, which is able to test more than 100,000 potential drug candidates per day with respect to a specific biological activity. This calls for certain experimental demands especially with respect to sensitivity, speed, and statistical accuracy, which are fulfilled by using fluorescence technology instrumentation. In particular the recently developed family of fluorescence techniques, FIDA (Fluorescence Intensity Distribution Analysis), which is based on confocal single-molecule detection, has opened up a new field of HTS applications. This report describes the application of these new techniques as well as of common fluorescence techniques--such as confocal fluorescence lifetime and anisotropy--to HTS. It gives experimental examples and presents advantages and disadvantages of each method. In addition the most common artifacts (auto-fluorescence or quenching by the drug candidates) emerging from the fluorescence detection techniques are highlighted and correction methods for confocal fluorescence read-outs are presented, which are able to circumvent this deficiency.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Sparse grid techniques for particle-in-cell schemes

NASA Astrophysics Data System (ADS)

Ricketson, L. F.; Cerfon, A. J.

2017-02-01

We propose the use of sparse grids to accelerate particle-in-cell (PIC) schemes. By using the so-called ‘combination technique’ from the sparse grids literature, we are able to dramatically increase the size of the spatial cells in multi-dimensional PIC schemes while paying only a slight penalty in grid-based error. The resulting increase in cell size allows us to reduce the statistical noise in the simulation without increasing total particle number. We present initial proof-of-principle results from test cases in two and three dimensions that demonstrate the new scheme’s efficiency, both in terms of computation time and memory usage.

A comparison of calls subjected to a malpractice claim versus 'normal calls' within the Swedish healthcare direct: a case-control study.

PubMed

Ernesäter, Annica; Engström, Maria; Winblad, Ulrika; Holmström, Inger K

2014-10-03

The purpose of this study is to compare communication patterns in calls subjected to a malpractice claim with matched controls. In many countries, telephone advice nursing is patients' first contact with healthcare. Telenurses' assessment of callers' symptoms and needs are based on verbal communication only, and problems with over-triage and under-triage have been reported. A total sample of all reported medical errors (n=33) during the period 2003-2010 within Swedish Healthcare Direct was retrieved. Corresponding calls were thereafter identified and collected as sound files from the manager in charge at the respective call centres. For technical reasons, calls from four of the cases were not possible to retrieve. For the present study, matched control calls (n=26) based on the patient's age, gender and main symptom presented by the caller were collected. Male patients were in majority (n=16), and the most common reasons for calling were abdominal pain (n=10) and chest pain (n=5). There were statistically significant differences between the communication in the cases and controls: telenurses used fewer open-ended medical questions (p<0.001) in the cases compared to the control calls; callers provided telenurses with more medical information in the control calls compared to the cases (p=0.001); and telenurses used more facilitation and patient activation activities in the control calls (p=0.034), such as back-channel response (p=0.001), compared to the cases. The present study shows that telenurses in malpractice claimed calls used more closed-ended questioning compared to those in control calls, who used more open-ended questioning and back-channel response, which provided them with richer medical descriptions and more information from the caller. Hence, these communicative techniques are important in addition to solid medical and nursing competence and sound decision aid systems. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Machine learning to analyze images of shocked materials for precise and accurate measurements

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

Dresselhaus-Cooper, Leora; Howard, Marylesa; Hock, Margaret C.

A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast imagesmore » of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.« less

Helping Students Develop Statistical Reasoning: Implementing a Statistical Reasoning Learning Environment

ERIC Educational Resources Information Center

Garfield, Joan; Ben-Zvi, Dani

2009-01-01

This article describes a model for an interactive, introductory secondary- or tertiary-level statistics course that is designed to develop students' statistical reasoning. This model is called a "Statistical Reasoning Learning Environment" and is built on the constructivist theory of learning.

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

PubMed

Rollins, Derrick K; Teh, Ailing

2010-12-17

Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

The Sloan Digital Sky Survey-II: Photometry and Supernova Ia Light Curves from the 2005 Data

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

Holtzman, Jon A.; /New Mexico State U.; Marriner, John

2010-08-26

We present ugriz light curves for 146 spectroscopically confirmed or spectroscopically probable Type Ia supernovae from the 2005 season of the SDSS-II Supernova survey. The light curves have been constructed using a photometric technique that we call scene modeling, which is described in detail here; the major feature is that supernova brightnesses are extracted from a stack of images without spatial resampling or convolution of the image data. This procedure produces accurate photometry along with accurate estimates of the statistical uncertainty, and can be used to derive photometry taken with multiple telescopes. We discuss various tests of this technique thatmore » demonstrate its capabilities. We also describe the methodology used for the calibration of the photometry, and present calibrated magnitudes and fluxes for all of the spectroscopic SNe Ia from the 2005 season.« less

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Computer-aided boundary delineation of agricultural lands

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1989-01-01

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

Validation of a new technique to detect Cryptosporidium spp. oocysts in bovine feces.

PubMed

Inácio, Sandra Valéria; Gomes, Jancarlo Ferreira; Oliveira, Bruno César Miranda; Falcão, Alexandre Xavier; Suzuki, Celso Tetsuo Nagase; Dos Santos, Bianca Martins; de Aquino, Monally Conceição Costa; de Paula Ribeiro, Rafaela Silva; de Assunção, Danilla Mendes; Casemiro, Pamella Almeida Freire; Meireles, Marcelo Vasconcelos; Bresciani, Katia Denise Saraiva

2016-11-01

Due to its important zoonotic potential, cryptosporidiosis arouses strong interest in the scientific community, because, it was initially considered a rare and opportunistic disease. The parasitological diagnosis of the causative agent of this disease, the protozoan Cryptosporidium spp., requires the use of specific techniques of concentration and permanent staining, which are laborious and costly, and are difficult to use in routine laboratory tests. In view of the above, we conducted the feasibility, development, evaluation and intralaboratory validation of a new parasitological technique for analysis in optical microscopy of Cryptosporidium spp. oocysts, called TF-Test Coccidia, using fecal samples from calves from the city of Araçatuba, São Paulo. To confirm the aforementioned parasite and prove the diagnostic efficiency of the new technique, we used two established methodologies in the scientific literature: parasite concentration by centrifugal sedimentation and negative staining with malachite green (CSN-Malachite) and Nested-PCR. We observed good effectiveness of the TF-Test Coccidia technique, being statistically equivalent to CSN-Malachite. Thus, we verified the effectiveness of the TF-Test Coccidia parasitological technique for the detection of Cryptosporidium spp. oocysts and observed good concentration and morphology of the parasite, with a low amount of debris in the fecal smear. Copyright © 2016 Elsevier B.V. All rights reserved.

Japan Report

DTIC Science & Technology

1985-03-18

increased profitability, productivity and more effective management ." Members of the British side also called for an increase in Japan’s defense...copyright transfer, or rental permission is called technology trade. According to the Statistic Bureau of the Management and Coordina- tion Agency...1- 8.8 -Swizerland 6.3 5.6 Others 13.1 Source: Statistics Bureau of the Management and Coordination Agency China. 66.2% of Japan’s imported

Image Filtering with Boolean and Statistical Operators.

DTIC Science & Technology

1983-12-01

S3(2) COMPLEX AMAT(256, 4). BMAT (256. 4). CMAT(256. 4) CALL IOF(3. MAIN. AFLNM. DFLNI, CFLNM. MS., 82, S3) CALL OPEN(1.AFLNM* 1.IER) CALL CHECKC!ER...RDBLK(2. 6164. MAT. 16, IER) CALL CHECK(IER) DO I K-1. 4 DO I J-1.256 CMAT(J. K)-AMAT(J. K)’. BMAT (J. K) I CONTINUE S CALL WRBLK(3. 164!. CMAT. 16. IER

Developing Statistical Literacy with Year 9 Students: A Collaborative Research Project

ERIC Educational Resources Information Center

Sharma, Sashi

2013-01-01

Advances in technology and communication have increased the amount of statistical information delivered through everyday media. The importance of statistics in everyday life has led to calls for increased attention to statistical literacy in the mathematics curriculum (Watson 2006). Gal (2004) sees statistical literacy as the need for students to…

Genotyping and inflated type I error rate in genome-wide association case/control studies

PubMed Central

Sampson, Joshua N; Zhao, Hongyu

2009-01-01

Background One common goal of a case/control genome wide association study (GWAS) is to find SNPs associated with a disease. Traditionally, the first step in such studies is to assign a genotype to each SNP in each subject, based on a statistic summarizing fluorescence measurements. When the distributions of the summary statistics are not well separated by genotype, the act of genotype assignment can lead to more potential problems than acknowledged by the literature. Results Specifically, we show that the proportions of each called genotype need not equal the true proportions in the population, even as the number of subjects grows infinitely large. The called genotypes for two subjects need not be independent, even when their true genotypes are independent. Consequently, p-values from tests of association can be anti-conservative, even when the distributions of the summary statistic for the cases and controls are identical. To address these problems, we propose two new tests designed to reduce the inflation in the type I error rate caused by these problems. The first algorithm, logiCALL, measures call quality by fully exploring the likelihood profile of intensity measurements, and the second algorithm avoids genotyping by using a likelihood ratio statistic. Conclusion Genotyping can introduce avoidable false positives in GWAS. PMID:19236714

Probabilistic seasonal Forecasts to deterministic Farm Leve Decisions: Innovative Approach

NASA Astrophysics Data System (ADS)

Mwangi, M. W.

2015-12-01

Climate change and vulnerability are major challenges in ensuring household food security. Climate information services have the potential to cushion rural households from extreme climate risks. However, most the probabilistic nature of climate information products is not easily understood by majority of smallholder farmers. Despite the probabilistic nature, climate information have proved to be a valuable climate risk adaptation strategy at the farm level. This calls for innovative ways to help farmers understand and apply climate information services to inform their farm level decisions. The study endeavored to co-design and test appropriate innovation systems for climate information services uptake and scale up necessary for achieving climate risk development. In addition it also determined the conditions necessary to support the effective performance of the proposed innovation system. Data and information sources included systematic literature review, secondary sources, government statistics, focused group discussions, household surveys and semi-structured interviews. Data wasanalyzed using both quantitative and qualitative data analysis techniques. Quantitative data was analyzed using the Statistical Package for Social Sciences (SPSS) software. Qualitative data was analyzed using qualitative techniques, which involved establishing the categories and themes, relationships/patterns and conclusions in line with the study objectives. Sustainable livelihood, reduced household poverty and climate change resilience were the impact that resulted from the study.

Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure - Activity Relationships (PCSAR).

PubMed

Kamath, Padmaja; Fernandez, Alberto; Giralt, Francesc; Rallo, Robert

2015-01-01

Nanoparticles are likely to interact in real-case application scenarios with mixtures of proteins and biomolecules that will absorb onto their surface forming the so-called protein corona. Information related to the composition of the protein corona and net cell association was collected from literature for a library of surface-modified gold and silver nanoparticles. For each protein in the corona, sequence information was extracted and used to calculate physicochemical properties and statistical descriptors. Data cleaning and preprocessing techniques including statistical analysis and feature selection methods were applied to remove highly correlated, redundant and non-significant features. A weighting technique was applied to construct specific signatures that represent the corona composition for each nanoparticle. Using this basic set of protein descriptors, a new Protein Corona Structure-Activity Relationship (PCSAR) that relates net cell association with the physicochemical descriptors of the proteins that form the corona was developed and validated. The features that resulted from the feature selection were in line with already published literature, and the computational model constructed on these features had a good accuracy (R(2)LOO=0.76 and R(2)LMO(25%)=0.72) and stability, with the advantage that the fingerprints based on physicochemical descriptors were independent of the specific proteins that form the corona.

Integrating Formal Methods and Testing 2002

NASA Technical Reports Server (NTRS)

Cukic, Bojan

2002-01-01

Traditionally, qualitative program verification methodologies and program testing are studied in separate research communities. None of them alone is powerful and practical enough to provide sufficient confidence in ultra-high reliability assessment when used exclusively. Significant advances can be made by accounting not only tho formal verification and program testing. but also the impact of many other standard V&V techniques, in a unified software reliability assessment framework. The first year of this research resulted in the statistical framework that, given the assumptions on the success of the qualitative V&V and QA procedures, significantly reduces the amount of testing needed to confidently assess reliability at so-called high and ultra-high levels (10-4 or higher). The coming years shall address the methodologies to realistically estimate the impacts of various V&V techniques to system reliability and include the impact of operational risk to reliability assessment. Combine formal correctness verification, process and product metrics, and other standard qualitative software assurance methods with statistical testing with the aim of gaining higher confidence in software reliability assessment for high-assurance applications. B) Quantify the impact of these methods on software reliability. C) Demonstrate that accounting for the effectiveness of these methods reduces the number of tests needed to attain certain confidence level. D) Quantify and justify the reliability estimate for systems developed using various methods.

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

DREAM: An Efficient Methodology for DSMC Simulation of Unsteady Processes

NASA Astrophysics Data System (ADS)

Cave, H. M.; Jermy, M. C.; Tseng, K. C.; Wu, J. S.

2008-12-01

A technique called the DSMC Rapid Ensemble Averaging Method (DREAM) for reducing the statistical scatter in the output from unsteady DSMC simulations is introduced. During post-processing by DREAM, the DSMC algorithm is re-run multiple times over a short period before the temporal point of interest thus building up a combination of time- and ensemble-averaged sampling data. The particle data is regenerated several mean collision times before the output time using the particle data generated during the original DSMC run. This methodology conserves the original phase space data from the DSMC run and so is suitable for reducing the statistical scatter in highly non-equilibrium flows. In this paper, the DREAM-II method is investigated and verified in detail. Propagating shock waves at high Mach numbers (Mach 8 and 12) are simulated using a parallel DSMC code (PDSC) and then post-processed using DREAM. The ability of DREAM to obtain the correct particle velocity distribution in the shock structure is demonstrated and the reduction of statistical scatter in the output macroscopic properties is measured. DREAM is also used to reduce the statistical scatter in the results from the interaction of a Mach 4 shock with a square cavity and for the interaction of a Mach 12 shock on a wedge in a channel.

Space-filling designs for computer experiments: A review

DOE PAGES

Joseph, V. Roshan

2016-01-29

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Space-filling designs for computer experiments: A review

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

Joseph, V. Roshan

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

On effectiveness of network sensor-based defense framework

NASA Astrophysics Data System (ADS)

Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

2012-06-01

Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

Lipid membranes and single ion channel recording for the advanced physics laboratory

NASA Astrophysics Data System (ADS)

Klapper, Yvonne; Nienhaus, Karin; Röcker, Carlheinz; Ulrich Nienhaus, G.

2014-05-01

We present an easy-to-handle, low-cost, and reliable setup to study various physical phenomena on a nanometer-thin lipid bilayer using the so-called black lipid membrane technique. The apparatus allows us to precisely measure optical and electrical properties of free-standing lipid membranes, to study the formation of single ion channels, and to gain detailed information on the ion conduction properties of these channels using statistical physics and autocorrelation analysis. The experiments are well suited as part of an advanced physics or biophysics laboratory course; they interconnect physics, chemistry, and biology and will be appealing to students of the natural sciences who are interested in quantitative experimentation.

MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data

PubMed Central

Hu, Jiyuan; Li, Tengfei; Xiu, Zidi; Zhang, Hong

2015-01-01

Most existing statistical methods developed for calling single nucleotide polymorphisms (SNPs) using next-generation sequencing (NGS) data are based on Bayesian frameworks, and there does not exist any SNP caller that produces p-values for calling SNPs in a frequentist framework. To fill in this gap, we develop a new method MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs with NGS data. MAFsnp is based on an estimated likelihood ratio test (eLRT) statistic. In practical situation, the involved parameter is very close to the boundary of the parametric space, so the standard large sample property is not suitable to evaluate the finite-sample distribution of the eLRT statistic. Observing that the distribution of the test statistic is a mixture of zero and a continuous part, we propose to model the test statistic with a novel two-parameter mixture distribution. Once the parameters in the mixture distribution are estimated, p-values can be easily calculated for detecting SNPs, and the multiple-testing corrected p-values can be used to control false discovery rate (FDR) at any pre-specified level. With simulated data, MAFsnp is shown to have much better control of FDR than the existing SNP callers. Through the application to two real datasets, MAFsnp is also shown to outperform the existing SNP callers in terms of calling accuracy. An R package “MAFsnp” implementing the new SNP caller is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/. PMID:26309201

Applying behavior-analytic methodology to the science and practice of environmental enrichment in zoos and aquariums.

PubMed

Alligood, Christina A; Dorey, Nicole R; Mehrkam, Lindsay R; Leighty, Katherine A

2017-05-01

Environmental enrichment in zoos and aquariums is often evaluated at two overlapping levels: published research and day-to-day institutional record keeping. Several authors have discussed ongoing challenges with small sample sizes in between-groups zoological research and have cautioned against the inappropriate use of inferential statistics (Shepherdson, , International Zoo Yearbook, 38, 118-124; Shepherdson, Lewis, Carlstead, Bauman, & Perrin, Applied Animal Behaviour Science, 147, 298-277; Swaisgood, , Applied Animal Behaviour Science, 102, 139-162; Swaisgood & Shepherdson, , Zoo Biology, 24, 499-518). Multi-institutional studies are the typically-prescribed solution, but these are expensive and difficult to carry out. Kuhar ( Zoo Biology, 25, 339-352) provided a reminder that inferential statistics are only necessary when one wishes to draw general conclusions at the population level. Because welfare is assessed at the level of the individual animal, we argue that evaluations of enrichment efficacy are often instances in which inferential statistics may be neither necessary nor appropriate. In recent years, there have been calls for the application of behavior-analytic techniques to zoo animal behavior management, including environmental enrichment (e.g., Bloomsmith, Marr, & Maple, , Applied Animal Behaviour Science, 102, 205-222; Tarou & Bashaw, , Applied Animal Behaviour Science, 102, 189-204). Single-subject (also called single-case, or small-n) designs provide a means of designing evaluations of enrichment efficacy based on an individual's behavior. We discuss how these designs might apply to research and practice goals at zoos and aquariums, contrast them with standard practices in the field, and give examples of how each could be successfully applied in a zoo or aquarium setting. © 2017 Wiley Periodicals, Inc.

Semantically transparent fingerprinting for right protection of digital cinema

NASA Astrophysics Data System (ADS)

Wu, Xiaolin

2003-06-01

Digital cinema, a new frontier and crown jewel of digital multimedia, has the potential of revolutionizing the science, engineering and business of movie production and distribution. The advantages of digital cinema technology over traditional analog technology are numerous and profound. But without effective and enforceable copyright protection measures, digital cinema can be more susceptible to widespread piracy, which can dampen or even prevent the commercial deployment of digital cinema. In this paper we propose a novel approach of fingerprinting each individual distribution copy of a digital movie for the purpose of tracing pirated copies back to their source. The proposed fingerprinting technique presents a fundamental departure from the traditional digital watermarking/fingerprinting techniques. Its novelty and uniqueness lie in a so-called semantic or subjective transparency property. The fingerprints are created by editing those visual and audio attributes that can be modified with semantic and subjective transparency to the audience. Semantically-transparent fingerprinting or watermarking is the most robust kind among all existing watermarking techniques, because it is content-based not sample-based, and semantically-recoverable not statistically-recoverable.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Hold My Calls: An Activity for Introducing the Statistical Process

ERIC Educational Resources Information Center

Abel, Todd; Poling, Lisa

2015-01-01

Working with practicing teachers, this article demonstrates, through the facilitation of a statistical activity, how to introduce and investigate the unique qualities of the statistical process including: formulate a question, collect data, analyze data, and interpret data.

Health Statistics

MedlinePlus

... births, deaths, marriages, and divorces are sometimes called "vital statistics." Researchers use statistics to see patterns of diseases in groups of people. This can help in figuring out who is at risk for certain diseases, finding ways to control diseases and deciding which diseases ...

The Reasoning behind Informal Statistical Inference

ERIC Educational Resources Information Center

Makar, Katie; Bakker, Arthur; Ben-Zvi, Dani

2011-01-01

Informal statistical inference (ISI) has been a frequent focus of recent research in statistics education. Considering the role that context plays in developing ISI calls into question the need to be more explicit about the reasoning that underpins ISI. This paper uses educational literature on informal statistical inference and philosophical…

First Polarized Power Spectra from HERA-19 Commissioning Data: Comparison with Simulations

NASA Astrophysics Data System (ADS)

Igarashi, Amy; Chichura, Paul; Fox Fortino, Austin; Kohn, Saul; Aguirre, James; HERA Collaboration, CHAMP

2018-01-01

The Hydrogen Epoch of Reionization Array (HERA) is a radio telescope whose primary goal is the detection of redshifted 21-cm line radiation produced from the spin-flip transition of HI during the Epoch of Reionization (EoR). HERA is currently under construction in South Africa, and will eventually be an array of 350 14-m antennas. HERA aims for a statistical detection of the power spectrum of this emission, using the so-called delay spectrum technique (Parsons et al 2012). We examine a first season of commissioning data from the first 19 elements (HERA-19) to characterize Galactic and extragalactic foregrounds. We compare the delay spectrum for HERA-19 constructed from data to those constructed from simulations done using a detailed instrument electromagnetic model and using the unpolarized Global Sky Model (GSM2008). We compare the data and simulations to explore the effects of Stokes-I to Q and U leakage, and further examine whether statistical models of polarization match the observed polarized power spectra.

Perceptual basis of evolving Western musical styles

PubMed Central

Rodriguez Zivic, Pablo H.; Shifres, Favio; Cecchi, Guillermo A.

2013-01-01

The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectancies, are found in music perception, and they span a variety of different features and time scales. Specifically, there is evidence that music perception involves strong expectancies regarding the distribution of a melodic interval, namely, the distance between two consecutive notes within the context of another. The recent availability of a large Western music dataset, consisting of the historical record condensed as melodic interval counts, has opened new possibilities for data-driven analysis of musical perception. In this context, we present an analytical approach that, based on cognitive theories of music expectation and machine learning techniques, recovers a set of factors that accurately identifies historical trends and stylistic transitions between the Baroque, Classical, Romantic, and Post-Romantic periods. We also offer a plausible musicological and cognitive interpretation of these factors, allowing us to propose them as data-driven principles of melodic expectation. PMID:23716669

Learning coefficient of generalization error in Bayesian estimation and vandermonde matrix-type singularity.

PubMed

Aoyagi, Miki; Nagata, Kenji

2012-06-01

The term algebraic statistics arises from the study of probabilistic models and techniques for statistical inference using methods from algebra and geometry (Sturmfels, 2009 ). The purpose of our study is to consider the generalization error and stochastic complexity in learning theory by using the log-canonical threshold in algebraic geometry. Such thresholds correspond to the main term of the generalization error in Bayesian estimation, which is called a learning coefficient (Watanabe, 2001a , 2001b ). The learning coefficient serves to measure the learning efficiencies in hierarchical learning models. In this letter, we consider learning coefficients for Vandermonde matrix-type singularities, by using a new approach: focusing on the generators of the ideal, which defines singularities. We give tight new bound values of learning coefficients for the Vandermonde matrix-type singularities and the explicit values with certain conditions. By applying our results, we can show the learning coefficients of three-layered neural networks and normal mixture models.

An inequality for detecting financial fraud, derived from the Markowitz Optimal Portfolio Theory

NASA Astrophysics Data System (ADS)

Bard, Gregory V.

2016-12-01

The Markowitz Optimal Portfolio Theory, published in 1952, is well-known, and was often taught because it blends Lagrange Multipliers, matrices, statistics, and mathematical finance. However, the theory faded from prominence in American investing, as Business departments at US universities shifted from techniques based on mathematics, finance, and statistics, to focus instead on leadership, public speaking, interpersonal skills, advertising, etc… The author proposes a new application of Markowitz's Theory: the detection of a fairly broad category of financial fraud (called "Ponzi schemes" in American newspapers) by looking at a particular inequality derived from the Markowitz Optimal Portfolio Theory, relating volatility and expected rate of return. For example, one recent Ponzi scheme was that of Bernard Madoff, uncovered in December 2008, which comprised fraud totaling 64,800,000,000 US dollars [23]. The objective is to compare investments with the "efficient frontier" as predicted by Markowitz's theory. Violations of the inequality should be impossible in theory; therefore, in practice, violations might indicate fraud.

Matter-wave diffraction approaching limits predicted by Feynman path integrals for multipath interference

NASA Astrophysics Data System (ADS)

Barnea, A. Ronny; Cheshnovsky, Ori; Even, Uzi

2018-02-01

Interference experiments have been paramount in our understanding of quantum mechanics and are frequently the basis of testing the superposition principle in the framework of quantum theory. In recent years, several studies have challenged the nature of wave-function interference from the perspective of Born's rule—namely, the manifestation of so-called high-order interference terms in a superposition generated by diffraction of the wave functions. Here we present an experimental test of multipath interference in the diffraction of metastable helium atoms, with large-number counting statistics, comparable to photon-based experiments. We use a variation of the original triple-slit experiment and accurate single-event counting techniques to provide a new experimental bound of 2.9 ×10-5 on the statistical deviation from the commonly approximated null third-order interference term in Born's rule for matter waves. Our value is on the order of the maximal contribution predicted for multipath trajectories by Feynman path integrals.

Extraction of phase information in daily stock prices

NASA Astrophysics Data System (ADS)

Fujiwara, Yoshi; Maekawa, Satoshi

2000-06-01

It is known that, in an intermediate time-scale such as days, stock market fluctuations possess several statistical properties that are common to different markets. Namely, logarithmic returns of an asset price have (i) truncated Pareto-Lévy distribution, (ii) vanishing linear correlation, (iii) volatility clustering and its power-law autocorrelation. The fact (ii) is a consequence of nonexistence of arbitragers with simple strategies, but this does not mean statistical independence of market fluctuations. Little attention has been paid to temporal structure of higher-order statistics, although it contains some important information on market dynamics. We applied a signal separation technique, called Independent Component Analysis (ICA), to actual data of daily stock prices in Tokyo and New York Stock Exchange (TSE/NYSE). ICA does a linear transformation of lag vectors from time-series to find independent components by a nonlinear algorithm. We obtained a similar impulse response for these dataset. If it were a Martingale process, it can be shown that impulse response should be a delta-function under a few conditions that could be numerically checked and as was verified by surrogate data. This result would provide information on the market dynamics including speculative bubbles and arbitrating processes. .

Using Computational Modeling to Assess the Impact of Clinical Decision Support on Cancer Screening within Community Health Centers

PubMed Central

Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.

2014-01-01

Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241

Acoustic Mechanisms of a Species-Based Discrimination of the chick-a-dee Call in Sympatric Black-Capped (Poecile atricapillus) and Mountain Chickadees (P. gambeli).

PubMed

Guillette, Lauren M; Farrell, Tara M; Hoeschele, Marisa; Sturdy, Christopher B

2010-01-01

Previous perceptual research with black-capped and mountain chickadees has demonstrated that these species treat each other's namesake chick-a-dee calls as belonging to separate, open-ended categories. Further, the terminal dee portion of the call has been implicated as the most prominent species marker. However, statistical classification using acoustic summary features suggests that all note-types contained within the chick-a-dee call should be sufficient for species classification. The current study seeks to better understand the note-type based mechanisms underlying species-based classification of the chick-a-dee call by black-capped and mountain chickadees. In two, complementary, operant discrimination experiments, both species were trained to discriminate the species of the signaler using either entire chick-a-dee calls, or individual note-types from chick-a-dee calls. In agreement with previous perceptual work we find that the D note had significant stimulus control over species-based discrimination. However, in line with statistical classifications, we find that all note-types carry species information. We discuss reasons why the most easily discriminated note-types are likely candidates to carry species-based cues.

A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.

Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises

PubMed Central

Grama, Ion; Liu, Quansheng

2017-01-01

In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise. PMID:28692667

Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises.

PubMed

Jin, Qiyu; Grama, Ion; Liu, Quansheng

2017-01-01

In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise.

Developing Statistical Knowledge for Teaching during Design-Based Research

ERIC Educational Resources Information Center

Groth, Randall E.

2017-01-01

Statistical knowledge for teaching is not precisely equivalent to statistics subject matter knowledge. Teachers must know how to make statistics understandable to others as well as understand the subject matter themselves. This dual demand on teachers calls for the development of viable teacher education models. This paper offers one such model,…

Using GAISE and NCTM Standards as Frameworks for Teaching Probability and Statistics to Pre-Service Elementary and Middle School Mathematics Teachers

ERIC Educational Resources Information Center

Metz, Mary Louise

2010-01-01

Statistics education has become an increasingly important component of the mathematics education of today's citizens. In part to address the call for a more statistically literate citizenship, The "Guidelines for Assessment and Instruction in Statistics Education (GAISE)" were developed in 2005 by the American Statistical Association. These…

Parallel Geospatial Data Management for Multi-Scale Environmental Data Analysis on GPUs

NASA Astrophysics Data System (ADS)

Wang, D.; Zhang, J.; Wei, Y.

2013-12-01

As the spatial and temporal resolutions of Earth observatory data and Earth system simulation outputs are getting higher, in-situ and/or post- processing such large amount of geospatial data increasingly becomes a bottleneck in scientific inquires of Earth systems and their human impacts. Existing geospatial techniques that are based on outdated computing models (e.g., serial algorithms and disk-resident systems), as have been implemented in many commercial and open source packages, are incapable of processing large-scale geospatial data and achieve desired level of performance. In this study, we have developed a set of parallel data structures and algorithms that are capable of utilizing massively data parallel computing power available on commodity Graphics Processing Units (GPUs) for a popular geospatial technique called Zonal Statistics. Given two input datasets with one representing measurements (e.g., temperature or precipitation) and the other one represent polygonal zones (e.g., ecological or administrative zones), Zonal Statistics computes major statistics (or complete distribution histograms) of the measurements in all regions. Our technique has four steps and each step can be mapped to GPU hardware by identifying its inherent data parallelisms. First, a raster is divided into blocks and per-block histograms are derived. Second, the Minimum Bounding Boxes (MBRs) of polygons are computed and are spatially matched with raster blocks; matched polygon-block pairs are tested and blocks that are either inside or intersect with polygons are identified. Third, per-block histograms are aggregated to polygons for blocks that are completely within polygons. Finally, for blocks that intersect with polygon boundaries, all the raster cells within the blocks are examined using point-in-polygon-test and cells that are within polygons are used to update corresponding histograms. As the task becomes I/O bound after applying spatial indexing and GPU hardware acceleration, we have developed a GPU-based data compression technique by reusing our previous work on Bitplane Quadtree (or BPQ-Tree) based indexing of binary bitmaps. Results have shown that our GPU-based parallel Zonal Statistic technique on 3000+ US counties over 20+ billion NASA SRTM 30 meter resolution Digital Elevation (DEM) raster cells has achieved impressive end-to-end runtimes: 101 seconds and 46 seconds a low-end workstation equipped with a Nvidia GTX Titan GPU using cold and hot cache, respectively; and, 60-70 seconds using a single OLCF TITAN computing node and 10-15 seconds using 8 nodes. Our experiment results clearly show the potentials of using high-end computing facilities for large-scale geospatial processing.

Postoperative pain intensity after using different instrumentation techniques: a randomized clinical study

PubMed Central

ÇIÇEK, Ersan; KOÇAK, Mustafa Murat; KOÇAK, Sibel; SAĞLAM, Baran Can; TÜRKER, Sevinç Aktemur

2017-01-01

Abstract Postoperative pain is a frequent complication associated with root canal treatment, especially during apical instrumentation of tooth with preexisting periradicular inflammation Objectives The aim of this clinical study was to evaluate the influence of the instrumentation techniques on the incidence and intensity of postoperative pain in single-visit root canal treatment. Material and Methods Ninety patients with single root/canal and non-vital pulps were included. The patients were assigned into 3 groups according to root canal instrumentation technique used; modified step-back, reciprocal, and rotational techniques. Root canal treatment was carried out in a single visit and the severity of postoperative pain was assessed via 4-point pain intensity scale. All the participants were called through the phone at 12, 24 and 48 h to obtain the pain scores. Data were analyzed through the Kruskal–Wallis test. Results There was significant difference between all groups (p<0.05). The modified step-back technique produced postoperative pain significantly lower than the rotational (p=0.018) and reciprocal (p=0.020) techniques. No difference was found between the reciprocal and rotational techniques (p=0.868). Postoperative pain in the first 12 h period (p=0.763) and in the 24 h period (p=0.147) was not significantly different between the groups. However, the difference in the 48 h period was statistically different between the groups (p=0.040). Conclusion All instrumentation techniques caused postoperative pain. The modified step-back technique produced less pain compared to the rotational and reciprocal techniques. PMID:28198972

Three Reading Comprehension Strategies: TELLS, Story Mapping, and QARs.

ERIC Educational Resources Information Center

Sorrell, Adrian L.

1990-01-01

Three reading comprehension strategies are presented to assist learning-disabled students: an advance organizer technique called "TELLS Fact or Fiction" used before reading a passage, a schema-based technique called "Story Mapping" used while reading, and a postreading method of categorizing questions called…

Multivariate postprocessing techniques for probabilistic hydrological forecasting

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2016-04-01

Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power generation, Applied Energy, 96, 12-20, DOI: 10.1016/j.apenergy.2011.11.004. Schefzik, R., T. L. Thorarinsdottir, and T. Gneiting (2013), Uncertainty quantification in complex simulation models using ensemble copula coupling, Statistical Science, 28, 616-640, DOI: 10.1214/13-STS443.

Can fatigue affect acquisition of new surgical skills? A prospective trial of pre- and post-call general surgery residents using the da Vinci surgical skills simulator.

PubMed

Robison, Weston; Patel, Sonya K; Mehta, Akshat; Senkowski, Tristan; Allen, John; Shaw, Eric; Senkowski, Christopher K

2018-03-01

To study the effects of fatigue on general surgery residents' performance on the da Vinci Skills Simulator (dVSS). 15 General Surgery residents from various postgraduate training years (PGY2, PGY3, PGY4, and PGY5) performed 5 simulation tasks on the dVSS as recommended by the Robotic Training Network (RTN). The General Surgery residents had no prior experience with the dVSS. Participants were assigned to either the Pre-call group or Post-call group based on call schedule. As a measure of subjective fatigue, residents were given the Epworth Sleepiness Scale (ESS) prior to their dVSS testing. The dVSS MScore™ software recorded various metrics (Objective Structured Assessment of Technical Skills, OSATS) that were used to evaluate the performance of each resident to compare the robotic simulation proficiency between the Pre-call and Post-call groups. Six general surgery residents were stratified into the Pre-call group and nine into the Post-call group. These residents were also stratified into Fatigued (10) or Nonfatigued (5) groups, as determined by their reported ESS scores. A statistically significant difference was found between the Pre-call and Post-call reported sleep hours (p = 0.036). There was no statistically significant difference between the Pre-call and Post-call groups or between the Fatigued and Nonfatigued groups in time to complete exercise, number of attempts, and high MScore™ score. Despite variation in fatigue levels, there was no effect on the acquisition of robotic simulator skills.

LQAS: User Beware.

PubMed

Rhoda, Dale A; Fernandez, Soledad A; Fitch, David J; Lemeshow, Stanley

2010-02-01

Researchers around the world are using Lot Quality Assurance Sampling (LQAS) techniques to assess public health parameters and evaluate program outcomes. In this paper, we report that there are actually two methods being called LQAS in the world today, and that one of them is badly flawed. This paper reviews fundamental LQAS design principles, and compares and contrasts the two LQAS methods. We raise four concerns with the simply-written, freely-downloadable training materials associated with the second method. The first method is founded on sound statistical principles and is carefully designed to protect the vulnerable populations that it studies. The language used in the training materials for the second method is simple, but not at all clear, so the second method sounds very much like the first. On close inspection, however, the second method is found to promote study designs that are biased in favor of finding programmatic or intervention success, and therefore biased against the interests of the population being studied. We outline several recommendations, and issue a call for a new high standard of clarity and face validity for those who design, conduct, and report LQAS studies.

Visual field progression with frequency-doubling matrix perimetry and standard automated perimetry in patients with glaucoma and in healthy controls.

PubMed

Redmond, Tony; O'Leary, Neil; Hutchison, Donna M; Nicolela, Marcelo T; Artes, Paul H; Chauhan, Balwantray C

2013-12-01

A new analysis method called permutation of pointwise linear regression measures the significance of deterioration over time at each visual field location, combines the significance values into an overall statistic, and then determines the likelihood of change in the visual field. Because the outcome is a single P value, individualized to that specific visual field and independent of the scale of the original measurement, the method is well suited for comparing techniques with different stimuli and scales. To test the hypothesis that frequency-doubling matrix perimetry (FDT2) is more sensitive than standard automated perimetry (SAP) in identifying visual field progression in glaucoma. Patients with open-angle glaucoma and healthy controls were examined by FDT2 and SAP, both with the 24-2 test pattern, on the same day at 6-month intervals in a longitudinal prospective study conducted in a hospital-based setting. Only participants with at least 5 examinations were included. Data were analyzed with permutation of pointwise linear regression. Permutation of pointwise linear regression is individualized to each participant, in contrast to current analyses in which the statistical significance is inferred from population-based approaches. Analyses were performed with both total deviation and pattern deviation. Sixty-four patients and 36 controls were included in the study. The median age, SAP mean deviation, and follow-up period were 65 years, -2.6 dB, and 5.4 years, respectively, in patients and 62 years, +0.4 dB, and 5.2 years, respectively, in controls. Using total deviation analyses, statistically significant deterioration was identified in 17% of patients with FDT2, in 34% of patients with SAP, and in 14% of patients with both techniques; in controls these percentages were 8% with FDT2, 31% with SAP, and 8% with both. Using pattern deviation analyses, statistically significant deterioration was identified in 16% of patients with FDT2, in 17% of patients with SAP, and in 3% of patients with both techniques; in controls these values were 3% with FDT2 and none with SAP. No evidence was found that FDT2 is more sensitive than SAP in identifying visual field deterioration. In about one-third of healthy controls, age-related deterioration with SAP reached statistical significance.

Spatio-temporal Outlier Detection in Precipitation Data

NASA Astrophysics Data System (ADS)

Wu, Elizabeth; Liu, Wei; Chawla, Sanjay

The detection of outliers from spatio-temporal data is an important task due to the increasing amount of spatio-temporal data available and the need to understand and interpret it. Due to the limitations of current data mining techniques, new techniques to handle this data need to be developed. We propose a spatio-temporal outlier detection algorithm called Outstretch, which discovers the outlier movement patterns of the top-k spatial outliers over several time periods. The top-k spatial outliers are found using the Exact-Grid Top- k and Approx-Grid Top- k algorithms, which are an extension of algorithms developed by Agarwal et al. [1]. Since they use the Kulldorff spatial scan statistic, they are capable of discovering all outliers, unaffected by neighbouring regions that may contain missing values. After generating the outlier sequences, we show one way they can be interpreted, by comparing them to the phases of the El Niño Southern Oscilliation (ENSO) weather phenomenon to provide a meaningful analysis of the results.

Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

PubMed

Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2015-12-07

Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Candidate substances for space bioprocessing methodology and data specification for benefit evaluation

NASA Technical Reports Server (NTRS)

1978-01-01

Analytical and quantitative economic techniques are applied to the evaluation of the economic benefits of a wide range of substances for space bioprocessing. On the basis of expected clinical applications, as well as the size of the patient that could be affected by the clinical applications, eight substances are recommended for further benefit evaluation. Results show that a transitional probability methodology can be used to model at least one clinical application for each of these substances. In each recommended case, the disease and its therapy are sufficiently well understood and documented, and the statistical data is available to operate the model and produce estimates of the impact of new therapy systems on the cost of treatment, morbidity, and mortality. Utilizing the morbidity and mortality information produced by the model, a standard economic technique called the Value of Human Capital is used to estimate the social welfare benefits that could be attributable to the new therapy systems.

Generating a Multiphase Equation of State with Swarm Intelligence

NASA Astrophysics Data System (ADS)

Cox, Geoffrey

2017-06-01

Hydrocode calculations require knowledge of the variation of pressure of a material with density and temperature, which is given by the equation of state. An accurate model needs to account for discontinuities in energy, density and properties of a material across a phase boundary. When generating a multiphase equation of state the modeller attempts to balance the agreement between the available data for compression, expansion and phase boundary location. However, this can prove difficult because minor adjustments in the equation of state for a single phase can have a large impact on the overall phase diagram. Recently, Cox and Christie described a method for combining statistical-mechanics-based condensed matter physics models with a stochastic analysis technique called particle swarm optimisation. The models produced show good agreement with experiment over a wide range of pressure-temperature space. This talk details the general implementation of this technique, shows example results, and describes the types of analysis that can be performed with this method.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

Stochastic Partial Differential Equation Solver for Hydroacoustic Modeling: Improvements to Paracousti Sound Propagation Solver

NASA Astrophysics Data System (ADS)

Preston, L. A.

2017-12-01

Marine hydrokinetic (MHK) devices offer a clean, renewable alternative energy source for the future. Responsible utilization of MHK devices, however, requires that the effects of acoustic noise produced by these devices on marine life and marine-related human activities be well understood. Paracousti is a 3-D full waveform acoustic modeling suite that can accurately propagate MHK noise signals in the complex bathymetry found in the near-shore to open ocean environment and considers real properties of the seabed, water column, and air-surface interface. However, this is a deterministic simulation that assumes the environment and source are exactly known. In reality, environmental and source characteristics are often only known in a statistical sense. Thus, to fully characterize the expected noise levels within the marine environment, this uncertainty in environmental and source factors should be incorporated into the acoustic simulations. One method is to use Monte Carlo (MC) techniques where simulation results from a large number of deterministic solutions are aggregated to provide statistical properties of the output signal. However, MC methods can be computationally prohibitive since they can require tens of thousands or more simulations to build up an accurate representation of those statistical properties. An alternative method, using the technique of stochastic partial differential equations (SPDE), allows computation of the statistical properties of output signals at a small fraction of the computational cost of MC. We are developing a SPDE solver for the 3-D acoustic wave propagation problem called Paracousti-UQ to help regulators and operators assess the statistical properties of environmental noise produced by MHK devices. In this presentation, we present the SPDE method and compare statistical distributions of simulated acoustic signals in simple models to MC simulations to show the accuracy and efficiency of the SPDE method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Statistical properties of filtered pseudorandom digital sequences formed from the sum of maximum-length sequences

NASA Technical Reports Server (NTRS)

Wallace, G. R.; Weathers, G. D.; Graf, E. R.

1973-01-01

The statistics of filtered pseudorandom digital sequences called hybrid-sum sequences, formed from the modulo-two sum of several maximum-length sequences, are analyzed. The results indicate that a relation exists between the statistics of the filtered sequence and the characteristic polynomials of the component maximum length sequences. An analysis procedure is developed for identifying a large group of sequences with good statistical properties for applications requiring the generation of analog pseudorandom noise. By use of the analysis approach, the filtering process is approximated by the convolution of the sequence with a sum of unit step functions. A parameter reflecting the overall statistical properties of filtered pseudorandom sequences is derived. This parameter is called the statistical quality factor. A computer algorithm to calculate the statistical quality factor for the filtered sequences is presented, and the results for two examples of sequence combinations are included. The analysis reveals that the statistics of the signals generated with the hybrid-sum generator are potentially superior to the statistics of signals generated with maximum-length generators. Furthermore, fewer calculations are required to evaluate the statistics of a large group of hybrid-sum generators than are required to evaluate the statistics of the same size group of approximately equivalent maximum-length sequences.

Study of breast implant rupture: MRI versus surgical findings.

PubMed

Vestito, A; Mangieri, F F; Ancona, A; Minervini, C; Perchinunno, V; Rinaldi, S

2012-09-01

This study evaluated the role of breast magnetic resonance (MR) imaging in the selective study breast implant integrity. We retrospectively analysed the signs of breast implant rupture observed at breast MR examinations of 157 implants and determined the sensitivity and specificity of the technique in diagnosing implant rupture by comparing MR data with findings at surgical explantation. The linguine and the salad-oil signs were statistically the most significant signs for diagnosing intracapsular rupture; the presence of siliconomas/seromas outside the capsule and/or in the axillary lymph nodes calls for immediate explantation. In agreement with previous reports, we found a close correlation between imaging signs and findings at explantation. Breast MR imaging can be considered the gold standard in the study of breast implants.

Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic.

PubMed

Yokoyama, Jun'ichi

2014-01-01

After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student's t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case.

Development and Validation of Instruments to Measure Learning of Expert-Like Thinking

NASA Astrophysics Data System (ADS)

Adams, Wendy K.; Wieman, Carl E.

2011-06-01

This paper describes the process for creating and validating an assessment test that measures the effectiveness of instruction by probing how well that instruction causes students in a class to think like experts about specific areas of science. The design principles and process are laid out and it is shown how these align with professional standards that have been established for educational and psychological testing and the elements of assessment called for in a recent National Research Council study on assessment. The importance of student interviews for creating and validating the test is emphasized, and the appropriate interview procedures are presented. The relevance and use of standard psychometric statistical tests are discussed. Additionally, techniques for effective test administration are presented.

Factors contributing to academic achievement: a Bayesian structure equation modelling study

NASA Astrophysics Data System (ADS)

Payandeh Najafabadi, Amir T.; Omidi Najafabadi, Maryam; Farid-Rohani, Mohammad Reza

2013-06-01

In Iran, high school graduates enter university after taking a very difficult entrance exam called the Konkoor. Therefore, only the top-performing students are admitted by universities to continue their bachelor's education in statistics. Surprisingly, statistically, most of such students fall into the following categories: (1) do not succeed in their education despite their excellent performance on the Konkoor and in high school; (2) graduate with a grade point average (GPA) that is considerably lower than their high school GPA; (3) continue their master's education in majors other than statistics and (4) try to find jobs unrelated to statistics. This article employs the well-known and powerful statistical technique, the Bayesian structural equation modelling (SEM), to study the academic success of recent graduates who have studied statistics at Shahid Beheshti University in Iran. This research: (i) considered academic success as a latent variable, which was measured by GPA and other academic success (see below) of students in the target population; (ii) employed the Bayesian SEM, which works properly for small sample sizes and ordinal variables; (iii), which is taken from the literature, developed five main factors that affected academic success and (iv) considered several standard psychological tests and measured characteristics such as 'self-esteem' and 'anxiety'. We then study the impact of such factors on the academic success of the target population. Six factors that positively impact student academic success were identified in the following order of relative impact (from greatest to least): 'Teaching-Evaluation', 'Learner', 'Environment', 'Family', 'Curriculum' and 'Teaching Knowledge'. Particularly, influential variables within each factor have also been noted.

A promising biotechnical approach to pest management of Diabrotica virgifera virgifera in Illinois maize fields under kairomonal shielding with the new MSD technique.

PubMed

Hummel, H E; Shaw, J T; Hein, D F

2005-01-01

Environmentally compatible and sustainable plant protection requires novel approaches to pest management characterized by minimal emphasis on toxicants. Classical toxicants traditionally dominated economic entomology for half a century. But worldwide problems with environmental pollution and with increasing resistance levels in all major pesticide classes and in many key insect species including Diabrotica virgifera virgifera (D.v.v.) strongly advocate a rethinking and a change in management paradigms used. Soft, minimally invasive, biological, biotechnical and cultural approaches should replace hard pesticides which are in favor up to now. Fortunately, pheromones, kairomones, plant attractants, better traps, new plant varieties and cultural methods like crop rotation, in short more sophisticated methods are now available as pressure for finding and exploring novel strategies increases. Facing this situation, a new biotechnical approach of population reduction of D.v.v., called "MSD" technique, is introduced. MSD is characterized as an approach combining mass trapping, shielding and deflecting of adult insects along an invisible odor barrier of synthetic kairomone which diminishes the flux of insects across a high capacity trap line baited with kairomone, thus reducing both the population fluctuation and number and its reproductive success within the shielded area. In the case of D.v.v. in Zea mays fields, effects realized by the MSD technique have been measured simultaneously by a number of independent criteria during the summers of 2003 and 2004 at 2 different locations in Illinois maize fields of up to one half hectare size. Results observed are statistically significant and cannot be explained by mass trapping alone. There is also an additional shielding and deflection, in short "diversion" effect whose basic sensory and behavioral mechanisms call for future exploration.

Solar granulation and statistical crystallography: A modeling approach using size-shape relations

NASA Technical Reports Server (NTRS)

Noever, D. A.

1994-01-01

The irregular polygonal pattern of solar granulation is analyzed for size-shape relations using statistical crystallography. In contrast to previous work which has assumed perfectly hexagonal patterns for granulation, more realistic accounting of cell (granule) shapes reveals a broader basis for quantitative analysis. Several features emerge as noteworthy: (1) a linear correlation between number of cell-sides and neighboring shapes (called Aboav-Weaire's law); (2) a linear correlation between both average cell area and perimeter and the number of cell-sides (called Lewis's law and a perimeter law, respectively) and (3) a linear correlation between cell area and squared perimeter (called convolution index). This statistical picture of granulation is consistent with a finding of no correlation in cell shapes beyond nearest neighbors. A comparative calculation between existing model predictions taken from luminosity data and the present analysis shows substantial agreements for cell-size distributions. A model for understanding grain lifetimes is proposed which links convective times to cell shape using crystallographic results.

Compact low-noise preamplifier for noise spectroscopy with biased photodiodes in cargo inspection systems

NASA Astrophysics Data System (ADS)

Benetti, Bob; Langeveld, Willem G. J.

2013-09-01

Noise Spectroscopy, a.k.a. Z-determination by Statistical Count-rate ANalysis (Z-SCAN), is a statistical technique to determine a quantity called the "noise figure" from digitized waveforms of pulses of transmitted x-rays in cargo inspection systems. Depending only on quantities related to the x-ray energies, it measures a characteristic of the transmitted x-ray spectrum, which depends on the atomic number, Z, of the material penetrated. The noise figure can thus be used for material separation. In an 80-detector prototype, scintillators are used with large-area photodiodes biased at 80V and digitized using 50-MSPS 12-bit ADC boards. We present an ultra-compact low-noise preamplifier design, with one high-gain and one low-gain channel per detector for improved dynamic range. To achieve adequate detection sensitivity and spatial resolution each dual-gain preamplifier channel must fit within a 12.7 mm wide circuit board footprint and maintain adequate noise immunity to conducted and radiated interference from adjacent channels. The novel design included iterative SPICE analysis of transient response, dynamic range, frequency response, and noise analysis to optimize the selection and configuration of amplifiers and filter response. We discuss low-noise active and passive components and low-noise techniques for circuit board layout that are essential to achieving the design goals, and how the completed circuit board performed in comparison to the predicted responses.

Wavelet analysis of frequency chaos game signal: a time-frequency signature of the C. elegans DNA.

PubMed

Messaoudi, Imen; Oueslati, Afef Elloumi; Lachiri, Zied

2014-12-01

Challenging tasks are encountered in the field of bioinformatics. The choice of the genomic sequence's mapping technique is one the most fastidious tasks. It shows that a judicious choice would serve in examining periodic patterns distribution that concord with the underlying structure of genomes. Despite that, searching for a coding technique that can highlight all the information contained in the DNA has not yet attracted the attention it deserves. In this paper, we propose a new mapping technique based on the chaos game theory that we call the frequency chaos game signal (FCGS). The particularity of the FCGS coding resides in exploiting the statistical properties of the genomic sequence itself. This may reflect important structural and organizational features of DNA. To prove the usefulness of the FCGS approach in the detection of different local periodic patterns, we use the wavelet analysis because it provides access to information that can be obscured by other time-frequency methods such as the Fourier analysis. Thus, we apply the continuous wavelet transform (CWT) with the complex Morlet wavelet as a mother wavelet function. Scalograms that relate to the organism Caenorhabditis elegans (C. elegans) exhibit a multitude of periodic organization of specific DNA sequences.

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

The ground truth about metadata and community detection in networks.

PubMed

Peel, Leto; Larremore, Daniel B; Clauset, Aaron

2017-05-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.

MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data.

PubMed

Murillo, Gabriel H; You, Na; Su, Xiaoquan; Cui, Wei; Reilly, Muredach P; Li, Mingyao; Ning, Kang; Cui, Xinping

2016-05-15

Single nucleotide variant (SNV) detection procedures are being utilized as never before to analyze the recent abundance of high-throughput DNA sequencing data, both on single and multiple sample datasets. Building on previously published work with the single sample SNV caller genotype model selection (GeMS), a multiple sample version of GeMS (MultiGeMS) is introduced. Unlike other popular multiple sample SNV callers, the MultiGeMS statistical model accounts for enzymatic substitution sequencing errors. It also addresses the multiple testing problem endemic to multiple sample SNV calling and utilizes high performance computing (HPC) techniques. A simulation study demonstrates that MultiGeMS ranks highest in precision among a selection of popular multiple sample SNV callers, while showing exceptional recall in calling common SNVs. Further, both simulation studies and real data analyses indicate that MultiGeMS is robust to low-quality data. We also demonstrate that accounting for enzymatic substitution sequencing errors not only improves SNV call precision at low mapping quality regions, but also improves recall at reference allele-dominated sites with high mapping quality. The MultiGeMS package can be downloaded from https://github.com/cui-lab/multigems xinping.cui@ucr.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Spin Glass a Bridge Between Quantum Computation and Statistical Mechanics

NASA Astrophysics Data System (ADS)

Ohzeki, Masayuki

2013-09-01

In this chapter, we show two fascinating topics lying between quantum information processing and statistical mechanics. First, we introduce an elaborated technique, the surface code, to prepare the particular quantum state with robustness against decoherence. Interestingly, the theoretical limitation of the surface code, accuracy threshold, to restore the quantum state has a close connection with the problem on the phase transition in a special model known as spin glasses, which is one of the most active researches in statistical mechanics. The phase transition in spin glasses is an intractable problem, since we must strive many-body system with complicated interactions with change of their signs depending on the distance between spins. Fortunately, recent progress in spin-glass theory enables us to predict the precise location of the critical point, at which the phase transition occurs. It means that statistical mechanics is available for revealing one of the most interesting parts in quantum information processing. We show how to import the special tool in statistical mechanics into the problem on the accuracy threshold in quantum computation. Second, we show another interesting technique to employ quantum nature, quantum annealing. The purpose of quantum annealing is to search for the most favored solution of a multivariable function, namely optimization problem. The most typical instance is the traveling salesman problem to find the minimum tour while visiting all the cities. In quantum annealing, we introduce quantum fluctuation to drive a particular system with the artificial Hamiltonian, in which the ground state represents the optimal solution of the specific problem we desire to solve. Induction of the quantum fluctuation gives rise to the quantum tunneling effect, which allows nontrivial hopping from state to state. We then sketch a strategy to control the quantum fluctuation efficiently reaching the ground state. Such a generic framework is called quantum annealing. The most typical instance is quantum adiabatic computation based on the adiabatic theorem. The quantum adiabatic computation as discussed in the other chapter, unfortunately, has a crucial bottleneck for a part of the optimization problems. We here introduce several recent trials to overcome such a weakpoint by use of developments in statistical mechanics. Through both of the topics, we would shed light on the birth of the interdisciplinary field between quantum mechanics and statistical mechanics.

Statistical analysis of CCSN/SS7 traffic data from working CCS subnetworks

NASA Astrophysics Data System (ADS)

Duffy, Diane E.; McIntosh, Allen A.; Rosenstein, Mark; Willinger, Walter

1994-04-01

In this paper, we report on an ongoing statistical analysis of actual CCSN traffic data. The data consist of approximately 170 million signaling messages collected from a variety of different working CCS subnetworks. The key findings from our analysis concern: (1) the characteristics of both the telephone call arrival process and the signaling message arrival process; (2) the tail behavior of the call holding time distribution; and (3) the observed performance of the CCSN with respect to a variety of performance and reliability measurements.

CALL versus Paper: In Which Context Are L1 Glosses More Effective?

ERIC Educational Resources Information Center

Taylor, Alan M.

2013-01-01

CALL glossing in first language (L1) or second language (L2) texts has been shown by previous studies to be more effective than traditional, paper-and-pen L1 glossing. Using a pool of studies with much more statistical power and more accurate results, this meta-analysis demonstrates more precisely the degree to which CALL L1 glossing can be more…

Analogical Instruction in Statistics: Implications for Social Work Educators

ERIC Educational Resources Information Center

Thomas, Leela

2008-01-01

This paper examines the use of analogies in statistics instruction. Much has been written about the difficulty social work students have with statistics. To address this concern, Glisson and Fischer (1987) called for the use of analogies. Understanding of analogical problem solving has surged in the last few decades with the integration of…

Beneath the Skin: Statistics, Trust, and Status

ERIC Educational Resources Information Center

Smith, Richard

2011-01-01

Overreliance on statistics, and even faith in them--which Richard Smith in this essay calls a branch of "metricophilia"--is a common feature of research in education and in the social sciences more generally. Of course accurate statistics are important, but they often constitute essentially a powerful form of rhetoric. For purposes of analysis and…

InSAR Tropospheric Correction Methods: A Statistical Comparison over Different Regions

NASA Astrophysics Data System (ADS)

Bekaert, D. P.; Walters, R. J.; Wright, T. J.; Hooper, A. J.; Parker, D. J.

2015-12-01

Observing small magnitude surface displacements through InSAR is highly challenging, and requires advanced correction techniques to reduce noise. In fact, one of the largest obstacles facing the InSAR community is related to tropospheric noise correction. Spatial and temporal variations in temperature, pressure, and relative humidity result in a spatially-variable InSAR tropospheric signal, which masks smaller surface displacements due to tectonic or volcanic deformation. Correction methods applied today include those relying on weather model data, GNSS and/or spectrometer data. Unfortunately, these methods are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the high-resolution interferometric phase by assuming a linear or a power-law relationship between the phase and topography. For these methods, the challenge lies in separating deformation from tropospheric signals. We will present results of a statistical comparison of the state-of-the-art tropospheric corrections estimated from spectrometer products (MERIS and MODIS), a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and power-law empirical methods. We evaluate the correction capability over Southern Mexico, Italy, and El Hierro, and investigate the impact of increasing cloud cover on the accuracy of the tropospheric delay estimation. We find that each method has its strengths and weaknesses, and suggest that further developments should aim to combine different correction methods. All the presented methods are included into our new open source software package called TRAIN - Toolbox for Reducing Atmospheric InSAR Noise (Bekaert et al., in review), which is available to the community Bekaert, D., R. Walters, T. Wright, A. Hooper, and D. Parker (in review), Statistical comparison of InSAR tropospheric correction techniques, Remote Sensing of Environment

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

PubMed

Aussem, Alex; de Morais, Sérgio Rodrigues; Corbex, Marilys

2012-01-01

We propose a new graphical framework for extracting the relevant dietary, social and environmental risk factors that are associated with an increased risk of nasopharyngeal carcinoma (NPC) on a case-control epidemiologic study that consists of 1289 subjects and 150 risk factors. This framework builds on the use of Bayesian networks (BNs) for representing statistical dependencies between the random variables. We discuss a novel constraint-based procedure, called Hybrid Parents and Children (HPC), that builds recursively a local graph that includes all the relevant features statistically associated to the NPC, without having to find the whole BN first. The local graph is afterwards directed by the domain expert according to his knowledge. It provides a statistical profile of the recruited population, and meanwhile helps identify the risk factors associated to NPC. Extensive experiments on synthetic data sampled from known BNs show that the HPC outperforms state-of-the-art algorithms that appeared in the recent literature. From a biological perspective, the present study confirms that chemical products, pesticides and domestic fume intake from incomplete combustion of coal and wood are significantly associated with NPC risk. These results suggest that industrial workers are often exposed to noxious chemicals and poisonous substances that are used in the course of manufacturing. This study also supports previous findings that the consumption of a number of preserved food items, like house made proteins and sheep fat, are a major risk factor for NPC. BNs are valuable data mining tools for the analysis of epidemiologic data. They can explicitly combine both expert knowledge from the field and information inferred from the data. These techniques therefore merit consideration as valuable alternatives to traditional multivariate regression techniques in epidemiologic studies. Copyright © 2011 Elsevier B.V. All rights reserved.

High call volume at poison control centers: identification and implications for communication

PubMed Central

CARAVATI, E. M.; LATIMER, S.; REBLIN, M.; BENNETT, H. K. W.; CUMMINS, M. R.; CROUCH, B. I.; ELLINGTON, L.

2016-01-01

Context High volume surges in health care are uncommon and unpredictable events. Their impact on health system performance and capacity is difficult to study. Objectives To identify time periods that exhibited very busy conditions at a poison control center and to determine whether cases and communication during high volume call periods are different from cases during low volume periods. Methods Call data from a US poison control center over twelve consecutive months was collected via a call logger and an electronic case database (Toxicall®). Variables evaluated for high call volume conditions were: (1) call duration; (2) number of cases; and (3) number of calls per staff member per 30 minute period. Statistical analyses identified peak periods as busier than 99% of all other 30 minute time periods and low volume periods as slower than 70% of all other 30 minute periods. Case and communication characteristics of high volume and low volume calls were compared using logistic regression. Results A total of 65,364 incoming calls occurred over 12 months. One hundred high call volume and 4885 low call volume 30 minute periods were identified. High volume periods were more common between 1500 and 2300 hours and during the winter months. Coded verbal communication data were evaluated for 42 high volume and 296 low volume calls. The mean (standard deviation) call length of these calls during high volume and low volume periods was 3 minutes 27 seconds (1 minute 46 seconds) and 3 minutes 57 seconds (2 minutes 11 seconds), respectively. Regression analyses revealed a trend for fewer overall verbal statements and fewer staff questions during peak periods, but no other significant differences for staff-caller communication behaviors were found. Conclusion Peak activity for poison center call volume can be identified by statistical modeling. Calls during high volume periods were similar to low volume calls. Communication was more concise yet staff was able to maintain a good rapport with callers during busy call periods. This approach allows evaluation of poison exposure call characteristics and communication during high volume periods. PMID:22889059

High call volume at poison control centers: identification and implications for communication.

PubMed

Caravati, E M; Latimer, S; Reblin, M; Bennett, H K W; Cummins, M R; Crouch, B I; Ellington, L

2012-09-01

High volume surges in health care are uncommon and unpredictable events. Their impact on health system performance and capacity is difficult to study. To identify time periods that exhibited very busy conditions at a poison control center and to determine whether cases and communication during high volume call periods are different from cases during low volume periods. Call data from a US poison control center over twelve consecutive months was collected via a call logger and an electronic case database (Toxicall®).Variables evaluated for high call volume conditions were: (1) call duration; (2) number of cases; and (3) number of calls per staff member per 30 minute period. Statistical analyses identified peak periods as busier than 99% of all other 30 minute time periods and low volume periods as slower than 70% of all other 30 minute periods. Case and communication characteristics of high volume and low volume calls were compared using logistic regression. A total of 65,364 incoming calls occurred over 12 months. One hundred high call volume and 4885 low call volume 30 minute periods were identified. High volume periods were more common between 1500 and 2300 hours and during the winter months. Coded verbal communication data were evaluated for 42 high volume and 296 low volume calls. The mean (standard deviation) call length of these calls during high volume and low volume periods was 3 minutes 27 seconds (1 minute 46 seconds) and 3 minutes 57 seconds (2 minutes 11 seconds), respectively. Regression analyses revealed a trend for fewer overall verbal statements and fewer staff questions during peak periods, but no other significant differences for staff-caller communication behaviors were found. Peak activity for poison center call volume can be identified by statistical modeling. Calls during high volume periods were similar to low volume calls. Communication was more concise yet staff was able to maintain a good rapport with callers during busy call periods. This approach allows evaluation of poison exposure call characteristics and communication during high volume periods.

Brain Cancer—Patient Version

Cancer.gov

Brain cancer refers to growths of malignant cells in tissues of the brain. Tumors that start in the brain are called primary brain tumors. Tumors that spread to the brain are called metastatic brain tumors. Start here to find information on brain cancer treatment, research, and statistics.

A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments.

PubMed

Ganger, Michael T; Dietz, Geoffrey D; Ewing, Sarah J

2017-12-01

qPCR has established itself as the technique of choice for the quantification of gene expression. Procedures for conducting qPCR have received significant attention; however, more rigorous approaches to the statistical analysis of qPCR data are needed. Here we develop a mathematical model, termed the Common Base Method, for analysis of qPCR data based on threshold cycle values (C q ) and efficiencies of reactions (E). The Common Base Method keeps all calculations in the logscale as long as possible by working with log 10 (E) ∙ C q , which we call the efficiency-weighted C q value; subsequent statistical analyses are then applied in the logscale. We show how efficiency-weighted C q values may be analyzed using a simple paired or unpaired experimental design and develop blocking methods to help reduce unexplained variation. The Common Base Method has several advantages. It allows for the incorporation of well-specific efficiencies and multiple reference genes. The method does not necessitate the pairing of samples that must be performed using traditional analysis methods in order to calculate relative expression ratios. Our method is also simple enough to be implemented in any spreadsheet or statistical software without additional scripts or proprietary components.

Optimization technique for problems with an inequality constraint

NASA Technical Reports Server (NTRS)

Russell, K. J.

1972-01-01

General technique uses a modified version of an existing technique termed the pattern search technique. New procedure called the parallel move strategy permits pattern search technique to be used with problems involving a constraint.

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

NASA Astrophysics Data System (ADS)

Jesse, S.; Chi, M.; Belianinov, A.; Beekman, C.; Kalinin, S. V.; Borisevich, A. Y.; Lupini, A. R.

2016-05-01

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. Here, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in nature and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. However, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data.

PubMed

Vu, Trung N; Valkenborg, Dirk; Smets, Koen; Verwaest, Kim A; Dommisse, Roger; Lemière, Filip; Verschoren, Alain; Goethals, Bart; Laukens, Kris

2011-10-20

Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline. We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data. The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from http://code.google.com/p/speaq/.

Survey of statistical techniques used in validation studies of air pollution prediction models

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

Bornstein, R D; Anderson, S F

1979-03-01

Statistical techniques used by meteorologists to validate predictions made by air pollution models are surveyed. Techniques are divided into the following three groups: graphical, tabular, and summary statistics. Some of the practical problems associated with verification are also discussed. Characteristics desired in any validation program are listed and a suggested combination of techniques that possesses many of these characteristics is presented.

Weather and emotional state: a search for associations between weather and calls to telephone counseling services

NASA Astrophysics Data System (ADS)

Driscoll, Dennis; Stillman, Daniel

2002-08-01

Previous research has revealed that an emotional response to weather might be indicated by calls to telephone counseling services. We analyzed call frequency from such "hotlines", each serving communities in a major metropolitan area of the United States (Detroit, Washington DC, Dallas and Seattle). The periods examined were all, or parts of, the years 1997 and 1998. Associations with subjectively derived synoptic weather types for all cities except Seattle, as well as with individual weather elements [cloudiness (sky cover), precipitation, windspeed, and interdiurnal temperature change] for all four cities, were investigated. Analysis of variance and t-tests (significance of means) were applied to test the statistical significance of differences. Although statistically significant results were obtained in scattered instances, the total number was within that expected by chance, and there was little in the way of consistency to these associations. One clear exception was the increased call frequency during destructive (severe) weather, when there is obvious concern about the damage done by it.

Systems implications of L-band fade data statistics for LEO mobile systems

NASA Technical Reports Server (NTRS)

Devieux, Carrie L.

1993-01-01

This paper examines and analyzes research data on the role of foliage attenuation in signal fading between a satellite transmitter and a terrestrial vehicle-mounted receiver. The frequency band of measurement, called L-Band, includes the region 1610.0 to 1626.5 MHz. Data from tests involving various combinations of foliage and vehicle movement conditions clearly show evidence of fast fading (in excess of 0.5 dB per millisecond) and fade depths as great or greater than 16 dB. As a result, the design of a communications link power control that provides the level of accuracy necessary for power sensitive systems could be significantly impacted. Specific examples of this include the communications links that employ Code Division Multiple Access (CDMA) as a modulation technique.

Learning moment-based fast local binary descriptor

NASA Astrophysics Data System (ADS)

Bellarbi, Abdelkader; Zenati, Nadia; Otmane, Samir; Belghit, Hayet

2017-03-01

Recently, binary descriptors have attracted significant attention due to their speed and low memory consumption; however, using intensity differences to calculate the binary descriptive vector is not efficient enough. We propose an approach to binary description called POLAR_MOBIL, in which we perform binary tests between geometrical and statistical information using moments in the patch instead of the classical intensity binary test. In addition, we introduce a learning technique used to select an optimized set of binary tests with low correlation and high variance. This approach offers high distinctiveness against affine transformations and appearance changes. An extensive evaluation on well-known benchmark datasets reveals the robustness and the effectiveness of the proposed descriptor, as well as its good performance in terms of low computation complexity when compared with state-of-the-art real-time local descriptors.

Systems implications of L-band fade data statistics for LEO mobile systems

NASA Astrophysics Data System (ADS)

Devieux, Carrie L.

This paper examines and analyzes research data on the role of foliage attenuation in signal fading between a satellite transmitter and a terrestrial vehicle-mounted receiver. The frequency band of measurement, called L-Band, includes the region 1610.0 to 1626.5 MHz. Data from tests involving various combinations of foliage and vehicle movement conditions clearly show evidence of fast fading (in excess of 0.5 dB per millisecond) and fade depths as great or greater than 16 dB. As a result, the design of a communications link power control that provides the level of accuracy necessary for power sensitive systems could be significantly impacted. Specific examples of this include the communications links that employ Code Division Multiple Access (CDMA) as a modulation technique.

Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic

PubMed Central

YOKOYAMA, Jun’ichi

2014-01-01

After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student’s t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case. PMID:25504231

Geologic constraints on the upper limits of reserve growth

USGS Publications Warehouse

Stanley, Richard G.

2001-01-01

For many oil and gas fields, estimates of ultimate recovery (the sum of cumulative production plus estimated reserves) tend to increase from one year to the next, and the gain is called reserve growth. Forecasts of reserve growth by the U.S. Geological Survey rely on statistical analyses of historical records of oil and gas production and estimated reserves. The preproposal in this Open-File Report suggests that this traditional petroleum–engineering approach to reserve growth might be supplemented, or at least better understood, by using geological data from individual oil and gas fields, 3–D modeling software, and standard volumetric techniques to estimate in–place volumes of oil and gas. Such estimates, in turn, can be used to constrain the upper limits of reserve growth and ultimate recovery from those fields.

Probabilistic Open Set Recognition

NASA Astrophysics Data System (ADS)

Jain, Lalit Prithviraj

Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary support vector machines. Building from the success of statistical EVT based recognition methods such as PI-SVM and W-SVM on the open set problem, we present a new general supervised learning algorithm for multi-class classification and multi-class open set recognition called the Extreme Value Local Basis (EVLB). The design of this algorithm is motivated by the observation that extrema from known negative class distributions are the closest negative points to any positive sample during training, and thus should be used to define the parameters of a probabilistic decision model. In the EVLB, the kernel distribution for each positive training sample is estimated via an EVT distribution fit over the distances to the separating hyperplane between positive training sample and closest negative samples, with a subset of the overall positive training data retained to form a probabilistic decision boundary. Using this subset as a frame of reference, the probability of a sample at test time decreases as it moves away from the positive class. Possessing this property, the EVLB is well-suited to open set recognition problems where samples from unknown or novel classes are encountered at test. Our experimental evaluation shows that the EVLB provides a substantial improvement in scalability compared to standard radial basis function kernel machines, as well as P I-SVM and W-SVM, with improved accuracy in many cases. We evaluate our algorithm on open set variations of the standard visual learning benchmarks, as well as with an open subset of classes from Caltech 256 and ImageNet. Our experiments show that PI-SVM, WSVM and EVLB provide significant advances over the previous state-of-the-art solutions for the same tasks.

Quantum statistics in complex networks

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

The Barabasi-Albert (BA) model for a complex network shows a characteristic power law connectivity distribution typical of scale free systems. The Ising model on the BA network shows that the ferromagnetic phase transition temperature depends logarithmically on its size. We have introduced a fitness parameter for the BA network which describes the different abilities of nodes to compete for links. This model predicts the formation of a scale free network where each node increases its connectivity in time as a power-law with an exponent depending on its fitness. This model includes the fact that the node connectivity and growth rate do not depend on the node age alone and it reproduces non trivial correlation properties of the Internet. We have proposed a model of bosonic networks by a generalization of the BA model where the properties of quantum statistics can be applied. We have introduced a fitness eta i = e-bei where the temperature T = 1/ b is determined by the noise in the system and the energy ei accounts for qualitative differences of each node for acquiring links. The results of this work show that a power law network with exponent gamma = 2 can give a Bose condensation where a single node grabs a finite fraction of all the links. In order to address the connection with self-organized processes we have introduced a model for a growing Cayley tree that generalizes the dynamics of invasion percolation. At each node we associate a parameter ei (called energy) such that the probability to grow for each node is given by pii ∝ ebei where T = 1/ b is a statistical parameter of the system determined by the noise called the temperature. This model has been solved analytically with a similar mathematical technique as the bosonic scale-free networks and it shows the self organization of the low energy nodes at the interface. In the thermodynamic limit the Fermi distribution describes the probability of the energy distribution at the interface.

Analyzing thematic maps and mapping for accuracy

USGS Publications Warehouse

Rosenfield, G.H.

1982-01-01

Two problems which exist while attempting to test the accuracy of thematic maps and mapping are: (1) evaluating the accuracy of thematic content, and (2) evaluating the effects of the variables on thematic mapping. Statistical analysis techniques are applicable to both these problems and include techniques for sampling the data and determining their accuracy. In addition, techniques for hypothesis testing, or inferential statistics, are used when comparing the effects of variables. A comprehensive and valid accuracy test of a classification project, such as thematic mapping from remotely sensed data, includes the following components of statistical analysis: (1) sample design, including the sample distribution, sample size, size of the sample unit, and sampling procedure; and (2) accuracy estimation, including estimation of the variance and confidence limits. Careful consideration must be given to the minimum sample size necessary to validate the accuracy of a given. classification category. The results of an accuracy test are presented in a contingency table sometimes called a classification error matrix. Usually the rows represent the interpretation, and the columns represent the verification. The diagonal elements represent the correct classifications. The remaining elements of the rows represent errors by commission, and the remaining elements of the columns represent the errors of omission. For tests of hypothesis that compare variables, the general practice has been to use only the diagonal elements from several related classification error matrices. These data are arranged in the form of another contingency table. The columns of the table represent the different variables being compared, such as different scales of mapping. The rows represent the blocking characteristics, such as the various categories of classification. The values in the cells of the tables might be the counts of correct classification or the binomial proportions of these counts divided by either the row totals or the column totals from the original classification error matrices. In hypothesis testing, when the results of tests of multiple sample cases prove to be significant, some form of statistical test must be used to separate any results that differ significantly from the others. In the past, many analyses of the data in this error matrix were made by comparing the relative magnitudes of the percentage of correct classifications, for either individual categories, the entire map or both. More rigorous analyses have used data transformations and (or) two-way classification analysis of variance. A more sophisticated step of data analysis techniques would be to use the entire classification error matrices using the methods of discrete multivariate analysis or of multiviariate analysis of variance.

Effects of an artificially lengthened vocal tract on the glottal closed quotient in untrained male voices

NASA Astrophysics Data System (ADS)

Gaskill, Christopher Somers

The use of hard-walled narrow tubes, often called resonance tubes, for the purpose of voice therapy and voice training has a historical precedent and some theoretical support, but the mechanism of any potential benefit from the application of this technique has remained poorly understood. Fifteen vocally untrained male participants produced a series of spoken /a / vowels at a modal pitch and constant loudness, followed by a minute of repeated phonation into a hard-walled glass tube at the same pitch and loudness targets. The tube parameters and tube phonation task criteria were selected according to theoretical calculations predicting an increase in the acoustic load such that phonation would occur under conditions of near-maximum inertive reactance. Following tube phonation, each participant repeated a similar series of spoken /a/ vowels. Electroglottography (EGG) was used to measure the glottal closed quotient (CQ) during each phase of the experiment. A single-subject, multiple-baseline design with direct replication across subjects was used to identify any changes in CQ across the phases of the experiment. Single-subject analysis using the method of Statistical Process Control (SPC) revealed statistically significant changes in CQ during tube phonation, but with no discernable pattern across the 15 participants. These results indicate that the use of resonance tubes can have a distinct effect on glottal closure, but the mechanism behind this change remains unclear. The implication is that vocal loading techniques such as this need to be studied further with specific attention paid to the underlying mechanism of any measured changes in glottal behavior, and especially to the role of instruction and feedback in the therapeutic and pedagogical application of these techniques.

The Effect on Performance Time and Quality of the Knots after Mono or Bimanual Training of Laparoscopic Intracorporeal Knot Tying according to the Gladiator Rule Technique.

PubMed

Asencio, Fernanda de Almeida; Ribeiro, Helizabet Abdala Salomão Ayroza; Romeo, Armando; Wattiez, Arnauld; Ribeiro, Paulo Augusto Galvão Ayroza

2018-05-18

 To assess whether the monomanual or bimanual training of laparoscopic suture following the same technique may interfere with the knots' performance time and/or quality.  A prospective observational study involving 41 resident students of gynecology/obstetrics and general surgery who attended a laparoscopic suture training for 2 days. The participants were divided into two groups. Group A performed the training using exclusively their dominant hand, and group B performed the training using both hands to tie the intracorporeal knot. All participants followed the same technique, called Romeo Gladiator Rule. At the end of the course, the participants were asked to perform three exercises to assess the time it took them to tie the knots, as well as the quality of the knots.  A comparative analysis of the groups showed that there was no statistically significant difference ( p  = 0.334) between them regarding the length of time to tie one knot. However, when the time to tie 10 consecutive knots was compared, group A was faster than group B ( p  = 0.020). A comparison of the knot loosening average, in millimeters, revealed that the knots made by group B loosened less than those made by group A, but there was no statistically significant difference regarding the number of knots that became untied.  This study demonstrated that the knots from group B showed better quality than those from group A, with lower loosening measures and more strength necessary to untie the knots. The study also demonstrated that group A was faster than B when the time to tie ten consecutive knots was compared. Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil.

The Environmental Data Book: A Guide to Statistics on the Environment and Development.

ERIC Educational Resources Information Center

Sheram, Katherine

This book presents statistics on countries with populations of more than 1 million related to the quality of the environment, economic development, and how each is affected by the other. Sometimes called indicators, the statistics are measures of environmental, economic, and social conditions in developing and industrial countries. The book is…

Tri-Center Analysis: Determining Measures of Trichotomous Central Tendency for the Parametric Analysis of Tri-Squared Test Results

ERIC Educational Resources Information Center

Osler, James Edward

2014-01-01

This monograph provides an epistemological rational for the design of a novel post hoc statistical measure called "Tri-Center Analysis". This new statistic is designed to analyze the post hoc outcomes of the Tri-Squared Test. In Tri-Center Analysis trichotomous parametric inferential parametric statistical measures are calculated from…

The association of drinking water treatment and distribution network disturbances with Health Call Centre contacts for gastrointestinal illness symptoms.

PubMed

Malm, Annika; Axelsson, Gösta; Barregard, Lars; Ljungqvist, Jakob; Forsberg, Bertil; Bergstedt, Olof; Pettersson, Thomas J R

2013-09-01

There are relatively few studies on the association between disturbances in drinking water services and symptoms of gastrointestinal (GI) illness. Health Call Centres data concerning GI illness may be a useful source of information. This study investigates if there is an increased frequency of contacts with the Health Call Centre (HCC) concerning gastrointestinal symptoms at times when there is a risk of impaired water quality due to disturbances at water works or the distribution network. The study was conducted in Gothenburg, a Swedish city with 0.5 million inhabitants with a surface water source of drinking water and two water works. All HCC contacts due to GI symptoms (diarrhoea, vomiting or abdominal pain) were recorded for a three-year period, including also sex, age, and geocoded location of residence. The number of contacts with the HCC in the affected geographical areas were recorded during eight periods of disturbances in the water works (e.g. short stops of chlorine dosing), six periods of large disturbances in the distribution network (e.g. pumping station failure or pipe breaks with major consequences), and 818 pipe break and leak repairs over a three-year period. For each period of disturbance the observed number of calls was compared with the number of calls during a control period without disturbances in the same geographical area. In total about 55, 000 calls to the HCC due to GI symptoms were recorded over the three-year period, 35 per 1000 inhabitants and year, but much higher (>200) for children <3 yrs of age. There was no statistically significant increase in calls due to GI illness during or after disturbances at the water works or in the distribution network. Our results indicate that GI symptoms due to disturbances in water works or the distribution network are rare. The number of serious failures was, however limited, and further studies are needed to be able to assess the risk of GI illness in such cases. The technique of using geocoded HCC data together with geocoded records of disturbances in the drinking water network was feasible. Copyright © 2013 Elsevier Ltd. All rights reserved.

Plasma Cell Neoplasms (Including Multiple Myeloma)—Patient Version

Cancer.gov

Plasma cell neoplasms occur when abnormal plasma cells form cancerous tumors. When there is only one tumor, the disease is called a plasmacytoma. When there are multiple tumors, it is called multiple myeloma. Start here to find information on plasma cell neoplasms treatment, research, and statistics.

78 FR 17469 - Government Securities: Call for Large Position Reports

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-21

... DEPARTMENT OF THE TREASURY Government Securities: Call for Large Position Reports AGENCY: Office... Reserve Bank of New York, Government Securities Dealer Statistics Unit, 4th Floor, 33 Liberty Street, New... Eidemiller, or Kevin Hawkins; Government Securities Regulations Staff, Department of the Treasury, at 202-504...

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mount, David M.

2007-01-01

Interpolating scattered data points is a problem of wide ranging interest. A number of approaches for interpolation have been proposed both from theoretical domains such as computational geometry and in applications' fields such as geostatistics. Our motivation arises from geological and mining applications. In many instances data can be costly to compute and are available only at nonuniformly scattered positions. Because of the high cost of collecting measurements, high accuracy is required in the interpolants. One of the most popular interpolation methods in this field is called ordinary kriging. It is popular because it is a best linear unbiased estimator. The price for its statistical optimality is that the estimator is computationally very expensive. This is because the value of each interpolant is given by the solution of a large dense linear system. In practice, kriging problems have been solved approximately by restricting the domain to a small local neighborhood of points that lie near the query point. Determining the proper size for this neighborhood is a solved by ad hoc methods, and it has been shown that this approach leads to undesirable discontinuities in the interpolant. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. This process achieves its efficiency by replacing the large dense kriging system with a much sparser linear system. This technique has been applied to a restriction of our problem, called simple kriging, which is not unbiased for general data sets. In this paper we generalize these results by showing how to apply covariance tapering to the more general problem of ordinary kriging. Through experimentation we demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined with iterative methods for solving large sparse systems. We demonstrate our approach on large data sizes arising both from synthetic sources and from real applications.

Covert Channels in SIP for VoIP Signalling

NASA Astrophysics Data System (ADS)

Mazurczyk, Wojciech; Szczypiorski, Krzysztof

In this paper, we evaluate available steganographic techniques for SIP (Session Initiation Protocol) that can be used for creating covert channels during signaling phase of VoIP (Voice over IP) call. Apart from characterizing existing steganographic methods we provide new insights by introducing new techniques. We also estimate amount of data that can be transferred in signalling messages for typical IP telephony call.

Probability and Statistics in Sensor Performance Modeling

DTIC Science & Technology

2010-12-01

language software program is called Environmental Awareness for Sensor and Emitter Employment. Some important numerical issues in the implementation...3 Statistical analysis for measuring sensor performance...complementary cumulative distribution function cdf cumulative distribution function DST decision-support tool EASEE Environmental Awareness of

An Artificial Intelligence Approach to Analyzing Student Errors in Statistics.

ERIC Educational Resources Information Center

Sebrechts, Marc M.; Schooler, Lael J.

1987-01-01

Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)

Infinitely divisible cascades to model the statistics of natural images.

PubMed

Chainais, Pierre

2007-12-01

We propose to model the statistics of natural images thanks to the large class of stochastic processes called Infinitely Divisible Cascades (IDC). IDC were first introduced in one dimension to provide multifractal time series to model the so-called intermittency phenomenon in hydrodynamical turbulence. We have extended the definition of scalar infinitely divisible cascades from 1 to N dimensions and commented on the relevance of such a model in fully developed turbulence in [1]. In this article, we focus on the particular 2 dimensional case. IDC appear as good candidates to model the statistics of natural images. They share most of their usual properties and appear to be consistent with several independent theoretical and experimental approaches of the literature. We point out the interest of IDC for applications to procedural texture synthesis.

Chemical databases evaluated by order theoretical tools.

PubMed

Voigt, Kristina; Brüggemann, Rainer; Pudenz, Stefan

2004-10-01

Data on environmental chemicals are urgently needed to comply with the future chemicals policy in the European Union. The availability of data on parameters and chemicals can be evaluated by chemometrical and environmetrical methods. Different mathematical and statistical methods are taken into account in this paper. The emphasis is set on a new, discrete mathematical method called METEOR (method of evaluation by order theory). Application of the Hasse diagram technique (HDT) of the complete data-matrix comprising 12 objects (databases) x 27 attributes (parameters + chemicals) reveals that ECOTOX (ECO), environmental fate database (EFD) and extoxnet (EXT)--also called multi-database databases--are best. Most single databases which are specialised are found in a minimal position in the Hasse diagram; these are biocatalysis/biodegradation database (BID), pesticide database (PES) and UmweltInfo (UMW). The aggregation of environmental parameters and chemicals (equal weight) leads to a slimmer data-matrix on the attribute side. However, no significant differences are found in the "best" and "worst" objects. The whole approach indicates a rather bad situation in terms of the availability of data on existing chemicals and hence an alarming signal concerning the new and existing chemicals policies of the EEC.

Chaos as an intermittently forced linear system.

PubMed

Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kaiser, Eurika; Kutz, J Nathan

2017-05-30

Understanding the interplay of order and disorder in chaos is a central challenge in modern quantitative science. Approximate linear representations of nonlinear dynamics have long been sought, driving considerable interest in Koopman theory. We present a universal, data-driven decomposition of chaos as an intermittently forced linear system. This work combines delay embedding and Koopman theory to decompose chaotic dynamics into a linear model in the leading delay coordinates with forcing by low-energy delay coordinates; this is called the Hankel alternative view of Koopman (HAVOK) analysis. This analysis is applied to the Lorenz system and real-world examples including Earth's magnetic field reversal and measles outbreaks. In each case, forcing statistics are non-Gaussian, with long tails corresponding to rare intermittent forcing that precedes switching and bursting phenomena. The forcing activity demarcates coherent phase space regions where the dynamics are approximately linear from those that are strongly nonlinear.The huge amount of data generated in fields like neuroscience or finance calls for effective strategies that mine data to reveal underlying dynamics. Here Brunton et al.develop a data-driven technique to analyze chaotic systems and predict their dynamics in terms of a forced linear model.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

Jllumina - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data processing.

PubMed

Almeida, Diogo; Skov, Ida; Lund, Jesper; Mohammadnejad, Afsaneh; Silva, Artur; Vandin, Fabio; Tan, Qihua; Baumbach, Jan; Röttger, Richard

2016-10-01

Measuring differential methylation of the DNA is the nowadays most common approach to linking epigenetic modifications to diseases (called epigenome-wide association studies, EWAS). For its low cost, its efficiency and easy handling, the Illumina HumanMethylation450 BeadChip and its successor, the Infinium MethylationEPIC BeadChip, is the by far most popular techniques for conduction EWAS in large patient cohorts. Despite the popularity of this chip technology, raw data processing and statistical analysis of the array data remains far from trivial and still lacks dedicated software libraries enabling high quality and statistically sound downstream analyses. As of yet, only R-based solutions are freely available for low-level processing of the Illumina chip data. However, the lack of alternative libraries poses a hurdle for the development of new bioinformatic tools, in particular when it comes to web services or applications where run time and memory consumption matter, or EWAS data analysis is an integrative part of a bigger framework or data analysis pipeline. We have therefore developed and implemented Jllumina, an open-source Java library for raw data manipulation of Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data, supporting the developer with Java functions covering reading and preprocessing the raw data, down to statistical assessment, permutation tests, and identification of differentially methylated loci. Jllumina is fully parallelizable and publicly available at http://dimmer.compbio.sdu.dk/download.html.

Jllumina - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and MethylationEPIC data processing.

PubMed

Almeida, Diogo; Skov, Ida; Lund, Jesper; Mohammadnejad, Afsaneh; Silva, Artur; Vandin, Fabio; Tan, Qihua; Baumbach, Jan; Röttger, Richard

2016-12-18

Measuring differential methylation of the DNA is the nowadays most common approach to linking epigenetic modifications to diseases (called epigenome-wide association studies, EWAS). For its low cost, its efficiency and easy handling, the Illumina HumanMethylation450 BeadChip and its successor, the Infinium MethylationEPIC BeadChip, is the by far most popular techniques for conduction EWAS in large patient cohorts. Despite the popularity of this chip technology, raw data processing and statistical analysis of the array data remains far from trivial and still lacks dedicated software libraries enabling high quality and statistically sound downstream analyses. As of yet, only R-based solutions are freely available for low-level processing of the Illumina chip data. However, the lack of alternative libraries poses a hurdle for the development of new bioinformatic tools, in particular when it comes to web services or applications where run time and memory consumption matter, or EWAS data analysis is an integrative part of a bigger framework or data analysis pipeline. We have therefore developed and implemented Jllumina, an open-source Java library for raw data manipulation of Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data, supporting the developer with Java functions covering reading and preprocessing the raw data, down to statistical assessment, permutation tests, and identification of differentially methylated loci. Jllumina is fully parallelizable and publicly available at http://dimmer.compbio.sdu.dk/download.html.

77 FR 56710 - Proposed Information Collection (Call Center Satisfaction Survey): Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-13

... DEPARTMENT OF VETERANS AFFAIRS [OMB Control No. 2900-0744] Proposed Information Collection (Call Center Satisfaction Survey): Comment Request AGENCY: Veterans Benefits Administration, Department of... techniques or the use of other forms of information technology. Title: VBA Call Center Satisfaction Survey...

Integrating Statistical and Expert Knowledge to Develop Phenoregions for the Continental United States

NASA Astrophysics Data System (ADS)

Hoffman, F. M.; Kumar, J.; Hargrove, W. W.

2013-12-01

Vegetated ecosystems typically exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and storm disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution to develop phenological signatures of emergent ecological regimes called phenoregions. By applying a unsupervised, quantitative data mining technique to NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. Utilizing spatial overlays with multiple expert-derived maps, this "label-stealing"' technique exploits the knowledge contained in a collection of maps to identify biome characteristics of our statistically derived phenoregions. Generalized land cover maps were produced by combining phenoregions according to their degree of spatial coincidence with expert-developed land cover or biome regions. Goodness-of-fit maps, which show the strength the spatial correspondence, were also generated.

Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics

USGS Publications Warehouse

Antweiler, Ronald C.; Taylor, Howard E.

2008-01-01

The main classes of statistical treatment of below-detection limit (left-censored) environmental data for the determination of basic statistics that have been used in the literature are substitution methods, maximum likelihood, regression on order statistics (ROS), and nonparametric techniques. These treatments, along with using all instrument-generated data (even those below detection), were evaluated by examining data sets in which the true values of the censored data were known. It was found that for data sets with less than 70% censored data, the best technique overall for determination of summary statistics was the nonparametric Kaplan-Meier technique. ROS and the two substitution methods of assigning one-half the detection limit value to censored data or assigning a random number between zero and the detection limit to censored data were adequate alternatives. The use of these two substitution methods, however, requires a thorough understanding of how the laboratory censored the data. The technique of employing all instrument-generated data - including numbers below the detection limit - was found to be less adequate than the above techniques. At high degrees of censoring (greater than 70% censored data), no technique provided good estimates of summary statistics. Maximum likelihood techniques were found to be far inferior to all other treatments except substituting zero or the detection limit value to censored data.

Effect Sizes in Gifted Education Research

ERIC Educational Resources Information Center

Gentry, Marcia; Peters, Scott J.

2009-01-01

Recent calls for reporting and interpreting effect sizes have been numerous, with the 5th edition of the "Publication Manual of the American Psychological Association" (2001) calling for the inclusion of effect sizes to interpret quantitative findings. Many top journals have required that effect sizes accompany claims of statistical significance.…

Post-processing of auditory steady-state responses to correct spectral leakage.

PubMed

Felix, Leonardo Bonato; de Sá, Antonio Mauricio Ferreira Leite Miranda; Mendes, Eduardo Mazoni Andrade Marçal; Moraes, Márcio Flávio Dutra

2009-06-30

Auditory steady-state responses (ASSRs) are electrical manifestations of brain due to high rate sound stimulation. These evoked responses can be used to assess the hearing capabilities of a subject in an objective, automatic fashion. Usually, the detection protocol is accomplished by frequency-domain techniques, such as magnitude-squared coherence, whose estimation is based on the fast Fourier transform (FFT) of several data segments. In practice, the FFT-based spectrum may spread out the energy of a given frequency to its side bins and this escape of energy in the spectrum is called spectral leakage. The distortion of the spectrum due to leakage may severely compromise statistical significance of objective detection. This work presents an offline, a posteriori method for spectral leakage minimization in the frequency-domain analysis of ASSRs using coherent sampling criterion and interpolation in time. The technique was applied to the local field potentials of 10 Wistar rats and the results, together with those from simulated data, indicate that a leakage-free analysis of ASSRs is possible for any dataset if the methods showed in this paper were followed.

Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA)

PubMed Central

Maznah, Zainol; Halimah, Muhamad; Shitan, Mahendran; Kumar Karmokar, Provash; Najwa, Sulaiman

2017-01-01

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil. PMID:28060816

Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).

PubMed

Maznah, Zainol; Halimah, Muhamad; Shitan, Mahendran; Kumar Karmokar, Provash; Najwa, Sulaiman

2017-01-01

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil.

Interactive lesion segmentation with shape priors from offline and online learning.

PubMed

Shepherd, Tony; Prince, Simon J D; Alexander, Daniel C

2012-09-01

In medical image segmentation, tumors and other lesions demand the highest levels of accuracy but still call for the highest levels of manual delineation. One factor holding back automatic segmentation is the exemption of pathological regions from shape modelling techniques that rely on high-level shape information not offered by lesions. This paper introduces two new statistical shape models (SSMs) that combine radial shape parameterization with machine learning techniques from the field of nonlinear time series analysis. We then develop two dynamic contour models (DCMs) using the new SSMs as shape priors for tumor and lesion segmentation. From training data, the SSMs learn the lower level shape information of boundary fluctuations, which we prove to be nevertheless highly discriminant. One of the new DCMs also uses online learning to refine the shape prior for the lesion of interest based on user interactions. Classification experiments reveal superior sensitivity and specificity of the new shape priors over those previously used to constrain DCMs. User trials with the new interactive algorithms show that the shape priors are directly responsible for improvements in accuracy and reductions in user demand.

Small fenestra stapedectomy. A preliminary report.

PubMed

Bailey, H A; Pappas, J J; Graham, S S

1981-08-01

The small fenestra stapedectomy is based on a rationale of creating a more effective acoustical mechanical transmission system, while reducing potential labyrinthine disturbance. Surgical technique for the small fenestra stapedectomy is described, including the creation of the fenestra and the use of McGee stainless steel piston prosthesis with loose areolar tissue around the piston. Postoperative results are compared in a series of 100 cases, 50 having the small fenestra technique, SFT, and 50 having partial or total footplate removal procedure. Vestibular results demonstrate a noticeable reduction in postoperative complaints of balance disorders in the SFT patients. Hearing results, when compared between the two groups, show a statistically significant advantage for the SFT patients in postoperative high frequency threshold sensitivity and speech discrimination scores. Technical difficulties in creating the fenestra without fracturing the entire footplate are discussed and suggestions made for their avoidance. The advantages of lowered risk, based on reduced trauma to and contamination of the labyrinth, as well as improved high frequency hearing sensitivity and speech discrimination, support the use of this procedure and call for further investigation and development of its clinical potential.

Anomaly-based intrusion detection for SCADA systems

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

Yang, D.; Usynin, A.; Hines, J. W.

2006-07-01

Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper willmore » briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)« less

A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

NASA Astrophysics Data System (ADS)

Zack, J. W.

2015-12-01

Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble, which is a case-matching scheme. The presentation will provide (1) an overview of each method and the experimental design, (2) performance comparisons based on standard metrics such as bias, MAE and RMSE, (3) a summary of the performance characteristics of each approach and (4) a preview of further experiments to be conducted.

CAPSAS: Computer Assisted Program for the Selection of Appropriate Statistics.

ERIC Educational Resources Information Center

Shermis, Mark D.; Albert, Susan L.

A computer-assisted program has been developed for the selection of statistics or statistical techniques by both students and researchers. Based on Andrews, Klem, Davidson, O'Malley and Rodgers "A Guide for Selecting Statistical Techniques for Analyzing Social Science Data," this FORTRAN-compiled interactive computer program was…

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

An empirical analysis of the corporate call decision

NASA Astrophysics Data System (ADS)

Carlson, Murray Dean

1998-12-01

In this thesis we provide insights into the behavior of financial managers of utility companies by studying their decisions to redeem callable preferred shares. In particular, we investigate whether or not an option pricing based model of the call decision, with managers who maximize shareholder value, does a better job of explaining callable preferred share prices and call decisions than do other models of the decision. In order to perform these tests, we extend an empirical technique introduced by Rust (1987) to include the use of information from preferred share prices in addition to the call decisions. The model we develop to value the option embedded in a callable preferred share differs from standard models in two ways. First, as suggested in Kraus (1983), we explicitly account for transaction costs associated with a redemption. Second, we account for state variables that are observed by the decision makers but not by the preferred shareholders. We interpret these unobservable state variables as the benefits and costs associated with a change in capital structure that can accompany a call decision. When we add this variable, our empirical model changes from one which predicts exactly when a share should be called to one which predicts the probability of a call as the function of the observable state. These two modifications of the standard model result in predictions of calls, and therefore of callable preferred share prices, that are consistent with several previously unexplained features of the data; we show that the predictive power of the model is improved in a statistical sense by adding these features to the model. The pricing and call probability functions from our model do a good job of describing call decisions and preferred share prices for several utilities. Using data from shares of the Pacific Gas and Electric Co. (PGE) we obtain reasonable estimates for the transaction costs associated with a call. Using a formal empirical test, we are able to conclude that the managers of the Pacific Gas and Electric Company clearly take into account the value of the option to delay the call when making their call decisions. Overall, the model seems to be robust to tests of its specification and does a better job of describing the data than do simpler models of the decision making process. Limitations in the data do not allow us to perform the same tests in a larger cross-section of utility companies. However, we are able to estimate transaction cost parameters for many firms and these do not seem to vary significantly from those of PGE. This evidence does not cause us to reject our hypothesis that managerial behavior is consistent with a model in which managers maximize shareholder value.

The ground truth about metadata and community detection in networks

PubMed Central

Peel, Leto; Larremore, Daniel B.; Clauset, Aaron

2017-01-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system’s components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks’ links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures. PMID:28508065

Reinventing Biostatistics Education for Basic Scientists

PubMed Central

Weissgerber, Tracey L.; Garovic, Vesna D.; Milin-Lazovic, Jelena S.; Winham, Stacey J.; Obradovic, Zoran; Trzeciakowski, Jerome P.; Milic, Natasa M.

2016-01-01

Numerous studies demonstrating that statistical errors are common in basic science publications have led to calls to improve statistical training for basic scientists. In this article, we sought to evaluate statistical requirements for PhD training and to identify opportunities for improving biostatistics education in the basic sciences. We provide recommendations for improving statistics training for basic biomedical scientists, including: 1. Encouraging departments to require statistics training, 2. Tailoring coursework to the students’ fields of research, and 3. Developing tools and strategies to promote education and dissemination of statistical knowledge. We also provide a list of statistical considerations that should be addressed in statistics education for basic scientists. PMID:27058055

BAYESIAN SEMI-BLIND COMPONENT SEPARATION FOR FOREGROUND REMOVAL IN INTERFEROMETRIC 21 cm OBSERVATIONS

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

Zhang, Le; Timbie, Peter T.; Bunn, Emory F.

In this paper, we present a new Bayesian semi-blind approach for foreground removal in observations of the 21 cm signal measured by interferometers. The technique, which we call H i Expectation–Maximization Independent Component Analysis (HIEMICA), is an extension of the Independent Component Analysis technique developed for two-dimensional (2D) cosmic microwave background maps to three-dimensional (3D) 21 cm cosmological signals measured by interferometers. This technique provides a fully Bayesian inference of power spectra and maps and separates the foregrounds from the signal based on the diversity of their power spectra. Relying only on the statistical independence of the components, this approachmore » can jointly estimate the 3D power spectrum of the 21 cm signal, as well as the 2D angular power spectrum and the frequency dependence of each foreground component, without any prior assumptions about the foregrounds. This approach has been tested extensively by applying it to mock data from interferometric 21 cm intensity mapping observations under idealized assumptions of instrumental effects. We also discuss the impact when the noise properties are not known completely. As a first step toward solving the 21 cm power spectrum analysis problem, we compare the semi-blind HIEMICA technique to the commonly used Principal Component Analysis. Under the same idealized circumstances, the proposed technique provides significantly improved recovery of the power spectrum. This technique can be applied in a straightforward manner to all 21 cm interferometric observations, including epoch of reionization measurements, and can be extended to single-dish observations as well.« less

AI in CALL--Artificially Inflated or Almost Imminent?

ERIC Educational Resources Information Center

Schulze, Mathias

2008-01-01

The application of techniques from artificial intelligence (AI) to CALL has commonly been referred to as intelligent CALL (ICALL). ICALL is only slightly older than the "CALICO Journal", and this paper looks back at a quarter century of published research mainly in North America and by North American scholars. This "inventory…

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Peplinski, Jesse; Koch, Patrick N.; Allen, Janet K.

1997-01-01

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

Environmental statistics and optimal regulation

NASA Astrophysics Data System (ADS)

Sivak, David; Thomson, Matt

2015-03-01

The precision with which an organism can detect its environment, and the timescale for and statistics of environmental change, will affect the suitability of different strategies for regulating protein levels in response to environmental inputs. We propose a general framework--here applied to the enzymatic regulation of metabolism in response to changing nutrient concentrations--to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, and the costs associated with enzyme production. We find: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

Incorporating principal component analysis into air quality ...

EPA Pesticide Factsheets

The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Principal Component Analysis (PCA) with the intent of motivating its use by the evaluation community. One of the main objectives of PCA is to identify, through data reduction, the recurring and independent modes of variations (or signals) within a very large dataset, thereby summarizing the essential information of that dataset so that meaningful and descriptive conclusions can be made. In this demonstration, PCA is applied to a simple evaluation metric – the model bias associated with EPA's Community Multi-scale Air Quality (CMAQ) model when compared to weekly observations of sulfate (SO42−) and ammonium (NH4+) ambient air concentrations measured by the Clean Air Status and Trends Network (CASTNet). The advantages of using this technique are demonstrated as it identifies strong and systematic patterns of CMAQ model bias across a myriad of spatial and temporal scales that are neither constrained to geopolitical boundaries nor monthly/seasonal time periods (a limitation of many current studies). The technique also identifies locations (station–grid cell pairs) that are used as indicators for a more thorough diagnostic evaluation thereby hastening and facilitating understanding of the prob

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

PubMed

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Hanson, Stephen José; Haxby, James V.; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

The effect of an artificially lengthened vocal tract on estimated glottal contact quotient in untrained male voices.

PubMed

Gaskill, Christopher S; Erickson, Molly L

2010-01-01

The use of hard-walled narrow tubes, often called resonance tubes, for the purpose of voice therapy and voice training has a historical precedent and some theoretical support, but the mechanism of any potential benefit from the application of this technique is not well understood. Fifteen vocally untrained male participants produced a series of spoken /a/ vowels at a modal pitch and constant loudness, before and after a minute of repeated phonation into a 50-cm hard-walled glass tube at the same pitch and loudness targets. Electroglottography was used to measure the glottal contact quotient (CQ) during each phase of the experiment. Single-subject analysis revealed statistically significant changes in CQ during tube phonation, but with no discernable pattern across the 15 participants. These results indicate that the use of resonance tubes can have a distinct effect on glottal closure, but the mechanism behind this change remains unclear. The implication is that vocal loading techniques such as this need to be studied further with specific attention paid to the underlying mechanism of any measured changes in glottal behavior, and especially to the role of instruction and feedback in the therapeutic and pedagogical application of these techniques. Copyright 2010 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Modern approaches to the treatment of human infertility through assisted reproduction.

PubMed

Fernández Pelegrina, R; Kessler, A G; Rawlins, R G

1991-08-01

Medical statistics from the United States show approximately 15 percent of all couples of reproductive age are unable to conceive naturally. In recent years, the numbers of couples with reproductive problems has increased, principally due to changes in life style and delayed childbearing. Only 13 years after the birth of the first "test tube baby", advances in the field of human reproduction have created a wide range of alternatives to help infertile couples conceive a healthy infant. Together, these techniques are called Assisted Reproductive Technology (ART) and include: in vitro fertilization (IVF), intratubal transfer of gametes (GIFT), intratubal transfer of zygotes (ZIFT), tubal transfer of preimplantation embryos (TET), gamete or embryo donation, cryopreservtion, and micromanipulation. The application of these techniques is presented here. While much remains to be learned, the ability to fertilize ova in vitro and sustain early embryonic life outside the body is now a reality. Contrary to the idea that these techniques create life in vitro, they simply remove barriers caused by different forms of infertility which impede the creation of life. More than 30,000 infants have now been produced world-wide through ART. In the future, new developments in the field of assisted reproduction promise to bring new hope to the growing numbers of infertile couples around the world.

Focusing on the golden ball metaheuristic: an extended study on a wider set of problems.

PubMed

Osaba, E; Diaz, F; Carballedo, R; Onieva, E; Perallos, A

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results.

Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems

PubMed Central

Osaba, E.; Diaz, F.; Carballedo, R.; Onieva, E.; Perallos, A.

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results. PMID:25165742

Data communications in a parallel active messaging interface of a parallel computer

DOEpatents

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-11-12

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

Static Methods in the Design of Nonlinear Automatic Control Systems,

DTIC Science & Technology

1984-06-27

227 Chapter VI. Ways of Decrease of the Number of Statistical Nodes During the Research of Nonlinear Systems...at present occupies the central place. This region of research was called the statistical dynamics of nonlinear H automatic control systems...receives further development in the numerous research of Soviet and C foreign scientists. Special role in the development of the statistical dynamics of

Bio-inspired computational heuristics to study Lane-Emden systems arising in astrophysics model.

PubMed

Ahmad, Iftikhar; Raja, Muhammad Asif Zahoor; Bilal, Muhammad; Ashraf, Farooq

2016-01-01

This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane-Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network, sub-part of large field called soft computing, is exploited for modelling of the equation in an unsupervised manner. The proposed approximated solutions of higher order ordinary differential equation are calculated with the weights of neural networks trained with genetic algorithm, and pattern search hybrid with sequential quadratic programming for rapid local convergence. The results of proposed solvers for solving the nonlinear singular systems are in good agreements with the standard solutions. Accuracy and convergence the design schemes are demonstrated by the results of statistical performance measures based on the sufficient large number of independent runs.

Combined slope ratio analysis and linear-subtraction: An extension of the Pearce ratio method

NASA Astrophysics Data System (ADS)

De Waal, Sybrand A.

1996-07-01

A new technique, called combined slope ratio analysis, has been developed by extending the Pearce element ratio or conserved-denominator method (Pearce, 1968) to its logical conclusions. If two stoichiometric substances are mixed and certain chemical components are uniquely contained in either one of the two mixing substances, then by treating these unique components as conserved, the composition of the substance not containing the relevant component can be accurately calculated within the limits allowed by analytical and geological error. The calculated composition can then be subjected to rigorous statistical testing using the linear-subtraction method recently advanced by Woronow (1994). Application of combined slope ratio analysis to the rocks of the Uwekahuna Laccolith, Hawaii, USA, and the lavas of the 1959-summit eruption of Kilauea Volcano, Hawaii, USA, yields results that are consistent with field observations.

Auditing Complex Concepts in Overlapping Subsets of SNOMED

PubMed Central

Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A.; Hripcsak, George

2008-01-01

Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries. PMID:18998838

Auditing complex concepts in overlapping subsets of SNOMED.

PubMed

Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A; Hripcsak, George

2008-11-06

Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED's Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries.

75 FR 7445 - Pacific Fishery Management Council; Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-19

... to Order 1. Opening Remarks and Introductions 2. Roll Call 3. Executive Director's Report 4. Approve... Permits for 2010 SCHEDULE OF ANCILLARY MEETINGS Friday, March 5, 2010 Scientific and Statistical Committee... California Ballroom Salon 2 Scientific and Statistical Committee 8 am California Ballroom Salon 4 Legislative...

ASURV: Astronomical SURVival Statistics

NASA Astrophysics Data System (ADS)

Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

2014-06-01

ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

Normalization, bias correction, and peak calling for ChIP-seq

PubMed Central

Diaz, Aaron; Park, Kiyoub; Lim, Daniel A.; Song, Jun S.

2012-01-01

Next-generation sequencing is rapidly transforming our ability to profile the transcriptional, genetic, and epigenetic states of a cell. In particular, sequencing DNA from the immunoprecipitation of protein-DNA complexes (ChIP-seq) and methylated DNA (MeDIP-seq) can reveal the locations of protein binding sites and epigenetic modifications. These approaches contain numerous biases which may significantly influence the interpretation of the resulting data. Rigorous computational methods for detecting and removing such biases are still lacking. Also, multi-sample normalization still remains an important open problem. This theoretical paper systematically characterizes the biases and properties of ChIP-seq data by comparing 62 separate publicly available datasets, using rigorous statistical models and signal processing techniques. Statistical methods for separating ChIP-seq signal from background noise, as well as correcting enrichment test statistics for sequence-dependent and sonication biases, are presented. Our method effectively separates reads into signal and background components prior to normalization, improving the signal-to-noise ratio. Moreover, most peak callers currently use a generic null model which suffers from low specificity at the sensitivity level requisite for detecting subtle, but true, ChIP enrichment. The proposed method of determining a cell type-specific null model, which accounts for cell type-specific biases, is shown to be capable of achieving a lower false discovery rate at a given significance threshold than current methods. PMID:22499706

MV-OPES: Multivalued-Order Preserving Encryption Scheme: A Novel Scheme for Encrypting Integer Value to Many Different Values

NASA Astrophysics Data System (ADS)

Kadhem, Hasan; Amagasa, Toshiyuki; Kitagawa, Hiroyuki

Encryption can provide strong security for sensitive data against inside and outside attacks. This is especially true in the “Database as Service” model, where confidentiality and privacy are important issues for the client. In fact, existing encryption approaches are vulnerable to a statistical attack because each value is encrypted to another fixed value. This paper presents a novel database encryption scheme called MV-OPES (Multivalued — Order Preserving Encryption Scheme), which allows privacy-preserving queries over encrypted databases with an improved security level. Our idea is to encrypt a value to different multiple values to prevent statistical attacks. At the same time, MV-OPES preserves the order of the integer values to allow comparison operations to be directly applied on encrypted data. Using calculated distance (range), we propose a novel method that allows a join query between relations based on inequality over encrypted values. We also present techniques to offload query execution load to a database server as much as possible, thereby making a better use of server resources in a database outsourcing environment. Our scheme can easily be integrated with current database systems as it is designed to work with existing indexing structures. It is robust against statistical attack and the estimation of true values. MV-OPES experiments show that security for sensitive data can be achieved with reasonable overhead, establishing the practicability of the scheme.

Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data.

PubMed

Jayaswal, Vivek; Lutherborrow, Mark; Ma, David D F; Hwa Yang, Yee

2009-05-01

Over the past decade, a class of small RNA molecules called microRNAs (miRNAs) has been shown to regulate gene expression at the post-transcription stage. While early work focused on the identification of miRNAs using a combination of experimental and computational techniques, subsequent studies have focused on identification of miRNA-target mRNA pairs as each miRNA can have hundreds of mRNA targets. The experimental validation of some miRNAs as oncogenic has provided further motivation for research in this area. In this article we propose an odds-ratio (OR) statistic for identification of regulatory miRNAs. It is based on integrative analysis of matched miRNA and mRNA time-course microarray data. The OR-statistic was used for (i) identification of miRNAs with regulatory potential, (ii) identification of miRNA-target mRNA pairs and (iii) identification of time lags between changes in miRNA expression and those of its target mRNAs. We applied the OR-statistic to a cancer data set and identified a small set of miRNAs that were negatively correlated to mRNAs. A literature survey revealed that some of the miRNAs that were predicted to be regulatory, were indeed oncogenic or tumor suppressors. Finally, some of the predicted miRNA targets have been shown to be experimentally valid.

Offset Stream Technology Test-Summary of Results

NASA Technical Reports Server (NTRS)

Brown, Clifford A.; Bridges, James E.; Henderson, Brenda

2007-01-01

Statistical jet noise prediction codes that accurately predict spectral directivity for both cold and hot jets are highly sought both in industry and academia. Their formulation, whether based upon manipulations of the Navier-Stokes equations or upon heuristic arguments, require substantial experimental observation of jet turbulence statistics. Unfortunately, the statistics of most interest involve the space-time correlation of flow quantities, especially velocity. Until the last 10 years, all turbulence statistics were made with single-point probes, such as hotwires or laser Doppler anemometry. Particle image velocimetry (PIV) brought many new insights with its ability to measure velocity fields over large regions of jets simultaneously; however, it could not measure velocity at rates higher than a few fields per second, making it unsuitable for obtaining temporal spectra and correlations. The development of time-resolved PIV, herein called TR-PIV, has removed this limitation, enabling measurement of velocity fields at high resolution in both space and time. In this paper, ground-breaking results from the application of TR-PIV to single-flow hot jets are used to explore the impact of heat on turbulent statistics of interest to jet noise models. First, a brief summary of validation studies is reported, undertaken to show that the new technique produces the same trusted results as hotwire at cold, low-speed jets. Second, velocity spectra from cold and hot jets are compared to see the effect of heat on the spectra. It is seen that heated jets possess 10 percent more turbulence intensity compared to the unheated jets with the same velocity. The spectral shapes, when normalized using Strouhal scaling, are insensitive to temperature if the stream-wise location is normalized relative to the potential core length. Similarly, second order velocity correlations, of interest in modeling of jet noise sources, are also insensitive to temperature as well.

Effect of Temperature on Jet Velocity Spectra

NASA Technical Reports Server (NTRS)

Bridges, James E.; Wernet, Mark P.

2007-01-01

Statistical jet noise prediction codes that accurately predict spectral directivity for both cold and hot jets are highly sought both in industry and academia. Their formulation, whether based upon manipulations of the Navier-Stokes equations or upon heuristic arguments, require substantial experimental observation of jet turbulence statistics. Unfortunately, the statistics of most interest involve the space-time correlation of flow quantities, especially velocity. Until the last 10 years, all turbulence statistics were made with single-point probes, such as hotwires or laser Doppler anemometry. Particle image velocimetry (PIV) brought many new insights with its ability to measure velocity fields over large regions of jets simultaneously; however, it could not measure velocity at rates higher than a few fields per second, making it unsuitable for obtaining temporal spectra and correlations. The development of time-resolved PIV, herein called TR-PIV, has removed this limitation, enabling measurement of velocity fields at high resolution in both space and time. In this paper, ground-breaking results from the application of TR-PIV to single-flow hot jets are used to explore the impact of heat on turbulent statistics of interest to jet noise models. First, a brief summary of validation studies is reported, undertaken to show that the new technique produces the same trusted results as hotwire at cold, low-speed jets. Second, velocity spectra from cold and hot jets are compared to see the effect of heat on the spectra. It is seen that heated jets possess 10 percent more turbulence intensity compared to the unheated jets with the same velocity. The spectral shapes, when normalized using Strouhal scaling, are insensitive to temperature if the stream-wise location is normalized relative to the potential core length. Similarly, second order velocity correlations, of interest in modeling of jet noise sources, are also insensitive to temperature as well.

A comparison in Colorado of three methods to monitor breeding amphibians

USGS Publications Warehouse

Corn, P.S.; Muths, E.; Iko, W.M.

2000-01-01

We surveyed amphibians at 4 montane and 2 plains lentic sites in northern Colorado using 3 techniques: standardized call surveys, automated recording devices (frog-loggers), and intensive surveys including capture-recapture techniques. Amphibians were observed at 5 sites. Species richness varied from 0 to 4 species at each site. Richness scores, the sums of species richness among sites, were similar among methods: 8 for call surveys, 10 for frog-loggers, and 11 for intensive surveys (9 if the non-vocal salamander Ambystoma tigrinum is excluded). The frog-logger at 1 site recorded Spea bombifrons which was not active during the times when call and intensive surveys were conducted. Relative abundance scores from call surveys failed to reflect a relatively large population of Bufo woodhousii at 1 site and only weakly differentiated among different-sized populations of Pseudacris maculata at 3 other sites. For extensive applications, call surveys have the lowest costs and fewest requirements for highly trained personnel. However, for a variety of reasons, call surveys cannot be used with equal effectiveness in all parts of North America.

A non-parametric peak calling algorithm for DamID-Seq.

PubMed

Li, Renhua; Hempel, Leonie U; Jiang, Tingbo

2015-01-01

Protein-DNA interactions play a significant role in gene regulation and expression. In order to identify transcription factor binding sites (TFBS) of double sex (DSX)-an important transcription factor in sex determination, we applied the DNA adenine methylation identification (DamID) technology to the fat body tissue of Drosophila, followed by deep sequencing (DamID-Seq). One feature of DamID-Seq data is that induced adenine methylation signals are not assured to be symmetrically distributed at TFBS, which renders the existing peak calling algorithms for ChIP-Seq, including SPP and MACS, inappropriate for DamID-Seq data. This challenged us to develop a new algorithm for peak calling. A challenge in peaking calling based on sequence data is estimating the averaged behavior of background signals. We applied a bootstrap resampling method to short sequence reads in the control (Dam only). After data quality check and mapping reads to a reference genome, the peaking calling procedure compromises the following steps: 1) reads resampling; 2) reads scaling (normalization) and computing signal-to-noise fold changes; 3) filtering; 4) Calling peaks based on a statistically significant threshold. This is a non-parametric method for peak calling (NPPC). We also used irreproducible discovery rate (IDR) analysis, as well as ChIP-Seq data to compare the peaks called by the NPPC. We identified approximately 6,000 peaks for DSX, which point to 1,225 genes related to the fat body tissue difference between female and male Drosophila. Statistical evidence from IDR analysis indicated that these peaks are reproducible across biological replicates. In addition, these peaks are comparable to those identified by use of ChIP-Seq on S2 cells, in terms of peak number, location, and peaks width.

Structurally Sound Statistics Instruction

ERIC Educational Resources Information Center

Casey, Stephanie A.; Bostic, Jonathan D.

2016-01-01

The Common Core's Standards for Mathematical Practice (SMP) call for all K-grade 12 students to develop expertise in the processes and proficiencies of doing mathematics. However, the Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010) as a whole addresses students' learning of not only mathematics but also statistics. This situation…

ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM (EMAP): WESTERN STREAMS AND RIVERS STATISTICAL SUMMARY

EPA Science Inventory

This statistical summary reports data from the Environmental Monitoring and Assessment Program (EMAP) Western Pilot (EMAP-W). EMAP-W was a sample survey (or probability survey, often simply called 'random') of streams and rivers in 12 states of the western U.S. (Arizona, Californ...

Survival analysis, or what to do with upper limits in astronomical surveys

NASA Technical Reports Server (NTRS)

Isobe, Takashi; Feigelson, Eric D.

1986-01-01

A field of applied statistics called survival analysis has been developed over several decades to deal with censored data, which occur in astronomical surveys when objects are too faint to be detected. How these methods can assist in the statistical interpretation of astronomical data are reviewed.

Soldier Decision-Making for Allocation of Intelligence, Surveillance, and Reconnaissance Assets

DTIC Science & Technology

2014-06-01

Judgments; also called Algoritmic or Statistical Judgements Computer Science , Psychology, and Statistics Actuarial or algorithmic...Jan. 2011. [17] R. M. Dawes, D. Faust, and P. E. Meehl, “Clinical versus Actuarial Judgment,” Science , vol. 243, no. 4899, pp. 1668–1674, 1989. [18...School of Computer Science

17 CFR Appendix A to Part 145 - Compilation of Commission Records Available to the Public

Code of Federal Regulations, 2011 CFR

2011-04-01

... photographs. (10) Statistical data concerning the Commission's budget. (11) Statistical data concerning...) Complaint packages, which contain the Reparation Rules, Brochure “Questions and Answers About How You Can... grain reports. (2) Weekly cotton or call reports. (f) Division of Enforcement. Complaint package...

Comparative Analysis Between Computed and Conventional Inferior Alveolar Nerve Block Techniques.

PubMed

Araújo, Gabriela Madeira; Barbalho, Jimmy Charles Melo; Dias, Tasiana Guedes de Souza; Santos, Thiago de Santana; Vasconcellos, Ricardo José de Holanda; de Morais, Hécio Henrique Araújo

2015-11-01

The aim of this randomized, double-blind, controlled trial was to compare the computed and conventional inferior alveolar nerve block techniques in symmetrically positioned inferior third molars. Both computed and conventional anesthetic techniques were performed in 29 healthy patients (58 surgeries) aged between 18 and 40 years. The anesthetic of choice was 2% lidocaine with 1: 200,000 epinephrine. The Visual Analogue Scale assessed the pain variable after anesthetic infiltration. Patient satisfaction was evaluated using the Likert Scale. Heart and respiratory rates, mean time to perform technique, and the need for additional anesthesia were also evaluated. Pain variable means were higher for the conventional technique as compared with computed, 3.45 ± 2.73 and 2.86 ± 1.96, respectively, but no statistically significant differences were found (P > 0.05). Patient satisfaction showed no statistically significant differences. The average computed technique runtime and the conventional were 3.85 and 1.61 minutes, respectively, showing statistically significant differences (P <0.001). The computed anesthetic technique showed lower mean pain perception, but did not show statistically significant differences when contrasted to the conventional technique.

A climatology of total ozone mapping spectrometer data using rotated principal component analysis

NASA Astrophysics Data System (ADS)

Eder, Brian K.; Leduc, Sharon K.; Sickles, Joseph E.

1999-02-01

The spatial and temporal variability of total column ozone (Ω) obtained from the total ozone mapping spectrometer (TOMS version 7.0) during the period 1980-1992 was examined through the use of a multivariate statistical technique called rotated principal component analysis. Utilization of Kaiser's varimax orthogonal rotation led to the identification of 14, mostly contiguous subregions that together accounted for more than 70% of the total Ω variance. Each subregion displayed statistically unique Ω characteristics that were further examined through time series and spectral density analyses, revealing significant periodicities on semiannual, annual, quasi-biennial, and longer term time frames. This analysis facilitated identification of the probable mechanisms responsible for the variability of Ω within the 14 homogeneous subregions. The mechanisms were either dynamical in nature (i.e., advection associated with baroclinic waves, the quasi-biennial oscillation, or El Niño-Southern Oscillation) or photochemical in nature (i.e., production of odd oxygen (O or O3) associated with the annual progression of the Sun). The analysis has also revealed that the influence of a data retrieval artifact, found in equatorial latitudes of version 6.0 of the TOMS data, has been reduced in version 7.0.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

NASA Astrophysics Data System (ADS)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

Role of hydrogen in volatile behaviour of defects in SiO2-based electronic devices

NASA Astrophysics Data System (ADS)

Wimmer, Yannick; El-Sayed, Al-Moatasem; Gös, Wolfgang; Grasser, Tibor; Shluger, Alexander L.

2016-06-01

Charge capture and emission by point defects in gate oxides of metal-oxide-semiconductor field-effect transistors (MOSFETs) strongly affect reliability and performance of electronic devices. Recent advances in experimental techniques used for probing defect properties have led to new insights into their characteristics. In particular, these experimental data show a repeated dis- and reappearance (the so-called volatility) of the defect-related signals. We use multiscale modelling to explain the charge capture and emission as well as defect volatility in amorphous SiO2 gate dielectrics. We first briefly discuss the recent experimental results and use a multiphonon charge capture model to describe the charge-trapping behaviour of defects in silicon-based MOSFETs. We then link this model to ab initio calculations that investigate the three most promising defect candidates. Statistical distributions of defect characteristics obtained from ab initio calculations in amorphous SiO2 are compared with the experimentally measured statistical properties of charge traps. This allows us to suggest an atomistic mechanism to explain the experimentally observed volatile behaviour of defects. We conclude that the hydroxyl-E' centre is a promising candidate to explain all the observed features, including defect volatility.

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

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

Jesse, S.; Chi, M.; Belianinov, A.

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. In this paper, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO 3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in naturemore » and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. Finally, however, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.« less

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

DOE PAGES

Jesse, S.; Chi, M.; Belianinov, A.; ...

2016-05-23

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. In this paper, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO 3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in naturemore » and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. Finally, however, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.« less

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

PubMed Central

Jesse, S.; Chi, M.; Belianinov, A.; Beekman, C.; Kalinin, S. V.; Borisevich, A. Y.; Lupini, A. R.

2016-01-01

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. Here, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in nature and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. However, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy. PMID:27211523

A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

NASA Astrophysics Data System (ADS)

Guillen, George; Rainey, Gail; Morin, Michelle

2004-04-01

Currently, the Minerals Management Service uses the Oil Spill Risk Analysis model (OSRAM) to predict the movement of potential oil spills greater than 1000 bbl originating from offshore oil and gas facilities. OSRAM generates oil spill trajectories using meteorological and hydrological data input from either actual physical measurements or estimates generated from other hydrological models. OSRAM and many other models produce output matrices of average, maximum and minimum contact probabilities to specific landfall or target segments (columns) from oil spills at specific points (rows). Analysts and managers are often interested in identifying geographic areas or groups of facilities that pose similar risks to specific targets or groups of targets if a spill occurred. Unfortunately, due to the potentially large matrix generated by many spill models, this question is difficult to answer without the use of data reduction and visualization methods. In our study we utilized a multivariate statistical method called cluster analysis to group areas of similar risk based on potential distribution of landfall target trajectory probabilities. We also utilized ArcView™ GIS to display spill launch point groupings. The combination of GIS and multivariate statistical techniques in the post-processing of trajectory model output is a powerful tool for identifying and delineating areas of similar risk from multiple spill sources. We strongly encourage modelers, statistical and GIS software programmers to closely collaborate to produce a more seamless integration of these technologies and approaches to analyzing data. They are complimentary methods that strengthen the overall assessment of spill risks.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Multidisciplinary Responses to the Sexual Victimization of Children: Use of Control Phone Calls.

PubMed

Canavan, J William; Borowski, Christine; Essex, Stacy; Perkowski, Stefan

2017-10-01

This descriptive study addresses the question of the value of one-party consent phone calls regarding the sexual victimization of children. The authors reviewed 4 years of experience with children between the ages of 3 and 18 years selected for the control phone calls after a forensic interview by the New York State Police forensic interviewer. The forensic interviewer identified appropriate cases for control phone calls considering New York State law, the child's capacity to make the call, the presence of another person to make the call and a supportive residence. The control phone call process has been extremely effective forensically. Offenders choose to avoid trial by taking a plea bargain thereby dramatically speeding up the criminal judicial and family court processes. An additional outcome of the control phone call is the alleged offender's own words saved the child from the trauma of testifying in court. The control phone call reduced the need for children to repeat their stories to various interviewers. A successful control phone call gives the child a sense of vindication. This technique is the only technique that preserves the actual communication pattern between the alleged victim and the alleged offender. This can be of great value to the mental health professionals working with both the child and the alleged offender. Cautions must be considered regarding potential serious adverse effects on the child. The multidisciplinary team members must work together in the control phone call. The descriptive nature of this study did not allow the authors adequate demographic data, a subject that should be addressed in future prospective study.

Descriptive Statistical Techniques for Librarians. 2nd Edition.

ERIC Educational Resources Information Center

Hafner, Arthur W.

A thorough understanding of the uses and applications of statistical techniques is integral in gaining support for library funding or new initiatives. This resource is designed to help practitioners develop and manipulate descriptive statistical information in evaluating library services, tracking and controlling limited resources, and analyzing…

Understanding Summary Statistics and Graphical Techniques to Compare Michael Jordan versus LeBron James

ERIC Educational Resources Information Center

Williams, Immanuel James; Williams, Kelley Kim

2016-01-01

Understanding summary statistics and graphical techniques are building blocks to comprehending concepts beyond basic statistics. It's known that motivated students perform better in school. Using examples that students find engaging allows them to understand the concepts at a deeper level.

Effect of call organization on burnout and quality of life in psychiatry residents.

PubMed

Scarella, Timothy M; Nelligan, Julia; Roberts, Jacqueline; Boland, Robert J

2017-02-01

We aimed to measure the effects of a residency program's mid-year shift from 24-h call to night float on resident burnout and quality of life. At the end of the year, residents who started the year with 24-h call had worse burnout and quality of life, with statistical significance and large effect sizes. Exposure to a twenty-four hour call system, when compared to a full year of night float, may be associated with increased burnout and decreased quality of life, though measuring this effect is not straightforward. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

Encoding techniques for complex information structures in connectionist systems

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

Two general information encoding techniques called relative position encoding and pattern similarity association are presented. They are claimed to be a convenient basis for the connectionist implementation of complex, short term information processing of the sort needed in common sense reasoning, semantic/pragmatic interpretation of natural language utterances, and other types of high level cognitive processing. The relationships of the techniques to other connectionist information-structuring methods, and also to methods used in computers, are discussed in detail. The rich inter-relationships of these other connectionist and computer methods are also clarified. The particular, simple forms are discussed that the relative position encoding and pattern similarity association techniques take in the author's own connectionist system, called Conposit, in order to clarify some issues and to provide evidence that the techniques are indeed useful in practice.

Collecting and Analyzing Patient Experiences of Health Care From Social Media.

PubMed

Rastegar-Mojarad, Majid; Ye, Zhan; Wall, Daniel; Murali, Narayana; Lin, Simon

2015-07-02

Social Media, such as Yelp, provides rich information of consumer experience. Previous studies suggest that Yelp can serve as a new source to study patient experience. However, the lack of a corpus of patient reviews causes a major bottleneck for applying computational techniques. The objective of this study is to create a corpus of patient experience (COPE) and report descriptive statistics to characterize COPE. Yelp reviews about health care-related businesses were extracted from the Yelp Academic Dataset. Natural language processing (NLP) tools were used to split reviews into sentences, extract noun phrases and adjectives from each sentence, and generate parse trees and dependency trees for each sentence. Sentiment analysis techniques and Hadoop were used to calculate a sentiment score of each sentence and for parallel processing, respectively. COPE contains 79,173 sentences from 6914 patient reviews of 985 health care facilities near 30 universities in the United States. We found that patients wrote longer reviews when they rated the facility poorly (1 or 2 stars). We demonstrated that the computed sentiment scores correlated well with consumer-generated ratings. A consumer vocabulary to describe their health care experience was constructed by a statistical analysis of word counts and co-occurrences in COPE. A corpus called COPE was built as an initial step to utilize social media to understand patient experiences at health care facilities. The corpus is available to download and COPE can be used in future studies to extract knowledge of patients' experiences from their perspectives. Such information can subsequently inform and provide opportunity to improve the quality of health care.

Pathogenesis-based treatments in primary Sjogren's syndrome using artificial intelligence and advanced machine learning techniques: a systematic literature review.

PubMed

Foulquier, Nathan; Redou, Pascal; Le Gal, Christophe; Rouvière, Bénédicte; Pers, Jacques-Olivier; Saraux, Alain

2018-05-17

Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade. An automatic bibliography screening method has been developed to perform this task. The program called BIBOT was designed to fetch and analyze articles from the pubmed database using a list of keywords and Natural Language Processing approaches. The evolution of trends in statistical approaches, sizes of cohorts and number of publications over this period were also computed in the process. In all, 44077 abstracts were screened and 1017 publications were analyzed. The mean number of selected articles was 101.0 (S.D. 19.16) by year, but increased significantly over the time (from 74 articles in 2008 to 138 in 2017). Among them only 12 focused on pSS but none of them emphasized on the aspect of pathogenesis-based treatments. To conclude, medicine progressively enters the era of big data analysis and artificial intelligence, but these approaches are not yet used to describe pSS-specific pathogenesis-based treatment. Nevertheless, large multicentre studies are investigating this aspect with advanced algorithmic tools on large cohorts of SADs patients.

ALCF Data Science Program: Productive Data-centric Supercomputing

NASA Astrophysics Data System (ADS)

Romero, Nichols; Vishwanath, Venkatram

The ALCF Data Science Program (ADSP) is targeted at big data science problems that require leadership computing resources. The goal of the program is to explore and improve a variety of computational methods that will enable data-driven discoveries across all scientific disciplines. The projects will focus on data science techniques covering a wide area of discovery including but not limited to uncertainty quantification, statistics, machine learning, deep learning, databases, pattern recognition, image processing, graph analytics, data mining, real-time data analysis, and complex and interactive workflows. Project teams will be among the first to access Theta, ALCFs forthcoming 8.5 petaflops Intel/Cray system. The program will transition to the 200 petaflop/s Aurora supercomputing system when it becomes available. In 2016, four projects have been selected to kick off the ADSP. The selected projects span experimental and computational sciences and range from modeling the brain to discovering new materials for solar-powered windows to simulating collision events at the Large Hadron Collider (LHC). The program will have a regular call for proposals with the next call expected in Spring 2017.http://www.alcf.anl.gov/alcf-data-science-program This research used resources of the ALCF, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.

A new approach to characterize very-low-level radioactive waste produced at hadron accelerators.

PubMed

Zaffora, Biagio; Magistris, Matteo; Chevalier, Jean-Pierre; Luccioni, Catherine; Saporta, Gilbert; Ulrici, Luisa

2017-04-01

Radioactive waste is produced as a consequence of preventive and corrective maintenance during the operation of high-energy particle accelerators or associated dismantling campaigns. Their radiological characterization must be performed to ensure an appropriate disposal in the disposal facilities. The radiological characterization of waste includes the establishment of the list of produced radionuclides, called "radionuclide inventory", and the estimation of their activity. The present paper describes the process adopted at CERN to characterize very-low-level radioactive waste with a focus on activated metals. The characterization method consists of measuring and estimating the activity of produced radionuclides either by experimental methods or statistical and numerical approaches. We adapted the so-called Scaling Factor (SF) and Correlation Factor (CF) techniques to the needs of hadron accelerators, and applied them to very-low-level metallic waste produced at CERN. For each type of metal we calculated the radionuclide inventory and identified the radionuclides that most contribute to hazard factors. The methodology proposed is of general validity, can be extended to other activated materials and can be used for the characterization of waste produced in particle accelerators and research centres, where the activation mechanisms are comparable to the ones occurring at CERN. Copyright © 2017 Elsevier Ltd. All rights reserved.

Expert Systems on Multiprocessor Architectures. Volume 4. Technical Reports

DTIC Science & Technology

1991-06-01

Floated-Current-Time0 -> The time that this function is called in user time uflts, expressed as a floating point number. Halt- Poligono Arrests the...default a statistics file will be printed out, if it can be. To prevent this make No-Statistics true. Unhalt- Poligono Unarrests the process in which the

78 FR 30922 - Agency Information Collection Activities: Submission for OMB Review; Joint Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-23

..., Division of Research and Statistics, Board of Governors of the Federal Reserve System, 20th and C Streets... individual institutions and the industry as a whole. Call Report data provide the most current statistical data available for evaluating institutions' corporate applications, identifying areas of focus for on...

Factors Contributing to Academic Achievement: A Bayesian Structure Equation Modelling Study

ERIC Educational Resources Information Center

Payandeh Najafabadi, Amir T.; Najafabadi, Maryam Omidi; Farid-Rohani, Mohammad Reza

2013-01-01

In Iran, high school graduates enter university after taking a very difficult entrance exam called the Konkoor. Therefore, only the top-performing students are admitted by universities to continue their bachelor's education in statistics. Surprisingly, statistically, most of such students fall into the following categories: (1) do not succeed in…

A Computer-Assisted Instruction in Teaching Abstract Statistics to Public Affairs Undergraduates

ERIC Educational Resources Information Center

Ozturk, Ali Osman

2012-01-01

This article attempts to demonstrate the applicability of a computer-assisted instruction supported with simulated data in teaching abstract statistical concepts to political science and public affairs students in an introductory research methods course. The software is called the Elaboration Model Computer Exercise (EMCE) in that it takes a great…

Hispanics in 1979--A Statistical Appraisal.

ERIC Educational Resources Information Center

Martinez, Douglas R.

1979-01-01

Public Law 94-311, passed by Congress in 1976, called for the expansion of statistics reflecting the socioeconomic status of Hispanics. The article discusses the state of the Hispanic community in early 1979, one agency's difficulties in implementing the mandates of P.L. 94-311, and the status of other agencies' work on the law's requirements. (NQ)

75 FR 29517 - Pacific Fishery Management Council; Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-26

... Remarks and Introductions 2. Roll Call 3. Executive Director's Report 4. Approve Agenda B. Groundfish... and Statistical Committee 8 a.m Habitat Committee 8:30 a.m Budget Committee 1:15 p.m Saturday, June 12... Statistical Committee 8 a.m Council Chair's Reception 6 p.m Sunday, June 13, 2010 California State Delegation...

75 FR 51240 - Pacific Fishery Management Council; Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-19

... Remarks and Introductions 2. Council Member Appointments 3. Roll Call 4. Executive Director's Report 5... Technical Team/Salmon Amendment Committee Joint 8 a.m. Session Scientific and Statistical Committee 8 a.m.... Salmon Technical Team 8 a.m. Scientific and Statistical Committee 8 a.m. Enforcement Consultants 4:30 p.m...

Statistical Literacy for Active Citizenship: A Call for Data Science Education

ERIC Educational Resources Information Center

Engel, Joachim

2017-01-01

Data are abundant, quantitative information about the state of society and the wider world is around us more than ever. Paradoxically, recent trends in the public discourse point towards a post-factual world that seems content to ignore or misrepresent empirical evidence. As statistics educators we are challenged to promote understanding of…

Guide to Using Onionskin Analysis Code (U)

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

Fugate, Michael Lynn; Morzinski, Jerome Arthur

2016-09-15

This document is a guide to using R-code written for the purpose of analyzing onionskin experiments. We expect the user to be very familiar with statistical methods and the R programming language. For more details about onionskin experiments and the statistical methods mentioned in this document see Storlie, Fugate, et al. (2013). Engineers at LANL experiment with detonators and high explosives to assess performance. The experimental unit, called an onionskin, is a hemisphere consisting of a detonator and a booster pellet surrounded by explosive material. When the detonator explodes, a streak camera mounted above the pole of the hemisphere recordsmore » when the shock wave arrives at the surface. The output from the camera is a two-dimensional image that is transformed into a curve that shows the arrival time as a function of polar angle. The statistical challenge is to characterize a baseline population of arrival time curves and to compare the baseline curves to curves from a new, so-called, test series. The hope is that the new test series of curves is statistically similar to the baseline population.« less

MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2014-01-01

MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free-magnetic-energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the "Present MAG4" technique and each of three alternative techniques, called "McIntosh Active-Region Class," "Total Magnetic Flux," and "Next MAG4." We do this by using (1) the MAG4 database of magnetograms and major-flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique-performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4).

Educator and participant perceptions and cost analysis of stage-tailored educational telephone calls.

PubMed

Esters, Onikia N; Boeckner, Linda S; Hubert, Melanie; Horacek, Tanya; Kritsch, Karen R; Oakland, Mary J; Lohse, Barbara; Greene, Geoffrey; Nitzke, Susan

2008-01-01

To identify strengths and weaknesses of nutrition education via telephone calls as part of a larger stage-of-change tailored intervention with mailed materials. Evaluative feedback was elicited from educators who placed the calls and respondents who received the calls. An internet and telephone survey of 10 states in the midwestern United States. 21 educators in 10 states reached via the internet and 50 young adults reached via telephone. VARIABLES MEASURED AND ANALYSIS: Rankings of intervention components, ratings of key aspects of educational calls, and cost data (as provided by a lead researcher in each state) were summarized via descriptive statistics. RESULTS, CONCLUSIONS, AND IMPLICATIONS: Educational calls used 6 to 17 minutes of preparation time, required 8 to 15 minutes of contact time, and had a mean estimated cost of $5.82 per call. Low-income young adults favored print materials over educational calls. However, the calls were reported to have positive effects on motivating participants to set goals. Educators who use educational telephone calls to reach young adults, a highly mobile target audience, may require a robust and flexible contact plan.

No Place to Call Home: Child & Youth Homelessness in the United States. Poverty Fact Sheet

ERIC Educational Resources Information Center

Damron, Neil

2015-01-01

"No Place to Call Home: Child and Youth Homelessness in the United States," prepared by intern Neil Damron and released in May 2015, presents the statistics on child and youth homelessness and recent trends in Wisconsin and the United States. It explores the major challenges faced by homeless minors, and, drawing from recent research by…

Preventive Intervention in Families at Risk: The Limits of Liberalism

ERIC Educational Resources Information Center

Snik, Ger; De Jong, Johan; Van Haaften, Wouter

2004-01-01

There is an increasing call for preventive state interventions in so-called families at risk - that is, interventions before any overt harm has been done by parents to their children or by the children to a third party, in families that are statistically known to be liable to harm children. One of the basic principles of liberal morality, however,…

Nonlinear acoustics in cicada mating calls enhance sound propagation.

PubMed

Hughes, Derke R; Nuttall, Albert H; Katz, Richard A; Carter, G Clifford

2009-02-01

An analysis of cicada mating calls, measured in field experiments, indicates that the very high levels of acoustic energy radiated by this relatively small insect are mainly attributed to the nonlinear characteristics of the signal. The cicada emits one of the loudest sounds in all of the insect population with a sound production system occupying a physical space typically less than 3 cc. The sounds made by tymbals are amplified by the hollow abdomen, functioning as a tuned resonator, but models of the signal based solely on linear techniques do not fully account for a sound radiation capability that is so disproportionate to the insect's size. The nonlinear behavior of the cicada signal is demonstrated by combining the mutual information and surrogate data techniques; the results obtained indicate decorrelation when the phase-randomized and non-phase-randomized data separate. The Volterra expansion technique is used to fit the nonlinearity in the insect's call. The second-order Volterra estimate provides further evidence that the cicada mating calls are dominated by nonlinear characteristics and also suggests that the medium contributes to the cicada's efficient sound propagation. Application of the same principles has the potential to improve radiated sound levels for sonar applications.

Methods and materials, for locating and studying spotted owls.

Treesearch

Eric D. Forsman

1983-01-01

Nocturnal calling surveys are the most effective and most frequently used technique for locating spotted owls. Roosts and general nest locations may be located during the day by calling in suspected roost or nest areas. Specific nest trees are located by: (1) baiting with a live mouse to induce owls to visit the nest, (2) calling in suspected nest areas to stimulate...

What Does CALL Have to Offer Computer Science and What Does Computer Science Have to Offer CALL?

ERIC Educational Resources Information Center

Cushion, Steve

2006-01-01

We will argue that CALL can usefully be viewed as a subset of computer software engineering and can profit from adopting some of the recent progress in software development theory. The unified modelling language has become the industry standard modelling technique and the accompanying unified process is rapidly gaining acceptance. The manner in…

Chi-squared and C statistic minimization for low count per bin data

NASA Astrophysics Data System (ADS)

Nousek, John A.; Shue, David R.

1989-07-01

Results are presented from a computer simulation comparing two statistical fitting techniques on data samples with large and small counts per bin; the results are then related specifically to X-ray astronomy. The Marquardt and Powell minimization techniques are compared by using both to minimize the chi-squared statistic. In addition, Cash's C statistic is applied, with Powell's method, and it is shown that the C statistic produces better fits in the low-count regime than chi-squared.

Chi-squared and C statistic minimization for low count per bin data. [sampling in X ray astronomy

NASA Technical Reports Server (NTRS)

Nousek, John A.; Shue, David R.

1989-01-01

Results are presented from a computer simulation comparing two statistical fitting techniques on data samples with large and small counts per bin; the results are then related specifically to X-ray astronomy. The Marquardt and Powell minimization techniques are compared by using both to minimize the chi-squared statistic. In addition, Cash's C statistic is applied, with Powell's method, and it is shown that the C statistic produces better fits in the low-count regime than chi-squared.

Red-shouldered hawk occupancy surveys in central Minnesota, USA

USGS Publications Warehouse

Henneman, C.; McLeod, M.A.; Andersen, D.E.

2007-01-01

Forest-dwelling raptors are often difficult to detect because many species occur at low density or are secretive. Broadcasting conspecific vocalizations can increase the probability of detecting forest-dwelling raptors and has been shown to be an effective method for locating raptors and assessing their relative abundance. Recent advances in statistical techniques based on presence-absence data use probabilistic arguments to derive probability of detection when it is <1 and to provide a model and likelihood-based method for estimating proportion of sites occupied. We used these maximum-likelihood models with data from red-shouldered hawk (Buteo lineatus) call-broadcast surveys conducted in central Minnesota, USA, in 1994-1995 and 2004-2005. Our objectives were to obtain estimates of occupancy and detection probability 1) over multiple sampling seasons (yr), 2) incorporating within-season time-specific detection probabilities, 3) with call type and breeding stage included as covariates in models of probability of detection, and 4) with different sampling strategies. We visited individual survey locations 2-9 times per year, and estimates of both probability of detection (range = 0.28-0.54) and site occupancy (range = 0.81-0.97) varied among years. Detection probability was affected by inclusion of a within-season time-specific covariate, call type, and breeding stage. In 2004 and 2005 we used survey results to assess the effect that number of sample locations, double sampling, and discontinued sampling had on parameter estimates. We found that estimates of probability of detection and proportion of sites occupied were similar across different sampling strategies, and we suggest ways to reduce sampling effort in a monitoring program.

Morphometricity as a measure of the neuroanatomical signature of a trait.

PubMed

Sabuncu, Mert R; Ge, Tian; Holmes, Avram J; Smoller, Jordan W; Buckner, Randy L; Fischl, Bruce

2016-09-27

Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer's disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Sampling designs for HIV molecular epidemiology with application to Honduras.

PubMed

Shepherd, Bryan E; Rossini, Anthony J; Soto, Ramon Jeremias; De Rivera, Ivette Lorenzana; Mullins, James I

2005-11-01

Proper sampling is essential to characterize the molecular epidemiology of human immunodeficiency virus (HIV). HIV sampling frames are difficult to identify, so most studies use convenience samples. We discuss statistically valid and feasible sampling techniques that overcome some of the potential for bias due to convenience sampling and ensure better representation of the study population. We employ a sampling design called stratified cluster sampling. This first divides the population into geographical and/or social strata. Within each stratum, a population of clusters is chosen from groups, locations, or facilities where HIV-positive individuals might be found. Some clusters are randomly selected within strata and individuals are randomly selected within clusters. Variation and cost help determine the number of clusters and the number of individuals within clusters that are to be sampled. We illustrate the approach through a study designed to survey the heterogeneity of subtype B strains in Honduras.

Comparative Analysis of Document level Text Classification Algorithms using R

NASA Astrophysics Data System (ADS)

Syamala, Maganti; Nalini, N. J., Dr; Maguluri, Lakshamanaphaneendra; Ragupathy, R., Dr.

2017-08-01

From the past few decades there has been tremendous volumes of data available in Internet either in structured or unstructured form. Also, there is an exponential growth of information on Internet, so there is an emergent need of text classifiers. Text mining is an interdisciplinary field which draws attention on information retrieval, data mining, machine learning, statistics and computational linguistics. And to handle this situation, a wide range of supervised learning algorithms has been introduced. Among all these K-Nearest Neighbor(KNN) is efficient and simplest classifier in text classification family. But KNN suffers from imbalanced class distribution and noisy term features. So, to cope up with this challenge we use document based centroid dimensionality reduction(CentroidDR) using R Programming. By combining these two text classification techniques, KNN and Centroid classifiers, we propose a scalable and effective flat classifier, called MCenKNN which works well substantially better than CenKNN.

Morphometricity as a measure of the neuroanatomical signature of a trait

PubMed Central

Sabuncu, Mert R.; Ge, Tian; Holmes, Avram J.; Smoller, Jordan W.; Buckner, Randy L.; Fischl, Bruce

2016-01-01

Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques. PMID:27613854

Latent morpho-semantic analysis : multilingual information retrieval with character n-grams and mutual information.

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

Bader, Brett William; Chew, Peter A.; Abdelali, Ahmed

We describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related previous approaches such as Latent Semantic Analysis (LSA). LMSA has an important theoretical advantage over LSA: it combines well-known techniques in a novel way to break the terms of LSA down into units which correspond more closely to morphemes. Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. We show through empirical results that the theoretical advantages of LMSA can translate into significant gains in precisionmore » in multilingual information retrieval tests. These gains are not matched either when a standard stemmer is used with LSA, or when terms are indiscriminately broken down into n-grams.« less

Consistent Partial Least Squares Path Modeling via Regularization.

PubMed

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

On fitting the Pareto Levy distribution to stock market index data: Selecting a suitable cutoff value

NASA Astrophysics Data System (ADS)

Coronel-Brizio, H. F.; Hernández-Montoya, A. R.

2005-08-01

The so-called Pareto-Levy or power-law distribution has been successfully used as a model to describe probabilities associated to extreme variations of stock markets indexes worldwide. The selection of the threshold parameter from empirical data and consequently, the determination of the exponent of the distribution, is often done using a simple graphical method based on a log-log scale, where a power-law probability plot shows a straight line with slope equal to the exponent of the power-law distribution. This procedure can be considered subjective, particularly with regard to the choice of the threshold or cutoff parameter. In this work, a more objective procedure based on a statistical measure of discrepancy between the empirical and the Pareto-Levy distribution is presented. The technique is illustrated for data sets from the New York Stock Exchange (DJIA) and the Mexican Stock Market (IPC).

Identification of Genes Involved in Breast Cancer Metastasis by Integrating Protein-Protein Interaction Information with Expression Data.

PubMed

Tian, Xin; Xin, Mingyuan; Luo, Jian; Liu, Mingyao; Jiang, Zhenran

2017-02-01

The selection of relevant genes for breast cancer metastasis is critical for the treatment and prognosis of cancer patients. Although much effort has been devoted to the gene selection procedures by use of different statistical analysis methods or computational techniques, the interpretation of the variables in the resulting survival models has been limited so far. This article proposes a new Random Forest (RF)-based algorithm to identify important variables highly related with breast cancer metastasis, which is based on the important scores of two variable selection algorithms, including the mean decrease Gini (MDG) criteria of Random Forest and the GeneRank algorithm with protein-protein interaction (PPI) information. The new gene selection algorithm can be called PPIRF. The improved prediction accuracy fully illustrated the reliability and high interpretability of gene list selected by the PPIRF approach.

Dissimilar material joining using laser (aluminum to steel using zinc-based filler wire)

NASA Astrophysics Data System (ADS)

Mathieu, Alexandre; Shabadi, Rajashekar; Deschamps, Alexis; Suery, Michel; Matteï, Simone; Grevey, Dominique; Cicala, Eugen

2007-04-01

Joining steel with aluminum involving the fusion of one or both materials is possible by laser beam welding technique. This paper describes a method, called laser braze welding, which is a suitable process to realize this structure. The main problem with thermal joining of steel/aluminum assembly with processes such as TIG or MIG is the formation of fragile intermetallic phases, which are detrimental to the mechanical performances of such joints. Braze welding permits a localized fusion of the materials resulting in a limitation on the growth of fragile phases. This article presents the results of a statistical approach for an overlap assembly configuration using a filler wire composed of 85% Zn and 15% Al. Tensile tests carried on these assemblies demonstrate a good performance of the joints. The fracture mechanisms of the joints are analyzed by a detailed characterization of the seams.

The Importance of Introductory Statistics Students Understanding Appropriate Sampling Techniques

ERIC Educational Resources Information Center

Menil, Violeta C.

2005-01-01

In this paper the author discusses the meaning of sampling, the reasons for sampling, the Central Limit Theorem, and the different techniques of sampling. Practical and relevant examples are given to make the appropriate sampling techniques understandable to students of Introductory Statistics courses. With a thorough knowledge of sampling…

Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

ERIC Educational Resources Information Center

Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

2006-01-01

In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

Change Detection in Rough Time Series

DTIC Science & Technology

2014-09-01

Business Statistics : An Inferential Approach, Dellen: San Francisco. [18] Winston, W. (1997) Operations Research Applications and Algorithms, Duxbury...distribution that can present significant challenges to conventional statistical tracking techniques. To address this problem the proposed method...applies hybrid fuzzy statistical techniques to series granules instead of to individual measures. Three examples demonstrated the robust nature of the

Enhancing Students' Ability to Use Statistical Reasoning with Everyday Problems

ERIC Educational Resources Information Center

Lawson, Timothy J.; Schwiers, Michael; Doellman, Maureen; Grady, Greg; Kelnhofer, Robert

2003-01-01

We discuss a technique for teaching students everyday applications of statistical concepts. We used this technique with students (n = 50) enrolled in several sections of an introductory statistics course; students (n = 45) in other sections served as a comparison group. A class of introductory psychology students (n = 24) served as a second…

Making Sense of 'Big Data' in Provenance Studies

NASA Astrophysics Data System (ADS)

Vermeesch, P.

2014-12-01

Huge online databases can be 'mined' to reveal previously hidden trends and relationships in society. One could argue that sedimentary geology has entered a similar era of 'Big Data', as modern provenance studies routinely apply multiple proxies to dozens of samples. Just like the Internet, sedimentary geology now requires specialised statistical tools to interpret such large datasets. These can be organised on three levels of progressively higher order:A single sample: The most effective way to reveal the provenance information contained in a representative sample of detrital zircon U-Pb ages are probability density estimators such as histograms and kernel density estimates. The widely popular 'probability density plots' implemented in IsoPlot and AgeDisplay compound analytical uncertainty with geological scatter and are therefore invalid.Several samples: Multi-panel diagrams comprising many detrital age distributions or compositional pie charts quickly become unwieldy and uninterpretable. For example, if there are N samples in a study, then the number of pairwise comparisons between samples increases quadratically as N(N-1)/2. This is simply too much information for the human eye to process. To solve this problem, it is necessary to (a) express the 'distance' between two samples as a simple scalar and (b) combine all N(N-1)/2 such values in a single two-dimensional 'map', grouping similar and pulling apart dissimilar samples. This can be easily achieved using simple statistics-based dissimilarity measures and a standard statistical method called Multidimensional Scaling (MDS).Several methods: Suppose that we use four provenance proxies: bulk petrography, chemistry, heavy minerals and detrital geochronology. This will result in four MDS maps, each of which likely show slightly different trends and patterns. To deal with such cases, it may be useful to use a related technique called 'three way multidimensional scaling'. This results in two graphical outputs: an MDS map, and a map with 'weights' showing to what extent the different provenance proxies influence the horizontal and vertical axis of the MDS map. Thus, detrital data can not only inform the user about the provenance of sediments, but also about the causal relationships between the mineralogy, geochronology and chemistry.

High-speed GPU-based finite element simulations for NDT

NASA Astrophysics Data System (ADS)

Huthwaite, P.; Shi, F.; Van Pamel, A.; Lowe, M. J. S.

2015-03-01

The finite element method solved with explicit time increments is a general approach which can be applied to many ultrasound problems. It is widely used as a powerful tool within NDE for developing and testing inspection techniques, and can also be used in inversion processes. However, the solution technique is computationally intensive, requiring many calculations to be performed for each simulation, so traditionally speed has been an issue. For maximum speed, an implementation of the method, called Pogo [Huthwaite, J. Comp. Phys. 2014, doi: 10.1016/j.jcp.2013.10.017], has been developed to run on graphics cards, exploiting the highly parallelisable nature of the algorithm. Pogo typically demonstrates speed improvements of 60-90x over commercial CPU alternatives. Pogo is applied to three NDE examples, where the speed improvements are important: guided wave tomography, where a full 3D simulation must be run for each source transducer and every different defect size; scattering from rough cracks, where many simulations need to be run to build up a statistical model of the behaviour; and ultrasound propagation within coarse-grained materials where the mesh must be highly refined and many different cases run.

A comparison of four streamflow record extension techniques

USGS Publications Warehouse

Hirsch, Robert M.

1982-01-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., ‘line of organic correlation,’ ‘reduced major axis,’ ‘unique solution,’ and ‘equivalence line.’ The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

Speech enhancement using the modified phase-opponency model.

PubMed

Deshmukh, Om D; Espy-Wilson, Carol Y; Carney, Laurel H

2007-06-01

In this paper we present a model called the Modified Phase-Opponency (MPO) model for single-channel speech enhancement when the speech is corrupted by additive noise. The MPO model is based on the auditory PO model, proposed for detection of tones in noise. The PO model includes a physiologically realistic mechanism for processing the information in neural discharge times and exploits the frequency-dependent phase properties of the tuned filters in the auditory periphery by using a cross-auditory-nerve-fiber coincidence detection for extracting temporal cues. The MPO model alters the components of the PO model such that the basic functionality of the PO model is maintained but the properties of the model can be analyzed and modified independently. The MPO-based speech enhancement scheme does not need to estimate the noise characteristics nor does it assume that the noise satisfies any statistical model. The MPO technique leads to the lowest value of the LPC-based objective measures and the highest value of the perceptual evaluation of speech quality measure compared to other methods when the speech signals are corrupted by fluctuating noise. Combining the MPO speech enhancement technique with our aperiodicity, periodicity, and pitch detector further improves its performance.

Climatic Models Ensemble-based Mid-21st Century Runoff Projections: A Bayesian Framework

NASA Astrophysics Data System (ADS)

Achieng, K. O.; Zhu, J.

2017-12-01

There are a number of North American Regional Climate Change Assessment Program (NARCCAP) climatic models that have been used to project surface runoff in the mid-21st century. Statistical model selection techniques are often used to select the model that best fits data. However, model selection techniques often lead to different conclusions. In this study, ten models are averaged in Bayesian paradigm to project runoff. Bayesian Model Averaging (BMA) is used to project and identify effect of model uncertainty on future runoff projections. Baseflow separation - a two-digital filter which is also called Eckhardt filter - is used to separate USGS streamflow (total runoff) into two components: baseflow and surface runoff. We use this surface runoff as the a priori runoff when conducting BMA of runoff simulated from the ten RCM models. The primary objective of this study is to evaluate how well RCM multi-model ensembles simulate surface runoff, in a Bayesian framework. Specifically, we investigate and discuss the following questions: How well do ten RCM models ensemble jointly simulate surface runoff by averaging over all the models using BMA, given a priori surface runoff? What are the effects of model uncertainty on surface runoff simulation?

Dynamic connectivity regression: Determining state-related changes in brain connectivity

PubMed Central

Cribben, Ivor; Haraldsdottir, Ragnheidur; Atlas, Lauren Y.; Wager, Tor D.; Lindquist, Martin A.

2014-01-01

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method’s ability to observe how the networks between different brain regions changed with subjects’ emotional state. PMID:22484408

Optimal Background Estimators in Single-Molecule FRET Microscopy.

PubMed

Preus, Søren; Hildebrandt, Lasse L; Birkedal, Victoria

2016-09-20

Single-molecule total internal reflection fluorescence (TIRF) microscopy constitutes an umbrella of powerful tools that facilitate direct observation of the biophysical properties, population heterogeneities, and interactions of single biomolecules without the need for ensemble synchronization. Due to the low signal/noise ratio in single-molecule TIRF microscopy experiments, it is important to determine the local background intensity, especially when the fluorescence intensity of the molecule is used quantitatively. Here we compare and evaluate the performance of different aperture-based background estimators used particularly in single-molecule Förster resonance energy transfer. We introduce the general concept of multiaperture signatures and use this technique to demonstrate how the choice of background can affect the measured fluorescence signal considerably. A new, to our knowledge, and simple background estimator is proposed, called the local statistical percentile (LSP). We show that the LSP background estimator performs as well as current background estimators at low molecular densities and significantly better in regions of high molecular densities. The LSP background estimator is thus suited for single-particle TIRF microscopy of dense biological samples in which the intensity itself is an observable of the technique. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Estimating background-subtracted fluorescence transients in calcium imaging experiments: a quantitative approach.

PubMed

Joucla, Sébastien; Franconville, Romain; Pippow, Andreas; Kloppenburg, Peter; Pouzat, Christophe

2013-08-01

Calcium imaging has become a routine technique in neuroscience for subcellular to network level investigations. The fast progresses in the development of new indicators and imaging techniques call for dedicated reliable analysis methods. In particular, efficient and quantitative background fluorescence subtraction routines would be beneficial to most of the calcium imaging research field. A background-subtracted fluorescence transients estimation method that does not require any independent background measurement is therefore developed. This method is based on a fluorescence model fitted to single-trial data using a classical nonlinear regression approach. The model includes an appropriate probabilistic description of the acquisition system's noise leading to accurate confidence intervals on all quantities of interest (background fluorescence, normalized background-subtracted fluorescence time course) when background fluorescence is homogeneous. An automatic procedure detecting background inhomogeneities inside the region of interest is also developed and is shown to be efficient on simulated data. The implementation and performances of the proposed method on experimental recordings from the mouse hypothalamus are presented in details. This method, which applies to both single-cell and bulk-stained tissues recordings, should help improving the statistical comparison of fluorescence calcium signals between experiments and studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Data re-arranging techniques leading to proper variable selections in high energy physics

NASA Astrophysics Data System (ADS)

Kůs, Václav; Bouř, Petr

2017-12-01

We introduce a new data based approach to homogeneity testing and variable selection carried out in high energy physics experiments, where one of the basic tasks is to test the homogeneity of weighted samples, mainly the Monte Carlo simulations (weighted) and real data measurements (unweighted). This technique is called ’data re-arranging’ and it enables variable selection performed by means of the classical statistical homogeneity tests such as Kolmogorov-Smirnov, Anderson-Darling, or Pearson’s chi-square divergence test. P-values of our variants of homogeneity tests are investigated and the empirical verification through 46 dimensional high energy particle physics data sets is accomplished under newly proposed (equiprobable) quantile binning. Particularly, the procedure of homogeneity testing is applied to re-arranged Monte Carlo samples and real DATA sets measured at the particle accelerator Tevatron in Fermilab at DØ experiment originating from top-antitop quark pair production in two decay channels (electron, muon) with 2, 3, or 4+ jets detected. Finally, the variable selections in the electron and muon channels induced by the re-arranging procedure for homogeneity testing are provided for Tevatron top-antitop quark data sets.

A Comparison of Four Streamflow Record Extension Techniques

NASA Astrophysics Data System (ADS)

Hirsch, Robert M.

1982-08-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., `line of organic correlation,' `reduced major axis,' `unique solution,' and `equivalence line.' The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

Queries over Unstructured Data: Probabilistic Methods to the Rescue

NASA Astrophysics Data System (ADS)

Sarawagi, Sunita

Unstructured data like emails, addresses, invoices, call transcripts, reviews, and press releases are now an integral part of any large enterprise. A challenge of modern business intelligence applications is analyzing and querying data seamlessly across structured and unstructured sources. This requires the development of automated techniques for extracting structured records from text sources and resolving entity mentions in data from various sources. The success of any automated method for extraction and integration depends on how effectively it unifies diverse clues in the unstructured source and in existing structured databases. We argue that statistical learning techniques like Conditional Random Fields (CRFs) provide a accurate, elegant and principled framework for tackling these tasks. Given the inherent noise in real-world sources, it is important to capture the uncertainty of the above operations via imprecise data models. CRFs provide a sound probability distribution over extractions but are not easy to represent and query in a relational framework. We present methods of approximating this distribution to query-friendly row and column uncertainty models. Finally, we present models for representing the uncertainty of de-duplication and algorithms for various Top-K count queries on imprecise duplicates.

Calling behavior of blue and fin whales off California

NASA Astrophysics Data System (ADS)

Oleson, Erin Marie

Passive acoustic monitoring is an effective means for evaluating cetacean presence in remote regions and over long time periods, and may become an important component of cetacean abundance surveys. To use passive acoustic recordings for abundance estimation, an understanding of the behavioral ecology of cetacean calling is crucial. In this dissertation, I develop a better understanding of how blue (Balaenoptera musculus) and fin (B. physalus ) whales use sound with the goal of evaluating passive acoustic techniques for studying their populations. Both blue and fin whales produce several different call types, though the behavioral and environmental context of these calls have not been widely investigated. To better understand how calling is used by these whales off California I have employed both new technologies and traditional techniques, including acoustic recording tags, continuous long-term autonomous acoustic recordings, and simultaneous shipboard acoustic and visual surveys. The outcome of these investigations has led to several conclusions. The production of blue whale calls varies with sex, behavior, season, location, and time of day. Each blue whale call type has a distinct behavioral context, including a male-only bias in the production of song, a call type thought to function in reproduction, and the production of some calls by both sexes. Long-term acoustic records, when interpreted using all call types, provide a more accurate measure of the local seasonal presence of whales, and how they use the region annually, seasonally and daily. The relative occurrence of different call types may indicate prime foraging habitat and the presence of different segments of the population. The proportion of animals heard calling changes seasonally and geographically relative to the number seen, indicating the calibration of acoustic and visual surveys is complex and requires further study on the motivations behind call production and the behavior of calling whales. These findings will play a role in the future development of acoustic census methods and habitat studies for these species, and will provide baseline information for the determination of anthropogenic impacts on these populations.

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

PubMed

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to combine the advantages brought forward by the proposed EWMA-GLRT fault detection chart with the KPCA model. Thus, it is used to enhance fault detection of the Cad System in E. coli model through monitoring some of the key variables involved in this model such as enzymes, transport proteins, regulatory proteins, lysine, and cadaverine. The results demonstrate the effectiveness of the proposed KPCA-based EWMA-GLRT method over Q , GLRT, EWMA, Shewhart, and moving window-GLRT methods. The detection performance is assessed and evaluated in terms of FAR, missed detection rates, and average run length (ARL 1 ) values.

Statistical approaches for studying the wave climate of crossing-sea states

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Portilla, Jesus; Benetazzo, Alvise; Cavaleri, Luigi; Sclavo, Mauro; Carniel, Sandro

2017-04-01

Surface waves are an important feature of the world's oceans and seas. Their role in the air-sea exchanges is well recognized, together with their effects on the upper ocean and lower atmosphere dynamics. Physical processes involving surface waves contribute in driving the Earth's climate that, while experiencing changes at global and regional scales, in turn affects the surface waves climate over the oceans. The assessment of the wave climate at specific locations of the ocean is fruitful for many research fields in marine and atmospheric sciences and also for the human activities in the marine environment. Very often, wind generated waves (wind-sea) and one or more swell systems occur simultaneously, depending on the complexity of the atmospheric conditions that force the waves. Therefore, a wave climate assessed from the statistical analysis of long time series of integral wave parameters, can hardly say something about the frequency of occurrence of the so-called crossing-seas, as well as of their features. Directional wave spectra carry such information but proper statistical methods to analyze them are needed. In this respect, in order to identify the crossing sea states within the spectral time series and to assess their frequency of occurrence we exploit two advanced statistical techniques. First, we apply the Spectral Partitioning, a well-established method based on a two-step partitioning of the spectrum that allows to identify the individual wave systems and to compute their probability of occurrence in the frequency/direction space. Then, we use the Self-Organizing Maps, an unsupervised neural network algorithm that quantize the time series by autonomously identifying an arbitrary (small) number of wave spectra representing the whole wave climate, each with its frequency of occurrence. This method has been previously applied to time series of wave parameters and for the first time is applied to directional wave spectra. We analyze the wave climate of one of the most severe regions of the Mediterranean Sea, between north-west Sardinia and the Gulf of Lion, where quite often wave systems coming from different directions superpose. Time series for the analysis is taken from the ERA-Interim Reanalysis dataset, which provides global directional wave spectra at 1° resolution, starting from 1979 up to the present. Results from the two techniques are shown to be consistent, and their comparison points out the contribution that each technique can provide for a more detailed interpretation of the wave climate.

Technical Note: The Initial Stages of Statistical Data Analysis

PubMed Central

Tandy, Richard D.

1998-01-01

Objective: To provide an overview of several important data-related considerations in the design stage of a research project and to review the levels of measurement and their relationship to the statistical technique chosen for the data analysis. Background: When planning a study, the researcher must clearly define the research problem and narrow it down to specific, testable questions. The next steps are to identify the variables in the study, decide how to group and treat subjects, and determine how to measure, and the underlying level of measurement of, the dependent variables. Then the appropriate statistical technique can be selected for data analysis. Description: The four levels of measurement in increasing complexity are nominal, ordinal, interval, and ratio. Nominal data are categorical or “count” data, and the numbers are treated as labels. Ordinal data can be ranked in a meaningful order by magnitude. Interval data possess the characteristics of ordinal data and also have equal distances between levels. Ratio data have a natural zero point. Nominal and ordinal data are analyzed with nonparametric statistical techniques and interval and ratio data with parametric statistical techniques. Advantages: Understanding the four levels of measurement and when it is appropriate to use each is important in determining which statistical technique to use when analyzing data. PMID:16558489

Design of a 3D Navigation Technique Supporting VR Interaction

NASA Astrophysics Data System (ADS)

Boudoin, Pierre; Otmane, Samir; Mallem, Malik

2008-06-01

Multimodality is a powerful paradigm to increase the realness and the easiness of the interaction in Virtual Environments (VEs). In particular, the search for new metaphors and techniques for 3D interaction adapted to the navigation task is an important stage for the realization of future 3D interaction systems that support multimodality, in order to increase efficiency and usability. In this paper we propose a new multimodal 3D interaction model called Fly Over. This model is especially devoted to the navigation task. We present a qualitative comparison between Fly Over and a classical navigation technique called gaze-directed steering. The results from preliminary evaluation on the IBISC semi-immersive Virtual Reality/Augmented Realty EVR@ platform show that Fly Over is a user friendly and efficient navigation technique.

Perspectives on statistics education: observations from statistical consulting in an academic nursing environment.

PubMed

Hayat, Matthew J; Schmiege, Sarah J; Cook, Paul F

2014-04-01

Statistics knowledge is essential for understanding the nursing and health care literature, as well as for applying rigorous science in nursing research. Statistical consultants providing services to faculty and students in an academic nursing program have the opportunity to identify gaps and challenges in statistics education for nursing students. This information may be useful to curriculum committees and statistics educators. This article aims to provide perspective on statistics education stemming from the experiences of three experienced statistics educators who regularly collaborate and consult with nurse investigators. The authors share their knowledge and express their views about data management, data screening and manipulation, statistical software, types of scientific investigation, and advanced statistical topics not covered in the usual coursework. The suggestions provided promote a call for data to study these topics. Relevant data about statistics education can assist educators in developing comprehensive statistics coursework for nursing students. Copyright 2014, SLACK Incorporated.

Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique

PubMed Central

Nasirudin, Radin A.; Mei, Kai; Panchev, Petar; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Fiebich, Martin; Noël, Peter B.

2015-01-01

Purpose The exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR). Method The proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods. Results Decomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms. Conclusion It is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers. PMID:25955019

Promoting Active Learning When Teaching Introductory Statistics and Probability Using a Portfolio Curriculum Approach

ERIC Educational Resources Information Center

Adair, Desmond; Jaeger, Martin; Price, Owen M.

2018-01-01

The use of a portfolio curriculum approach, when teaching a university introductory statistics and probability course to engineering students, is developed and evaluated. The portfolio curriculum approach, so called, as the students need to keep extensive records both as hard copies and digitally of reading materials, interactions with faculty,…

Doing Research That Matters: A Success Story from Statistics Education

ERIC Educational Resources Information Center

Hipkins, Rosemary

2014-01-01

This is the first report from a new initiative called TLRI Project Plus. It aims to add value to the Teaching and Learning Research Initiative (TLRI), which NZCER manages on behalf of the government, by synthesising findings across multiple projects. This report focuses on two projects in statistics education and explores the factors that…

Parameterizing Phrase Based Statistical Machine Translation Models: An Analytic Study

ERIC Educational Resources Information Center

Cer, Daniel

2011-01-01

The goal of this dissertation is to determine the best way to train a statistical machine translation system. I first develop a state-of-the-art machine translation system called Phrasal and then use it to examine a wide variety of potential learning algorithms and optimization criteria and arrive at two very surprising results. First, despite the…

Ten Ways to Improve the Use of Statistical Mediation Analysis in the Practice of Child and Adolescent Treatment Research

ERIC Educational Resources Information Center

Maric, Marija; Wiers, Reinout W.; Prins, Pier J. M.

2012-01-01

Despite guidelines and repeated calls from the literature, statistical mediation analysis in youth treatment outcome research is rare. Even more concerning is that many studies that "have" reported mediation analyses do not fulfill basic requirements for mediation analysis, providing inconclusive data and clinical implications. As a result, after…

78 FR 63966 - Gulf of Mexico Fishery Management Council; Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-25

... Scientific and Statistical Committee (SSC). DATES: The meeting will be held from 9 a.m. Until 5 p.m. on.... Recommendations to the Council 4. Other Business For meeting materials, call (813) 348-1630. Although other non-emergency issues not on the agenda may come before the Scientific and Statistical Committees for discussion...

Are Assumptions of Well-Known Statistical Techniques Checked, and Why (Not)?

PubMed Central

Hoekstra, Rink; Kiers, Henk A. L.; Johnson, Addie

2012-01-01

A valid interpretation of most statistical techniques requires that one or more assumptions be met. In published articles, however, little information tends to be reported on whether the data satisfy the assumptions underlying the statistical techniques used. This could be due to self-selection: Only manuscripts with data fulfilling the assumptions are submitted. Another explanation could be that violations of assumptions are rarely checked for in the first place. We studied whether and how 30 researchers checked fictitious data for violations of assumptions in their own working environment. Participants were asked to analyze the data as they would their own data, for which often used and well-known techniques such as the t-procedure, ANOVA and regression (or non-parametric alternatives) were required. It was found that the assumptions of the techniques were rarely checked, and that if they were, it was regularly by means of a statistical test. Interviews afterward revealed a general lack of knowledge about assumptions, the robustness of the techniques with regards to the assumptions, and how (or whether) assumptions should be checked. These data suggest that checking for violations of assumptions is not a well-considered choice, and that the use of statistics can be described as opportunistic. PMID:22593746

Evaluation of Three Different Processing Techniques in the Fabrication of Complete Dentures

PubMed Central

Chintalacheruvu, Vamsi Krishna; Balraj, Rajasekaran Uttukuli; Putchala, Lavanya Sireesha; Pachalla, Sreelekha

2017-01-01

Aims and Objectives: The objective of the present study is to compare the effectiveness of three different processing techniques and to find out the accuracy of processing techniques through number of occlusal interferences and increase in vertical dimension after denture processing. Materials and Methods: A cross-sectional study was conducted on a sample of 18 patients indicated for complete denture fabrication was selected for the study and they were divided into three subgroups. Three processing techniques, compression molding and injection molding using prepolymerized resin and unpolymerized resin, were used to fabricate dentures for each of the groups. After processing, laboratory-remounted dentures were evaluated for number of occlusal interferences in centric and eccentric relations and change in vertical dimension through vertical pin rise in articulator. Data were analyzed using statistical test ANOVA and SPSS software version 19.0 by IBM was used. Results: Data obtained from three groups were subjected to one-way ANOVA test. After ANOVA test, results with significant variations were subjected to post hoc test. Number of occlusal interferences with compression molding technique was reported to be more in both centric and eccentric positions as compared to the two injection molding techniques with statistical significance in centric, protrusive, right lateral nonworking, and left lateral working positions (P < 0.05). Mean vertical pin rise (0.52 mm) was reported to more in compression molding technique as compared to injection molding techniques, which is statistically significant (P < 0.001). Conclusions: Within the limitations of this study, injection molding techniques exhibited less processing errors as compared to compression molding technique with statistical significance. There was no statistically significant difference in processing errors reported within two injection molding systems. PMID:28713763

Evaluation of Three Different Processing Techniques in the Fabrication of Complete Dentures.

PubMed

Chintalacheruvu, Vamsi Krishna; Balraj, Rajasekaran Uttukuli; Putchala, Lavanya Sireesha; Pachalla, Sreelekha

2017-06-01

The objective of the present study is to compare the effectiveness of three different processing techniques and to find out the accuracy of processing techniques through number of occlusal interferences and increase in vertical dimension after denture processing. A cross-sectional study was conducted on a sample of 18 patients indicated for complete denture fabrication was selected for the study and they were divided into three subgroups. Three processing techniques, compression molding and injection molding using prepolymerized resin and unpolymerized resin, were used to fabricate dentures for each of the groups. After processing, laboratory-remounted dentures were evaluated for number of occlusal interferences in centric and eccentric relations and change in vertical dimension through vertical pin rise in articulator. Data were analyzed using statistical test ANOVA and SPSS software version 19.0 by IBM was used. Data obtained from three groups were subjected to one-way ANOVA test. After ANOVA test, results with significant variations were subjected to post hoc test. Number of occlusal interferences with compression molding technique was reported to be more in both centric and eccentric positions as compared to the two injection molding techniques with statistical significance in centric, protrusive, right lateral nonworking, and left lateral working positions ( P < 0.05). Mean vertical pin rise (0.52 mm) was reported to more in compression molding technique as compared to injection molding techniques, which is statistically significant ( P < 0.001). Within the limitations of this study, injection molding techniques exhibited less processing errors as compared to compression molding technique with statistical significance. There was no statistically significant difference in processing errors reported within two injection molding systems.

Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data.

PubMed

Janik, M; Bossew, P; Kurihara, O

2018-07-15

Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon ( 222 Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical predictors, while "day of the year" is a statistical proxy or surrogate for missing or unknown predictors. Copyright © 2018 Elsevier B.V. All rights reserved.

Pesticide poisoning in Palestine: a retrospective analysis of calls received by Poison Control and Drug Information Center from 2006-2010.

PubMed

Sawalha, Ansam F; O'Malley, Gerald F; Sweileh, Waleed M

2012-01-01

The agricultural industry is the largest economic sector in Palestine and is characterized by extensive and unregulated use of pesticides. The objective of this study was to analyze phone calls received by the Poison Control and Drug Information Center (PCDIC) in Palestine regarding pesticide poisoning. All phone calls regarding pesticide poisoning received by the PCDIC from 2006 to 2010 were descriptively analyzed. Statistical Package for Social Sciences (SPSS version 16) was used in statistical analysis and to create figures. A total of 290 calls regarding pesticide poisoning were received during the study period. Most calls (83.8%) were made by physicians. The average age of reported cases was 19.6 ± 15 years. Pesticide poisoning occurred mostly in males (56.9%). Pesticide poisoning was most common (75, 25.9%) in the age category of 20-29.9 years. The majority (51.7%) of the cases were deliberate self-harm while the remaining was accidental exposure. The majority of phone calls (250, 86.2%) described oral exposure to pesticides. Approximately one third (32.9%) of the cases had symptoms consistent with organophosphate poisoning. Gastric lavage (31.7%) was the major decontamination method used, while charcoal was only utilized in 1.4% of the cases. Follow up was performed in 45.5% of the cases, two patients died after hospital admission while the remaining had positive outcome. Pesticide poisoning is a major health problem in Palestine, and the PCDIC has a clear mission to help in recommending therapy and gathering information.

A methodology for the design of experiments in computational intelligence with multiple regression models.

PubMed

Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

A New Statistical Model of Electroencephalogram Noise Spectra for Real-Time Brain-Computer Interfaces.

PubMed

Paris, Alan; Atia, George K; Vosoughi, Azadeh; Berman, Stephen A

2017-08-01

A characteristic of neurological signal processing is high levels of noise from subcellular ion channels up to whole-brain processes. In this paper, we propose a new model of electroencephalogram (EEG) background periodograms, based on a family of functions which we call generalized van der Ziel-McWhorter (GVZM) power spectral densities (PSDs). To the best of our knowledge, the GVZM PSD function is the only EEG noise model that has relatively few parameters, matches recorded EEG PSD's with high accuracy from 0 to over 30 Hz, and has approximately 1/f θ behavior in the midfrequencies without infinities. We validate this model using three approaches. First, we show how GVZM PSDs can arise in a population of ion channels at maximum entropy equilibrium. Second, we present a class of mixed autoregressive models, which simulate brain background noise and whose periodograms are asymptotic to the GVZM PSD. Third, we present two real-time estimation algorithms for steady-state visual evoked potential (SSVEP) frequencies, and analyze their performance statistically. In pairwise comparisons, the GVZM-based algorithms showed statistically significant accuracy improvement over two well-known and widely used SSVEP estimators. The GVZM noise model can be a useful and reliable technique for EEG signal processing. Understanding EEG noise is essential for EEG-based neurology and applications such as real-time brain-computer interfaces, which must make accurate control decisions from very short data epochs. The GVZM approach represents a successful new paradigm for understanding and managing this neurological noise.

A methodology for the design of experiments in computational intelligence with multiple regression models

PubMed Central

Gestal, Marcos; Munteanu, Cristian R.; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable. PMID:27920952

Deriving Criteria-supporting Benchmark Values from Empirical Response Relationships: Comparison of Statistical Techniques and Effect of Log-transforming the Nutrient Variable

EPA Science Inventory

In analyses supporting the development of numeric nutrient criteria, multiple statistical techniques can be used to extract critical values from stressor response relationships. However there is little guidance for choosing among techniques, and the extent to which log-transfor...

Incorporating Nonparametric Statistics into Delphi Studies in Library and Information Science

ERIC Educational Resources Information Center

Ju, Boryung; Jin, Tao

2013-01-01

Introduction: The Delphi technique is widely used in library and information science research. However, many researchers in the field fail to employ standard statistical tests when using this technique. This makes the technique vulnerable to criticisms of its reliability and validity. The general goal of this article is to explore how…

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis

NASA Astrophysics Data System (ADS)

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

PubMed

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

ERIC Educational Resources Information Center

Karadag, Engin

2010-01-01

To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

Statistics in the Workplace: A Survey of Use by Recent Graduates with Higher Degrees

ERIC Educational Resources Information Center

Harraway, John A.; Barker, Richard J.

2005-01-01

A postal survey was conducted regarding statistical techniques, research methods and software used in the workplace by 913 graduates with PhD and Masters degrees in the biological sciences, psychology, business, economics, and statistics. The study identified gaps between topics and techniques learned at university and those used in the workplace,…

Terrestrial Radiodetermination Performance and Cost

DOT National Transportation Integrated Search

1977-09-01

The report summarizes information gathered during a study of the application of electronic techniques to geographical position determination on land and on inland waterways. Systems incorporating such techniques have been called terrestrial radiodete...

Statistical approach for selection of biologically informative genes.

PubMed

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes from high dimensional expression data for breeding and system biology studies. Published by Elsevier B.V.

Techniques in teaching statistics : linking research production and research use.

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

Martinez-Moyano, I .; Smith, A.; Univ. of Massachusetts at Boston)

In the spirit of closing the 'research-practice gap,' the authors extend evidence-based principles to statistics instruction in social science graduate education. The authors employ a Delphi method to survey experienced statistics instructors to identify teaching techniques to overcome the challenges inherent in teaching statistics to students enrolled in practitioner-oriented master's degree programs. Among the teaching techniques identi?ed as essential are using real-life examples, requiring data collection exercises, and emphasizing interpretation rather than results. Building on existing research, preliminary interviews, and the ?ndings from the study, the authors develop a model describing antecedents to the strength of the link between researchmore » and practice.« less

Statistical Symbolic Execution with Informed Sampling

NASA Technical Reports Server (NTRS)

Filieri, Antonio; Pasareanu, Corina S.; Visser, Willem; Geldenhuys, Jaco

2014-01-01

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Practical interpretation of CYP2D6 haplotypes: Comparison and integration of automated and expert calling.

PubMed

Ruaño, Gualberto; Kocherla, Mohan; Graydon, James S; Holford, Theodore R; Makowski, Gregory S; Goethe, John W

2016-05-01

We describe a population genetic approach to compare samples interpreted with expert calling (EC) versus automated calling (AC) for CYP2D6 haplotyping. The analysis represents 4812 haplotype calls based on signal data generated by the Luminex xMap analyzers from 2406 patients referred to a high-complexity molecular diagnostics laboratory for CYP450 testing. DNA was extracted from buccal swabs. We compared the results of expert calls (EC) and automated calls (AC) with regard to haplotype number and frequency. The ratio of EC to AC was 1:3. Haplotype frequencies from EC and AC samples were convergent across haplotypes, and their distribution was not statistically different between the groups. Most duplications required EC, as only expansions with homozygous or hemizygous haplotypes could be automatedly called. High-complexity laboratories can offer equivalent interpretation to automated calling for non-expanded CYP2D6 loci, and superior interpretation for duplications. We have validated scientific expert calling specified by scoring rules as standard operating procedure integrated with an automated calling algorithm. The integration of EC with AC is a practical strategy for CYP2D6 clinical haplotyping. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

PubMed

Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

2015-01-01

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001). Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

Control algorithms for aerobraking in the Martian atmosphere

NASA Technical Reports Server (NTRS)

Ward, Donald T.; Shipley, Buford W., Jr.

1991-01-01

The Analytic Predictor Corrector (APC) and Energy Controller (EC) atmospheric guidance concepts were adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. Changes are made to the APC to improve its robustness to density variations. These changes include adaptation of a new exit phase algorithm, an adaptive transition velocity to initiate the exit phase, refinement of the reference dynamic pressure calculation and two improved density estimation techniques. The modified controller with the hybrid density estimation technique is called the Mars Hybrid Predictor Corrector (MHPC), while the modified controller with a polynomial density estimator is called the Mars Predictor Corrector (MPC). A Lyapunov Steepest Descent Controller (LSDC) is adapted to control the vehicle. The LSDC lacked robustness, so a Lyapunov tracking exit phase algorithm is developed to guide the vehicle along a reference trajectory. This algorithm, when using the hybrid density estimation technique to define the reference path, is called the Lyapunov Hybrid Tracking Controller (LHTC). With the polynomial density estimator used to define the reference trajectory, the algorithm is called the Lyapunov Tracking Controller (LTC). These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. The MHPC, MPC, LHTC, and LTC show dramatic improvements in robustness over the APC and EC.

Blind source computer device identification from recorded VoIP calls for forensic investigation.

PubMed

Jahanirad, Mehdi; Anuar, Nor Badrul; Wahab, Ainuddin Wahid Abdul

2017-03-01

The VoIP services provide fertile ground for criminal activity, thus identifying the transmitting computer devices from recorded VoIP call may help the forensic investigator to reveal useful information. It also proves the authenticity of the call recording submitted to the court as evidence. This paper extended the previous study on the use of recorded VoIP call for blind source computer device identification. Although initial results were promising but theoretical reasoning for this is yet to be found. The study suggested computing entropy of mel-frequency cepstrum coefficients (entropy-MFCC) from near-silent segments as an intrinsic feature set that captures the device response function due to the tolerances in the electronic components of individual computer devices. By applying the supervised learning techniques of naïve Bayesian, linear logistic regression, neural networks and support vector machines to the entropy-MFCC features, state-of-the-art identification accuracy of near 99.9% has been achieved on different sets of computer devices for both call recording and microphone recording scenarios. Furthermore, unsupervised learning techniques, including simple k-means, expectation-maximization and density-based spatial clustering of applications with noise (DBSCAN) provided promising results for call recording dataset by assigning the majority of instances to their correct clusters. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Terrestrial Radiodetermination Potential Users and Their Requirements

DOT National Transportation Integrated Search

1976-07-01

The report summarizes information gathered during a preliminary study of the application of electronic techniques to geographical position determination on land and on inland waterways. Systems incorporating such techniques have been called terrestri...

Earth Observation System Flight Dynamics System Covariance Realism

NASA Technical Reports Server (NTRS)

Zaidi, Waqar H.; Tracewell, David

2016-01-01

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.

The Shock and Vibration Digest. Volume 16, Number 1

DTIC Science & Technology

1984-01-01

investigation of the measure- ment of frequency band average loss factors of structural components for use in the statistical energy analysis method of...stiffness. Matrix methods Key Words: Finite element technique. Statistical energy analysis . Experimental techniques. Framed structures, Com- puter...programs In order to further understand the practical application of the statistical energy analysis , a two section plate-like frame structure is

Interactive algebraic grid-generation technique

NASA Technical Reports Server (NTRS)

Smith, R. E.; Wiese, M. R.

1986-01-01

An algebraic grid generation technique and use of an associated interactive computer program are described. The technique, called the two boundary technique, is based on Hermite cubic interpolation between two fixed, nonintersecting boundaries. The boundaries are referred to as the bottom and top, and they are defined by two ordered sets of points. Left and right side boundaries which intersect the bottom and top boundaries may also be specified by two ordered sets of points. when side boundaries are specified, linear blending functions are used to conform interior interpolation to the side boundaries. Spacing between physical grid coordinates is determined as a function of boundary data and uniformly space computational coordinates. Control functions relating computational coordinates to parametric intermediate variables that affect the distance between grid points are embedded in the interpolation formulas. A versatile control function technique with smooth-cubic-spline functions is presented. The technique works best in an interactive graphics environment where computational displays and user responses are quickly exchanged. An interactive computer program based on the technique and called TBGG (two boundary grid generation) is also described.

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

Towards Solving the Mixing Problem in the Decomposition of Geophysical Time Series by Independent Component Analysis

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2000-01-01

The use of the Principal Component Analysis technique for the analysis of geophysical time series has been questioned in particular for its tendency to extract components that mix several physical phenomena even when the signal is just their linear sum. We demonstrate with a data simulation experiment that the Independent Component Analysis, a recently developed technique, is able to solve this problem. This new technique requires the statistical independence of components, a stronger constraint, that uses higher-order statistics, instead of the classical decorrelation a weaker constraint, that uses only second-order statistics. Furthermore, ICA does not require additional a priori information such as the localization constraint used in Rotational Techniques.

GyneScan

PubMed Central

Acharya, U. Rajendra; Sree, S. Vinitha; Kulshreshtha, Sanjeev; Molinari, Filippo; Koh, Joel En Wei; Saba, Luca; Suri, Jasjit S.

2014-01-01

Ovarian cancer is the fifth highest cause of cancer in women and the leading cause of death from gynecological cancers. Accurate diagnosis of ovarian cancer from acquired images is dependent on the expertise and experience of ultrasonographers or physicians, and is therefore, associated with inter observer variabilities. Computer Aided Diagnostic (CAD) techniques use a number of different data mining techniques to automatically predict the presence or absence of cancer, and therefore, are more reliable and accurate. A review of published literature in the field of CAD based ovarian cancer detection indicates that many studies use ultrasound images as the base for analysis. The key objective of this work is to propose an effective adjunct CAD technique called GyneScan for ovarian tumor detection in ultrasound images. In our proposed data mining framework, we extract several texture features based on first order statistics, Gray Level Co-occurrence Matrix and run length matrix. The significant features selected using t-test are then used to train and test several supervised learning based classifiers such as Probabilistic Neural Networks (PNN), Support Vector Machine (SVM), Decision Tree (DT), k-Nearest Neighbor (KNN), and Naïve Bayes (NB). We evaluated the developed framework using 1300 benign and 1300 malignant images. Using 11 significant features in KNN/PNN classifiers, we were able to achieve 100% classification accuracy, sensitivity, specificity, and positive predictive value in detecting ovarian tumor. Even though more validation using larger databases would better establish the robustness of our technique, the preliminary results are promising. This technique could be used as a reliable adjunct method to existing imaging modalities to provide a more confident second opinion on the presence/absence of ovarian tumor. PMID:24325128

Probabilistic topic modeling for the analysis and classification of genomic sequences

PubMed Central

2015-01-01

Background Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques. Methods The presented method is based on Probabilistic Topic Modeling, a statistical technique originally proposed for text documents. Probabilistic topic models are able to find in a document corpus the topics (recurrent themes) characterizing classes of documents. This technique, applied on DNA sequences representing the documents, exploits the frequency of fixed-length k-mers and builds a generative model for a training group of sequences. This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. Results and conclusions We performed classification of over 7000 16S DNA barcode sequences taken from Ribosomal Database Project (RDP) repository, training probabilistic topic models. The proposed method is compared to the RDP tool and Support Vector Machine (SVM) classification algorithm in a extensive set of trials using both complete sequences and short sequence snippets (from 400 bp to 25 bp). Our method reaches very similar results to RDP classifier and SVM for complete sequences. The most interesting results are obtained when short sequence snippets are considered. In these conditions the proposed method outperforms RDP and SVM with ultra short sequences and it exhibits a smooth decrease of performance, at every taxonomic level, when the sequence length is decreased. PMID:25916734

Calling depths of baleen whales from single sensor data: development of an autocorrelation method using multipath localization.

PubMed

Valtierra, Robert D; Glynn Holt, R; Cholewiak, Danielle; Van Parijs, Sofie M

2013-09-01

Multipath localization techniques have not previously been applied to baleen whale vocalizations due to difficulties in application to tonal vocalizations. Here it is shown that an autocorrelation method coupled with the direct reflected time difference of arrival localization technique can successfully resolve location information. A derivation was made to model the autocorrelation of a direct signal and its overlapping reflections to illustrate that an autocorrelation may be used to extract reflection information from longer duration signals containing a frequency sweep, such as some calls produced by baleen whales. An analysis was performed to characterize the difference in behavior of the autocorrelation when applied to call types with varying parameters (sweep rate, call duration). The method's feasibility was tested using data from playback transmissions to localize an acoustic transducer at a known depth and location. The method was then used to estimate the depth and range of a single North Atlantic right whale (Eubalaena glacialis) and humpback whale (Megaptera novaeangliae) from two separate experiments.

An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-Tracking Data

ERIC Educational Resources Information Center

Sharma, Kshitij; Chavez-Demoulin, Valérie; Dillenbourg, Pierre

2017-01-01

The statistics used in education research are based on central trends such as the mean or standard deviation, discarding outliers. This paper adopts another viewpoint that has emerged in statistics, called extreme value theory (EVT). EVT claims that the bulk of normal distribution is comprised mainly of uninteresting variations while the most…

Monetary policy and the effects of oil price shocks on the Japanese economy

NASA Astrophysics Data System (ADS)

Lee, Byung Rhae

1998-12-01

The evidence of output decreases and price level increases following oil price shocks in the Japanese economy is presented in this paper. These negative effects of oil shocks are better explained by Hamilton's (1996) net oil price increase measure (NOPI) than by other oil measures. The fact that an oil shock has a statistically significant effect on the call money rate and real output and that the call money rate also has a statistically significant effect on real output appears to explain that the effects of oil price shocks on economic activity are partially attributed to contractionary monetary policy responses. The asymmetric effects of positive and negative oil shocks are also found in the Japanese economy and this asymmetry can also be partially explained by monetary policy responses. To assess the relative contribution of oil shocks and endogenous monetary policy responses to the economic downturns, I shut off the responses of the call money rate to oil shocks utilizing the impulse response results from the VAR model. Then, I re-run the VAR with the adjusted call money rate series. The empirical results show that around 30--40% of the negative effects of oil price shocks on the Japanese economy can be accounted for by oil shock induced monetary tightening.

w4CSeq: software and web application to analyze 4C-seq data.

PubMed

Cai, Mingyang; Gao, Fan; Lu, Wange; Wang, Kai

2016-11-01

Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a powerful technique to identify genome-wide partners interacting with a pre-specified genomic locus. Here, we present a computational and statistical approach to analyze 4C-Seq data generated from both enzyme digestion and sonication fragmentation-based methods. We implemented a command line software tool and a web interface called w4CSeq, which takes in the raw 4C sequencing data (FASTQ files) as input, performs automated statistical analysis and presents results in a user-friendly manner. Besides providing users with the list of candidate interacting sites/regions, w4CSeq generates figures showing genome-wide distribution of interacting regions, and sketches the enrichment of key features such as TSSs, TTSs, CpG sites and DNA replication timing around 4C sites. Users can establish their own web server by downloading source codes at https://github.com/WGLab/w4CSeq Additionally, a demo web server is available at http://w4cseq.wglab.org CONTACT: kaiwang@usc.edu or wangelu@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Characterization of time series via Rényi complexity-entropy curves

NASA Astrophysics Data System (ADS)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

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

Hou Fengji; Hogg, David W.; Goodman, Jonathan

Markov chain Monte Carlo (MCMC) proves to be powerful for Bayesian inference and in particular for exoplanet radial velocity fitting because MCMC provides more statistical information and makes better use of data than common approaches like chi-square fitting. However, the nonlinear density functions encountered in these problems can make MCMC time-consuming. In this paper, we apply an ensemble sampler respecting affine invariance to orbital parameter extraction from radial velocity data. This new sampler has only one free parameter, and does not require much tuning for good performance, which is important for automatization. The autocorrelation time of this sampler is approximatelymore » the same for all parameters and far smaller than Metropolis-Hastings, which means it requires many fewer function calls to produce the same number of independent samples. The affine-invariant sampler speeds up MCMC by hundreds of times compared with Metropolis-Hastings in the same computing situation. This novel sampler would be ideal for projects involving large data sets such as statistical investigations of planet distribution. The biggest obstacle to ensemble samplers is the existence of multiple local optima; we present a clustering technique to deal with local optima by clustering based on the likelihood of the walkers in the ensemble. We demonstrate the effectiveness of the sampler on real radial velocity data.« less

Characterization of interfade duration for satellite communication systems design and optimization in a temperate climate

NASA Astrophysics Data System (ADS)

Jorge, Flávio; Riva, Carlo; Rocha, Armando

2016-03-01

The characterization of the fade dynamics on Earth-satellite links is an important subject when designing the so called fade mitigation techniques that contribute to the proper reliability of the satellite communication systems and the customers' quality of service (QoS). The interfade duration, defined as the period between two consecutive fade events, has been only poorly analyzed using limited data sets, but its complete characterization would enable the design and optimization of the satellite communication systems by estimating the system requirements to recover in time before the next propagation impairment. Depending on this analysis, several actions can be taken ensuring the service maintenance. In this paper we present for the first time a detailed and comprehensive analysis of the interfade events statistical properties based on 9 years of in-excess attenuation measurements at Ka band (19.7 GHz) with very high availability that is required to build a reliable data set mainly for the longer interfade duration events. The number of years necessary to reach the statistical stability of interfade duration is also evaluated for the first time, providing a reference when accessing the relevance of the results published in the past. The study is carried out in Aveiro, Portugal, which is conditioned by temperate Mediterranean climate with Oceanic influences.

An image adaptive, wavelet-based watermarking of digital images

NASA Astrophysics Data System (ADS)

Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia

2007-12-01

In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

Intimate Debate Technique: Medicinal Use of Marijuana

ERIC Educational Resources Information Center

Herreid, Clyde Freeman; DeRei, Kristie

2007-01-01

Classroom debates used to be familiar exercises to students schooled in past generations. In this article, the authors describe the technique called "intimate debate". To cooperative learning specialists, the technique is known as "structured debate" or "constructive debate". It is a powerful method for dealing with case topics that involve…

Development of dual PZT transducers for reference-free crack detection in thin plate structures.

PubMed

Sohn, Hoon; Kim, Seuno Bum

2010-01-01

A new Lamb-wave-based nondestructive testing (NDT) technique, which does not rely on previously stored baseline data, is developed for crack monitoring in plate structures. Commonly, the presence of damage is identified by comparing "current data" measured from a potentially damaged stage of a structure with "baseline data" previously obtained at the intact condition of the structure. In practice, structural defects typically take place long after collection of the baseline data, and the baseline data can be also affected by external loading, temperature variations, and changing boundary conditions. To eliminate the dependence on the baseline data comparison, the authors previously developed a reference-free NDT technique using 2 pairs of collocated lead zirconate titanate (PZT) transducers placed on both sides of a plate. This reference-free technique is further advanced in the present study by the necessity of attaching transducers only on a single surface of a structure for certain applications such as aircraft. To achieve this goal, a new design of PZT transducers called dual PZT transducers is proposed. Crack formation creates Lamb wave mode conversion due to a sudden thickness change of the structure. This crack appearance is instantly detected from the measured Lamb wave signals using the dual PZT transducers. This study also suggests a reference-free statistical approach that enables damage classification using only the currently measured data set. Numerical simulations and experiments were conducted using an aluminum plate with uniform thickness and fundamental Lamb waves modes to demonstrate the applicability of the proposed technique to reference-free crack detection.

Detecting dark matter in the Milky Way with cosmic and gamma radiation

NASA Astrophysics Data System (ADS)

Carlson, Eric C.

Over the last decade, experiments in high-energy astroparticle physics have reached unprecedented precision and sensitivity which span the electromagnetic and cosmic-ray spectra. These advances have opened a new window onto the universe for which little was previously known. Such dramatic increases in sensitivity lead naturally to claims of excess emission, which call for either revised astrophysical models or the existence of exotic new sources such as particle dark matter. Here we stand firmly with Occam, sharpening his razor by (i) developing new techniques for discriminating astrophysical signatures from those of dark matter, and (ii) by developing detailed foreground models which can explain excess signals and shed light on the underlying astrophysical processes at hand. We concentrate most directly on observations of Galactic gamma and cosmic rays, factoring the discussion into three related parts which each contain significant advancements from our cumulative works. In Part I we introduce concepts which are fundamental to the Indirect Detection of particle dark matter, including motivations, targets, experiments, production of Standard Model particles, and a variety of statistical techniques. In Part II we introduce basic and advanced modelling techniques for propagation of cosmic-rays through the Galaxy and describe astrophysical gamma-ray production, as well as presenting state-of-the-art propagation models of the Milky Way.Finally, in Part III, we employ these models and techniques in order to study several indirect detection signals, including the Fermi GeV excess at the Galactic center, the Fermi 135 GeV line, the 3.5 keV line, and the WMAP-Planck haze.

The application of compressed sensing to long-term acoustic emission-based structural health monitoring

NASA Astrophysics Data System (ADS)

Cattaneo, Alessandro; Park, Gyuhae; Farrar, Charles; Mascareñas, David

2012-04-01

The acoustic emission (AE) phenomena generated by a rapid release in the internal stress of a material represent a promising technique for structural health monitoring (SHM) applications. AE events typically result in a discrete number of short-time, transient signals. The challenge associated with capturing these events using classical techniques is that very high sampling rates must be used over extended periods of time. The result is that a very large amount of data is collected to capture a phenomenon that rarely occurs. Furthermore, the high energy consumption associated with the required high sampling rates makes the implementation of high-endurance, low-power, embedded AE sensor nodes difficult to achieve. The relatively rare occurrence of AE events over long time scales implies that these measurements are inherently sparse in the spike domain. The sparse nature of AE measurements makes them an attractive candidate for the application of compressed sampling techniques. Collecting compressed measurements of sparse AE signals will relax the requirements on the sampling rate and memory demands. The focus of this work is to investigate the suitability of compressed sensing techniques for AE-based SHM. The work explores estimating AE signal statistics in the compressed domain for low-power classification applications. In the event compressed classification finds an event of interest, ι1 norm minimization will be used to reconstruct the measurement for further analysis. The impact of structured noise on compressive measurements is specifically addressed. The suitability of a particular algorithm, called Justice Pursuit, to increase robustness to a small amount of arbitrary measurement corruption is investigated.

Digital computer technique for setup and checkout of an analog computer

NASA Technical Reports Server (NTRS)

Ambaruch, R.

1968-01-01

Computer program technique, called Analog Computer Check-Out Routine Digitally /ACCORD/, generates complete setup and checkout data for an analog computer. In addition, the correctness of the analog program implementation is validated.

Discrete geometric analysis of message passing algorithm on graphs

NASA Astrophysics Data System (ADS)

Watanabe, Yusuke

2010-04-01

We often encounter probability distributions given as unnormalized products of non-negative functions. The factorization structures are represented by hypergraphs called factor graphs. Such distributions appear in various fields, including statistics, artificial intelligence, statistical physics, error correcting codes, etc. Given such a distribution, computations of marginal distributions and the normalization constant are often required. However, they are computationally intractable because of their computational costs. One successful approximation method is Loopy Belief Propagation (LBP) algorithm. The focus of this thesis is an analysis of the LBP algorithm. If the factor graph is a tree, i.e. having no cycle, the algorithm gives the exact quantities. If the factor graph has cycles, however, the LBP algorithm does not give exact results and possibly exhibits oscillatory and non-convergent behaviors. The thematic question of this thesis is "How the behaviors of the LBP algorithm are affected by the discrete geometry of the factor graph?" The primary contribution of this thesis is the discovery of a formula that establishes the relation between the LBP, the Bethe free energy and the graph zeta function. This formula provides new techniques for analysis of the LBP algorithm, connecting properties of the graph and of the LBP and the Bethe free energy. We demonstrate applications of the techniques to several problems including (non) convexity of the Bethe free energy, the uniqueness and stability of the LBP fixed point. We also discuss the loop series initiated by Chertkov and Chernyak. The loop series is a subgraph expansion of the normalization constant, or partition function, and reflects the graph geometry. We investigate theoretical natures of the series. Moreover, we show a partial connection between the loop series and the graph zeta function.

Aberrant Expression of Calretinin, D2-40 and Mesothelin in Mucinous and Non-Mucinous Colorectal Carcinomas and Relation to Clinicopathological Features and Prognosis.

PubMed

Foda, Abd AlRahman Mohammad; El-Hawary, Amira Kamal; Hamed, Hazem

2016-10-01

CRC is a heterogeneous disease in terms of morphology, invasive behavior, metastatic capacity, and clinical outcome. Recently, many so-called mesothelial markers, including calretinin, D2-40, WT1, thrombomodulin, mesothelin, and others, have been certified. The aim of this study was to assess the immunohistochemical expression of calretinin and other mesothelial markers (D2-40 and mesothelin) in colorectal mucinous adenocarcinoma (MA) and non mucinous adenocarcinoma (NMA) specimens and relation to clinicopathological features and prognosis using manual tissue microarray technique. We studied tumor tissue specimens from 150 patients with colorectal MA and NMA who underwent radical surgery from January 2007 to January 2012. High-density manual tissue microarrays were constructed using a modified mechanical pencil tip technique, and paraffin sections were submitted for immunohistochemistry using Calretinin, D2-40 and mesothelin expressions. We found that NMA showed significantly more calretinin and D2-40 expression than MA In contrast, no statistically significant difference between NMA and MA was detected in mesothelin expression. There were no statistically significant relations between any of the clinicopathological or histological parameters and any of the three markers. In a univariate analysis, neither calretinin nor D2-40 expressions showed any significant relations to DFS or OS. However, mesothelin luminal expression was significantly associated with worse DFS. Multivariate Cox regression analysis proved that luminal mesothelin expression was an independent negative prognostic factor in NMA. In conclusion, Calretinin, D2-40 and mesothelin are aberrantly expressed in a proportion of CRC cases with more expression in NMA than MA. Aberrant expression of these mesothelial markers was not associated with clinicopathological or histological features of CRCs. Only mesothelin expression appears to be a strong predictor of adverse prognosis.

Powerful Inference with the D-Statistic on Low-Coverage Whole-Genome Data

PubMed Central

Soraggi, Samuele; Wiuf, Carsten; Albrechtsen, Anders

2017-01-01

The detection of ancient gene flow between human populations is an important issue in population genetics. A common tool for detecting ancient admixture events is the D-statistic. The D-statistic is based on the hypothesis of a genetic relationship that involves four populations, whose correctness is assessed by evaluating specific coincidences of alleles between the groups. When working with high-throughput sequencing data, calling genotypes accurately is not always possible; therefore, the D-statistic currently samples a single base from the reads of one individual per population. This implies ignoring much of the information in the data, an issue especially striking in the case of ancient genomes. We provide a significant improvement to overcome the problems of the D-statistic by considering all reads from multiple individuals in each population. We also apply type-specific error correction to combat the problems of sequencing errors, and show a way to correct for introgression from an external population that is not part of the supposed genetic relationship, and how this leads to an estimate of the admixture rate. We prove that the D-statistic is approximated by a standard normal distribution. Furthermore, we show that our method outperforms the traditional D-statistic in detecting admixtures. The power gain is most pronounced for low and medium sequencing depth (1–10×), and performances are as good as with perfectly called genotypes at a sequencing depth of 2×. We show the reliability of error correction in scenarios with simulated errors and ancient data, and correct for introgression in known scenarios to estimate the admixture rates. PMID:29196497

Essentials of Suggestopedia: A Primer for Practitioners.

ERIC Educational Resources Information Center

Caskey, Owen L.; Flake, Muriel H.

Suggestology is the scientific study of the psychology of suggestion and Suggestopedia in the application of relaxation and suggestion techniques to learning. The approach applied to learning processes (called Suggestopedic) developed by Dr. Georgi Lozanov (called the Lozanov Method) utilizes mental and physical relaxation, deep breathing,…

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

40 CFR Appendix K to Part 50 - Interpretation of the National Ambient Air Quality Standards for Particulate Matter

Code of Federal Regulations, 2010 CFR

2010-07-01

..., other techniques, such as the use of statistical models or the use of historical data could be..., mathematical techniques should be applied to account for the trends to ensure that the expected annual values... emission patterns, either the most recent representative year(s) could be used or statistical techniques or...

The living Drake equation of the Tau Zero Foundation

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2011-03-01

The living Drake equation is our statistical generalization of the Drake equation such that it can take into account any number of factors. This new result opens up the possibility to enrich the equation by inserting more new factors as long as the scientific learning increases. The adjective "Living" refers just to this continuous enrichment of the Drake equation and is the goal of a new research project that the Tau Zero Foundation has entrusted to this author as the discoverer of the statistical Drake equation described hereafter. From a simple product of seven positive numbers, the Drake equation is now turned into the product of seven positive random variables. We call this "the Statistical Drake Equation". The mathematical consequences of this transformation are then derived. The proof of our results is based on the Central Limit Theorem (CLT) of Statistics. In loose terms, the CLT states that the sum of any number of independent random variables, each of which may be arbitrarily distributed, approaches a Gaussian (i.e. normal) random variable. This is called the Lyapunov form of the CLT, or the Lindeberg form of the CLT, depending on the mathematical constraints assumed on the third moments of the various probability distributions. In conclusion, we show that: The new random variable N, yielding the number of communicating civilizations in the Galaxy, follows the lognormal distribution. Then, the mean value, standard deviation, mode, median and all the moments of this lognormal N can be derived from the means and standard deviations of the seven input random variables. In fact, the seven factors in the ordinary Drake equation now become seven independent positive random variables. The probability distribution of each random variable may be arbitrary. The CLT in the so-called Lyapunov or Lindeberg forms (that both do not assume the factors to be identically distributed) allows for that. In other words, the CLT "translates" into our statistical Drake equation by allowing an arbitrary probability distribution for each factor. This is both physically realistic and practically very useful, of course. An application of our statistical Drake equation then follows. The (average) distance between any two neighbouring and communicating civilizations in the Galaxy may be shown to be inversely proportional to the cubic root of N. Then, this distance now becomes a new random variable. We derive the relevant probability density function, apparently previously unknown (dubbed "Maccone distribution" by Paul Davies). Data Enrichment Principle. It should be noticed that any positive number of random variables in the statistical Drake equation is compatible with the CLT. So, our generalization allows for many more factors to be added in the future as long as more refined scientific knowledge about each factor will be known to the scientists. This capability to make room for more future factors in the statistical Drake equation we call the "Data Enrichment Principle", and regard as the key to more profound, future results in Astrobiology and SETI.

The Use of a Context-Based Information Retrieval Technique

DTIC Science & Technology

2009-07-01

provided in context. Latent Semantic Analysis (LSA) is a statistical technique for inferring contextual and structural information, and previous studies...WAIS). 10 DSTO-TR-2322 1.4.4 Latent Semantic Analysis LSA, which is also known as latent semantic indexing (LSI), uses a statistical and...1.4.6 Language Models In contrast, natural language models apply algorithms that combine statistical information with semantic information. Semantic

Big data in medical science--a biostatistical view.

PubMed

Binder, Harald; Blettner, Maria

2015-02-27

Inexpensive techniques for measurement and data storage now enable medical researchers to acquire far more data than can conveniently be analyzed by traditional methods. The expression "big data" refers to quantities on the order of magnitude of a terabyte (1012 bytes); special techniques must be used to evaluate such huge quantities of data in a scientifically meaningful way. Whether data sets of this size are useful and important is an open question that currently confronts medical science. In this article, we give illustrative examples of the use of analytical techniques for big data and discuss them in the light of a selective literature review. We point out some critical aspects that should be considered to avoid errors when large amounts of data are analyzed. Machine learning techniques enable the recognition of potentially relevant patterns. When such techniques are used, certain additional steps should be taken that are unnecessary in more traditional analyses; for example, patient characteristics should be differentially weighted. If this is not done as a preliminary step before similarity detection, which is a component of many data analysis operations, characteristics such as age or sex will be weighted no higher than any one out of 10 000 gene expression values. Experience from the analysis of conventional observational data sets can be called upon to draw conclusions about potential causal effects from big data sets. Big data techniques can be used, for example, to evaluate observational data derived from the routine care of entire populations, with clustering methods used to analyze therapeutically relevant patient subgroups. Such analyses can provide complementary information to clinical trials of the classic type. As big data analyses become more popular, various statistical techniques for causality analysis in observational data are becoming more widely available. This is likely to be of benefit to medical science, but specific adaptations will have to be made according to the requirements of the applications.

MAG4 versus alternative techniques for forecasting active region flare productivity.

PubMed

Falconer, David A; Moore, Ronald L; Barghouty, Abdulnasser F; Khazanov, Igor

2014-05-01

MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free magnetic energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the "Present MAG4" technique and each of three alternative techniques, called "McIntosh Active-Region Class," "Total Magnetic Flux," and "Next MAG4." We do this by using (1) the MAG4 database of magnetograms and major flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4). Quantitative comparison of performance of pairs of forecasting techniques Next MAG4 forecasts major flares more accurately than Present MAG4 Present MAG4 forecast outperforms McIntosh AR Class and total magnetic flux.

MAG4 versus alternative techniques for forecasting active region flare productivity

PubMed Central

Falconer, David A; Moore, Ronald L; Barghouty, Abdulnasser F; Khazanov, Igor

2014-01-01

MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free magnetic energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the “Present MAG4” technique and each of three alternative techniques, called “McIntosh Active-Region Class,” “Total Magnetic Flux,” and “Next MAG4.” We do this by using (1) the MAG4 database of magnetograms and major flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4). Key Points Quantitative comparison of performance of pairs of forecasting techniques Next MAG4 forecasts major flares more accurately than Present MAG4 Present MAG4 forecast outperforms McIntosh AR Class and total magnetic flux PMID:26213517

Asymmetries in the individual distinctiveness and maternal recognition of infant contact calls and distress screams in baboons

PubMed Central

Rendall, Drew; Notman, Hugh; Owren, Michael J.

2009-01-01

A key component of nonhuman primate vocal communication is the production and recognition of clear cues to social identity that function in the management of these species’ individualistic social relationships. However, it remains unclear how ubiquitous such identity cues are across call types and age-sex classes and what the underlying vocal production mechanisms responsible might be. This study focused on two structurally distinct call types produced by infant baboons in contexts that place a similar functional premium on communicating clear cues to caller identity: (1) contact calls produced when physically separated from, and attempting to relocate, mothers and (2) distress screams produced when aggressively attacked by other group members. Acoustic analyses and field experiments were conducted to examine individual differentiation in single vocalizations of each type and to test mothers’ ability to recognize infant calls. Both call types showed statistically significant individual differentiation, but the magnitude of the differentiation was substantially higher in contact calls. Mothers readily discriminated own-offspring contact calls from those of familiar but unrelated infants, but did not do so when it came to distress screams. Several possible explanations for these asymmetries in call differentiation and recognition are considered. PMID:19275336

Association between secure patient–clinician email and clinical services utilisation in a US integrated health system: a retrospective cohort study

PubMed Central

Meng, Di; Palen, Ted E; Tsai, Joanne; McLeod, Melanie; Garrido, Terhilda; Qian, Heather

2015-01-01

Objective To assess associations between secure patient–clinician email use and clinical services utilisation over time. Design Retrospective cohort study between July 2010 and December 2013. Controlling for a utilisation surge around first secure email use, we analysed difference of differences between propensity score-matched groups of secure patient–clinician email users and non-users for utilisation 1–12 months before and 7–18 months after first email (users) or a randomly assigned index date (non-users). Setting US integrated healthcare delivery system. Participants 9345 adults with first secure email use between July 2011 and July 2012 and continuous enrolment for ≥30 months and 9345 adults without secure email use between July 2010 and July 2012 matched to users on demographics, health status, and baseline utilisation. Primary Outcome Measures Rates of office visits, patient-initiated phone calls, scheduled telephone visits, after-hours clinic visits, emergency department visits, and hospitalisations. Results After controlling for multiple factors, no statistically significant differences in utilisation between secure email users and non-users occurred. Utilisation transiently increased by 88–237% around first email use. Annual rates of patient-initiated phone calls decreased among secure email users, 0.2 fewer calls per person (95% CI −0.3 to −0.1), from a mean of 4.1 calls per person 1–12 months before first use to a mean of 3.8 calls per person 7–18 months after first use. Rates of patient-initiated phone calls also decreased among non-users, 0.1 fewer calls per person (95% CI −0.2 to 0.0), from a mean of 4.2 calls per person 1–12 months before the index date to mean of 4.1 calls per person 7–18 months after the index date. Conclusions Compared with non-users, patient use of secure email with clinicians was not associated with statistically significant differences in clinical services utilisation 7–18 months after first use. PMID:26553841

Association between secure patient-clinician email and clinical services utilisation in a US integrated health system: a retrospective cohort study.

PubMed

Meng, Di; Palen, Ted E; Tsai, Joanne; McLeod, Melanie; Garrido, Terhilda; Qian, Heather

2015-11-09

To assess associations between secure patient-clinician email use and clinical services utilisation over time. Retrospective cohort study between July 2010 and December 2013. Controlling for a utilisation surge around first secure email use, we analysed difference of differences between propensity score-matched groups of secure patient-clinician email users and non-users for utilisation 1-12 months before and 7-18 months after first email (users) or a randomly assigned index date (non-users). US integrated healthcare delivery system. 9345 adults with first secure email use between July 2011 and July 2012 and continuous enrolment for ≥30 months and 9345 adults without secure email use between July 2010 and July 2012 matched to users on demographics, health status, and baseline utilisation. Rates of office visits, patient-initiated phone calls, scheduled telephone visits, after-hours clinic visits, emergency department visits, and hospitalisations. After controlling for multiple factors, no statistically significant differences in utilisation between secure email users and non-users occurred. Utilisation transiently increased by 88-237% around first email use. Annual rates of patient-initiated phone calls decreased among secure email users, 0.2 fewer calls per person (95% CI -0.3 to -0.1), from a mean of 4.1 calls per person 1-12 months before first use to a mean of 3.8 calls per person 7-18 months after first use. Rates of patient-initiated phone calls also decreased among non-users, 0.1 fewer calls per person (95% CI -0.2 to 0.0), from a mean of 4.2 calls per person 1-12 months before the index date to mean of 4.1 calls per person 7-18 months after the index date. Compared with non-users, patient use of secure email with clinicians was not associated with statistically significant differences in clinical services utilisation 7-18 months after first use. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

FORSPAN Model Users Guide

USGS Publications Warehouse

Klett, T.R.; Charpentier, Ronald R.

2003-01-01

The USGS FORSPAN model is designed for the assessment of continuous accumulations of crude oil, natural gas, and natural gas liquids (collectively called petroleum). Continuous (also called ?unconventional?) accumulations have large spatial dimensions and lack well defined down-dip petroleum/water contacts. Oil and natural gas therefore are not localized by buoyancy in water in these accumulations. Continuous accumulations include ?tight gas reservoirs,? coalbed gas, oil and gas in shale, oil and gas in chalk, and shallow biogenic gas. The FORSPAN model treats a continuous accumulation as a collection of petroleumcontaining cells for assessment purposes. Each cell is capable of producing oil or gas, but the cells may vary significantly from one another in their production (and thus economic) characteristics. The potential additions to reserves from continuous petroleum resources are calculated by statistically combining probability distributions of the estimated number of untested cells having the potential for additions to reserves with the estimated volume of oil and natural gas that each of the untested cells may potentially produce (total recovery). One such statistical method for combination of number of cells with total recovery, used by the USGS, is called ACCESS.

Comparison of repair techniques in small and medium-sized rotator cuff tears in cadaveric sheep shoulders.

PubMed

Onay, Ulaş; Akpınar, Sercan; Akgün, Rahmi Can; Balçık, Cenk; Tuncay, Ismail Cengiz

2013-01-01

The aim of this study was to compare new knotless single-row and double-row suture anchor techniques with traditional transosseous suture techniques for different sized rotator cuff tears in an animal model. The study included 56 cadaveric sheep shoulders. Supraspinatus cuff tears of 1 cm repaired with new knotless single-row suture anchor technique and supraspinatus and infraspinatus rotator cuff tears of 3 cm repaired with double-row suture anchor technique were compared to traditional transosseous suture techniques and control groups. The repaired tendons were loaded with 5 mm/min static velocity with 2.5 kgN load cell in Instron 8874 machine until the repair failure. The 1 cm transosseous group was statistically superior to 1 cm control group (p=0.021, p<0.05) and the 3 cm SpeedBridge group was statistically superior to the 1 cm SpeedFix group (p=0.012, p<0.05). The differences between the other groups were not statistically significant. No significant difference was found between the new knotless suture anchor techniques and traditional transosseous suture techniques.

Non-song social call bouts of migrating humpback whales

PubMed Central

Rekdahl, Melinda L.; Dunlop, Rebecca A.; Goldizen, Anne W.; Garland, Ellen C.; Biassoni, Nicoletta; Miller, Patrick; Noad, Michael J.

2015-01-01

The use of stereotyped calls within structured bouts has been described for a number of species and may increase the information potential of call repertoires. Humpback whales produce a repertoire of social calls, although little is known about the complexity or function of these calls. In this study, digital acoustic tag recordings were used to investigate social call use within bouts, the use of bouts across different social contexts, and whether particular call type combinations were favored. Call order within bouts was investigated using call transition frequencies and information theory techniques. Call bouts were defined through analysis of inter-call intervals, as any calls within 3.9 s of each other. Bouts were produced significantly more when new whales joined a group compared to groups that did not change membership, and in groups containing multiple adults escorting a female and calf compared to adult only groups. Although social calls tended to be produced in bouts, there were few repeated bout types. However, the order in which most call types were produced within bouts was non-random and dependent on the preceding call type. These bouts appear to be at least partially governed by rules for how individual components are combined. PMID:26093396

Non-song social call bouts of migrating humpback whales.

PubMed

Rekdahl, Melinda L; Dunlop, Rebecca A; Goldizen, Anne W; Garland, Ellen C; Biassoni, Nicoletta; Miller, Patrick; Noad, Michael J

2015-06-01

The use of stereotyped calls within structured bouts has been described for a number of species and may increase the information potential of call repertoires. Humpback whales produce a repertoire of social calls, although little is known about the complexity or function of these calls. In this study, digital acoustic tag recordings were used to investigate social call use within bouts, the use of bouts across different social contexts, and whether particular call type combinations were favored. Call order within bouts was investigated using call transition frequencies and information theory techniques. Call bouts were defined through analysis of inter-call intervals, as any calls within 3.9 s of each other. Bouts were produced significantly more when new whales joined a group compared to groups that did not change membership, and in groups containing multiple adults escorting a female and calf compared to adult only groups. Although social calls tended to be produced in bouts, there were few repeated bout types. However, the order in which most call types were produced within bouts was non-random and dependent on the preceding call type. These bouts appear to be at least partially governed by rules for how individual components are combined.

Nebula--a web-server for advanced ChIP-seq data analysis.

PubMed

Boeva, Valentina; Lermine, Alban; Barette, Camille; Guillouf, Christel; Barillot, Emmanuel

2012-10-01

ChIP-seq consists of chromatin immunoprecipitation and deep sequencing of the extracted DNA fragments. It is the technique of choice for accurate characterization of the binding sites of transcription factors and other DNA-associated proteins. We present a web service, Nebula, which allows inexperienced users to perform a complete bioinformatics analysis of ChIP-seq data. Nebula was designed for both bioinformaticians and biologists. It is based on the Galaxy open source framework. Galaxy already includes a large number of functionalities for mapping reads and peak calling. We added the following to Galaxy: (i) peak calling with FindPeaks and a module for immunoprecipitation quality control, (ii) de novo motif discovery with ChIPMunk, (iii) calculation of the density and the cumulative distribution of peak locations relative to gene transcription start sites, (iv) annotation of peaks with genomic features and (v) annotation of genes with peak information. Nebula generates the graphs and the enrichment statistics at each step of the process. During Steps 3-5, Nebula optionally repeats the analysis on a control dataset and compares these results with those from the main dataset. Nebula can also incorporate gene expression (or gene modulation) data during these steps. In summary, Nebula is an innovative web service that provides an advanced ChIP-seq analysis pipeline providing ready-to-publish results. Nebula is available at http://nebula.curie.fr/ Supplementary data are available at Bioinformatics online.

Interobserver Agreement Among Uveitis Experts on Uveitic Diagnoses: The Standardization of Uveitis Nomenclature Experience.

PubMed

Jabs, Douglas A; Dick, Andrew; Doucette, John T; Gupta, Amod; Lightman, Susan; McCluskey, Peter; Okada, Annabelle A; Palestine, Alan G; Rosenbaum, James T; Saleem, Sophia M; Thorne, Jennifer; Trusko, Brett

2018-02-01

To evaluate the interobserver agreement among uveitis experts on the diagnosis of the specific uveitic disease. Interobserver agreement analysis. Five committees, each comprised of 9 individuals and working in parallel, reviewed cases from a preliminary database of 25 uveitic diseases, collected by disease, and voted independently online whether the case was the disease in question or not. The agreement statistic, κ, was calculated for the 36 pairwise comparisons for each disease, and a mean κ was calculated for each disease. After the independent online voting, committee consensus conference calls, using nominal group techniques, reviewed all cases not achieving supermajority agreement (>75%) on the diagnosis in the online voting to attempt to arrive at a supermajority agreement. A total of 5766 cases for the 25 diseases were evaluated. The overall mean κ for the entire project was 0.39, with disease-specific variation ranging from 0.23 to 0.79. After the formalized consensus conference calls to address cases that did not achieve supermajority agreement in the online voting, supermajority agreement overall was reached on approximately 99% of cases, with disease-specific variation ranging from 96% to 100%. Agreement among uveitis experts on diagnosis is moderate at best but can be improved by discussion among them. These data suggest the need for validated and widely used classification criteria in the field of uveitis. Copyright © 2017 Elsevier Inc. All rights reserved.

Inverse Function: Pre-Service Teachers' Techniques and Meanings

ERIC Educational Resources Information Center

Paoletti, Teo; Stevens, Irma E.; Hobson, Natalie L. F.; Moore, Kevin C.; LaForest, Kevin R.

2018-01-01

Researchers have argued teachers and students are not developing connected meanings for function inverse, thus calling for a closer examination of teachers' and students' inverse function meanings. Responding to this call, we characterize 25 pre-service teachers' inverse function meanings as inferred from our analysis of clinical interviews. After…

Perspectives: A Challenging Patriotism

ERIC Educational Resources Information Center

Boyte, Harry C.

2012-01-01

In a time of alarm about the poisoning of electoral politics, public passions inflamed by sophisticated techniques of mass polarization, and fears that the country is losing control of its collective future, higher education is called upon to take leadership in "reinventing citizenship." It needs to respond to that call on a scale unprecedented in…

Teaching Free Expression in Word and Example (Commentary).

ERIC Educational Resources Information Center

Merrill, John

1991-01-01

Suggests that the teaching of free expression may be the highest calling of a communications or journalism professor. Argues that freedom must be tempered by a sense of ethics. Calls upon teachers to encourage students to analyze the questions surrounding free expression. Describes techniques for scrutinizing journalistic myths. (SG)

Hands-free human-machine interaction with voice

NASA Astrophysics Data System (ADS)

Juang, B. H.

2004-05-01

Voice is natural communication interface between a human and a machine. The machine, when placed in today's communication networks, may be configured to provide automation to save substantial operating cost, as demonstrated in AT&T's VRCP (Voice Recognition Call Processing), or to facilitate intelligent services, such as virtual personal assistants, to enhance individual productivity. These intelligent services often need to be accessible anytime, anywhere (e.g., in cars when the user is in a hands-busy-eyes-busy situation or during meetings where constantly talking to a microphone is either undersirable or impossible), and thus call for advanced signal processing and automatic speech recognition techniques which support what we call ``hands-free'' human-machine communication. These techniques entail a broad spectrum of technical ideas, ranging from use of directional microphones and acoustic echo cancellatiion to robust speech recognition. In this talk, we highlight a number of key techniques that were developed for hands-free human-machine communication in the mid-1990s after Bell Labs became a unit of Lucent Technologies. A video clip will be played to demonstrate the accomplishement.

Reanalysis of Tyrannosaurus rex Mass Spectra.

PubMed

Bern, Marshall; Phinney, Brett S; Goldberg, David

2009-09-01

Asara et al. reported the detection of collagen peptides in a 68-million-year-old Tyrannosaurus rex bone by shotgun proteomics. This finding has been called into question as a possible statistical artifact. We reanalyze Asara et al.'s tandem mass spectra using a different search engine and different statistical tools. Our reanalysis shows a sample containing common laboratory contaminants, soil bacteria, and bird-like hemoglobin and collagen.

An Item Fit Statistic Based on Pseudocounts from the Generalized Graded Unfolding Model: A Preliminary Report.

ERIC Educational Resources Information Center

Roberts, James S.

Stone and colleagues (C. Stone, R. Ankenman, S. Lane, and M. Liu, 1993; C. Stone, R. Mislevy and J. Mazzeo, 1994; C. Stone, 2000) have proposed a fit index that explicitly accounts for the measurement error inherent in an estimated theta value, here called chi squared superscript 2, subscript i*. The elements of this statistic are natural…

Compositionality and Statistics in Adjective Acquisition: 4-Year-Olds Interpret "Tall" and "Short" Based on the Size Distributions of Novel Noun Referents

ERIC Educational Resources Information Center

Barner, David; Snedeker, Jesse

2008-01-01

Four experiments investigated 4-year-olds' understanding of adjective-noun compositionality and their sensitivity to statistics when interpreting scalar adjectives. In Experiments 1 and 2, children selected "tall" and "short" items from 9 novel objects called "pimwits" (1-9 in. in height) or from this array plus 4 taller or shorter distractor…

Screening Health Risk Assessment Burn Pit Exposures, Balad Air Base, Iraq and Addendum Report

DTIC Science & Technology

2008-05-01

risk uses principles drawn from many scientific disciplines including chemistry , toxicology, physics, mathematics, and statistics. Because the data...uses principles drawn from many scientific disciplines, including chemistry , toxicology, physics, mathematics, and statistics. Because the data...natural chemicals in plants (called flavonoids ) also act on the Ah-receptor and could potentially block the effects of dioxins. One more reason to

The accuracy of the lateral vertebral notch-referred pedicle screw insertion technique in subaxial cervical spine: a human cadaver study.

PubMed

Luo, Jiaquan; Wu, Chunyang; Huang, Zhongren; Pan, Zhimin; Li, Zhiyun; Zhong, Junlong; Chen, Yiwei; Han, Zhimin; Cao, Kai

2017-04-01

This is a cadaver specimen study to confirm new pedicle screw (PS) entry point and trajectory for subaxial cervical PS insertion. To assess the accuracy of the lateral vertebral notch-referred PS insertion technique in subaxial cervical spine in cadaver cervical spine. Reported morphometric landmarks used to guide the surgeon in PS insertion show significant variability. In the previous study, we proposed a new technique (as called "notch-referred" technique) primarily based on coronal multiplane reconstruction images (CMRI) and cortical integrity after PS insertion in cadavers. However, the PS position in cadaveric cervical segment was not confirmed radiologically. Therefore, the difference between the pedicle trajectory and the PS trajectory using the notch-referred technique needs to be illuminated. Twelve cadaveric cervical spines were conducted with PS insertion using the lateral vertebral notch-referred technique. The guideline for entry point and trajectory for each vertebra was established based on the morphometric data from our previous study. After 3.5-mm diameter screw insertion, each vertebra was dissected and inspected for pedicle trajectory by CT scan. The pedicle trajectory and PS trajectory were measured and compared in axial plane. The perforation rate was assessed radiologically and was graded from ideal to unacceptable: Grade 0 = screw in pedicle; Grade I = perforation of pedicle wall less than one-fourth of the screw diameter; Grade II = perforation more than one-fourth of the screw diameter but less than one-second; Grade III = perforation more than one-second outside of the screw diameter. In addition, pedicle width between the acceptable and unacceptable screws was compared. A total of 120 pedicle screws were inserted. The perforation rate of pedicle screws was 78.3% in grade 0 (excellent PS position), 10.0% in grade I (good PS position), 8.3% in grade II (fair PS position), and 3.3% in grade III (poor PS position). The overall accepted accuracy of pedicle screws was 96.7% (Grade 0 + Grade I + Grade II), and only 3.3% had critical breach. There was no statistical difference between the pedicle trajectory and PS trajectory (p > 0.05). Compared to the pedicle width (4.4 ± 0.7 mm) in acceptably inserted screw, the unacceptably screw is 3.2 ± 0.3 mm which was statistically different (p < 0.05). The accuracy of the notch-referred PS insertion in cadaveric subaxial cervical spine is satisfactory.

Comparing Noun Phrasing Techniques for Use with Medical Digital Library Tools.

ERIC Educational Resources Information Center

Tolle, Kristin M.; Chen, Hsinchun

2000-01-01

Describes a study that investigated the use of a natural language processing technique called noun phrasing to determine whether it is a viable technique for medical information retrieval. Evaluates four noun phrase generation tools for their ability to isolate noun phrases from medical journal abstracts, focusing on precision and recall.…

Underwater Photo-Elicitation: A New Experiential Marine Education Technique

ERIC Educational Resources Information Center

Andrews, Steve; Stocker, Laura; Oechel, Walter

2018-01-01

Underwater photo-elicitation is a novel experiential marine education technique that combines direct experience in the marine environment with the use of digital underwater cameras. A program called Show Us Your Ocean! (SUYO!) was created, utilising a mixed methodology (qualitative and quantitative methods) to test the efficacy of this technique.…

Q-Technique and Graphics Research.

ERIC Educational Resources Information Center

Kahle, Roger R.

Because Q-technique is as appropriate for use with visual and design items as for use with words, it is not stymied by the topics one is likely to encounter in graphics research. In particular Q-technique is suitable for studying the so-called "congeniality" of typography, for various copytesting usages, and for multivariate graphics research. The…

Writing with Basals: A Sentence Combining Approach to Comprehension.

ERIC Educational Resources Information Center

Reutzel, D. Ray; Merrill, Jimmie D.

Sentence combining techniques can be used with basal readers to help students develop writing skills. The first technique is addition, characterized by using the connecting word "and" to join two or more base sentences together. The second technique is called "embedding," and is characterized by putting parts of two or more base sentences together…

Design of order statistics filters using feedforward neural networks

NASA Astrophysics Data System (ADS)

Maslennikova, Yu. S.; Bochkarev, V. V.

2016-08-01

In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.

Statistical evaluation of vibration analysis techniques

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Miller, Patrice S.

1987-01-01

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

A Feasibility Study of the Collection of Unscheduled Maintenance Data Using Statistical Sampling Techniques.

DTIC Science & Technology

1985-09-01

TECHNIQUES THESIS Robert A. Heinlein Captain, USAF AFIT/GLM/LSM/855-32.- _ DTIC MU’noN ’ST.,TEMENT A A-ZELECTE Approved lt public teleo*I Al \\ Z #&N0V21...343" A FEASIBILITY STUDY OF THE COLLECTION OF UNSCHEDULED MAINTENANCE DATA USING STrATISTICAL SAMPLING TECHNIQUES THESIS L .9 Robe-t A. Heinlein...a AFIT/GLM/LSM/85S-32 A FEASIBILITY STUDY OF THE COLLECTION OF UNSCHEDULED MAINTENANCE DATA USING STATISTICAL SAMPLING TECHNIQUES THESIS

Recall accuracy of mobile phone calls among Japanese young people.

PubMed

Kiyohara, Kosuke; Wake, Kanako; Watanabe, Soichi; Arima, Takuji; Sato, Yasuto; Kojimahara, Noriko; Taki, Masao; Yamaguchi, Naohito

2016-11-01

This study aimed to elucidate the recall accuracy of mobile phone calls among young people using new software-modified phone (SMP) technology. A total of 198 Japanese students aged between 10 and 24 years were instructed to use a SMP for 1 month to record their actual call statuses. Ten to 12 months after this period, face-to-face interviews were conducted to obtain the self-reported call statuses during the monitoring period. Using the SMP record as the gold standard of validation, the recall accuracy of phone calls was evaluated. A total of 19% of the participants (34/177) misclassified their laterality (i.e., the dominant side of ear used while making calls), with the level of agreement being moderate (κ-statistics, 0.449). The level of agreement between the self-reports and SMP records was relatively good for the duration of calls (Pearson's r, 0.620), as compared with the number of calls (Pearson's r, 0.561). The recall was prone to small systematic and large random errors for both the number and duration of calls. Such a large random recall error for the amount of calls and misclassification of laterality suggest that the results of epidemiological studies of mobile phone use based on self-assessment should be interpreted cautiously.

A Self-Organizing Maps approach to assess the wave climate of the Adriatic Sea

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Marcello Falcieri, Francesco; Scotton, Carlotta; Benetazzo, Alvise; Bergamasco, Andrea; Bergamasco, Filippo; Bonaldo, Davide; Carniel, Sandro; Sclavo, Mauro

2015-04-01

The assessment of wave conditions at sea is fruitful for many research fields in marine and atmospheric sciences and for the human activities in the marine environment. To this end, in the last decades the observational network, that mostly relies on buoys, satellites and other probes from fixed platforms, has been integrated with numerical models outputs, which allow to compute the parameters of sea states (e.g. the significant wave height, the mean and peak wave periods, the mean and peak wave directions) over wider regions. Apart from the collection of wave parameters observed at specific sites or modeled on arbitrary domains, the data processing performed to infer the wave climate at those sites is a crucial step in order to provide high quality data and information to the community. In this context, several statistical techniques has been used to model the randomness of wave parameters. While univariate and bivariate probability distribution functions (pdf) are routinely used, multivariate pdfs that model the probability structure of more than two wave parameters are hardly managed. Recently, the Self-Organizing Maps (SOM) technique has been successfully applied to represent the multivariate random wave climate at sites around the Iberian peninsula and the South America continent. Indeed, the visualization properties offered by this technique allow to get the dependencies between the different parameters by visual inspection. In this study, carried out in the frame of the Italian National Flagship Project "RITMARE", we take advantage of the SOM technique to assess the multivariate wave climate over the Adriatic Sea, a semi-enclosed basin in the north-eastern Mediterranean Sea, where winds from North-East (called "Bora") and South-East (called "Sirocco") mainly blow causing sea storms. By means of the SOM techniques we can observe the multivariate character of the typical Bora and Sirocco wave features in the Adriatic Sea. To this end, we used both observed and modeled wave parameters. The "Acqua Alta" oceanographic tower in the northern Adriatic Sea (ISMAR-CNR) and the Italian Data Buoy Network (RON, managed by ISPRA) off the western Adriatic coasts furnished the wave parameters at specific sites of interest. Widespread wave parameters were obtained by means of a numerical SWAN wave model that was implemented on the whole Adriatic Sea with a 6x6 km2 resolution and forced by the high resolution COSMO-I7 atmospheric model for the period 2007-2013.

Impact of iron particles in groundwater on the UV inactivation of bacteriophages MS2 and T4.

PubMed

Templeton, M R; Andrews, R C; Hofmann, R

2006-09-01

To investigate the impact of iron particles in groundwater on the inactivation of two model viruses, bacteriophages MS2 and T4, by 254-nm ultraviolet (UV) light. One-litre samples of groundwater with high iron content (from the Indianapolis Water Company, mean dissolved iron concentration 1.3 mg l(-1)) were stirred vigorously while exposed to air, which oxidized and precipitated the dissolved iron. In parallel samples, ethylenediaminetetra-acetic acid (EDTA) was added to chelate the iron and prevent formation of iron precipitate. The average turbidity in the samples without EDTA (called the 'raw' samples) after 210 min of stirring was 2.7 +/- 0.1 NTU while the average turbidity of the samples containing EDTA (called the 'preserved' samples) was 1.0 +/- 0.1 NTU. 'Raw' and 'preserved' samples containing bacteriophage MS2 were exposed to 254-nm UV light at doses of 20, 40, or 60 mJ (cm(2))(-1), while samples containing bacteriophage T4 were exposed to 2 or 5 mJ (cm(2))(-1), using a low pressure UV collimated beam. The UV inactivation of both phages in the 'raw' groundwater was lower than in the EDTA-'preserved' groundwater to a statistically significant degree (alpha = 0.05), due to the association of phage with the UV-absorbing iron precipitate particles. A phage elution technique confirmed that a large fraction of the phage that survived the UV exposures were particle-associated. Phages that are associated with iron oxide particles in groundwater are shielded from UV light to a measurable and statistically significant degree at a turbidity level of 2.7 NTU when the phage particle association is induced under experimental conditions. While the particle association of the phage in this study was induced experimentally, the findings provide further evidence that certain particles in natural waters and wastewaters (e.g. iron oxide particles) may have the potential to shield viruses from UV light.

The Statistical Drake Equation

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2010-12-01

We provide the statistical generalization of the Drake equation. From a simple product of seven positive numbers, the Drake equation is now turned into the product of seven positive random variables. We call this "the Statistical Drake Equation". The mathematical consequences of this transformation are then derived. The proof of our results is based on the Central Limit Theorem (CLT) of Statistics. In loose terms, the CLT states that the sum of any number of independent random variables, each of which may be ARBITRARILY distributed, approaches a Gaussian (i.e. normal) random variable. This is called the Lyapunov Form of the CLT, or the Lindeberg Form of the CLT, depending on the mathematical constraints assumed on the third moments of the various probability distributions. In conclusion, we show that: The new random variable N, yielding the number of communicating civilizations in the Galaxy, follows the LOGNORMAL distribution. Then, as a consequence, the mean value of this lognormal distribution is the ordinary N in the Drake equation. The standard deviation, mode, and all the moments of this lognormal N are also found. The seven factors in the ordinary Drake equation now become seven positive random variables. The probability distribution of each random variable may be ARBITRARY. The CLT in the so-called Lyapunov or Lindeberg forms (that both do not assume the factors to be identically distributed) allows for that. In other words, the CLT "translates" into our statistical Drake equation by allowing an arbitrary probability distribution for each factor. This is both physically realistic and practically very useful, of course. An application of our statistical Drake equation then follows. The (average) DISTANCE between any two neighboring and communicating civilizations in the Galaxy may be shown to be inversely proportional to the cubic root of N. Then, in our approach, this distance becomes a new random variable. We derive the relevant probability density function, apparently previously unknown and dubbed "Maccone distribution" by Paul Davies. DATA ENRICHMENT PRINCIPLE. It should be noticed that ANY positive number of random variables in the Statistical Drake Equation is compatible with the CLT. So, our generalization allows for many more factors to be added in the future as long as more refined scientific knowledge about each factor will be known to the scientists. This capability to make room for more future factors in the statistical Drake equation, we call the "Data Enrichment Principle," and we regard it as the key to more profound future results in the fields of Astrobiology and SETI. Finally, a practical example is given of how our statistical Drake equation works numerically. We work out in detail the case, where each of the seven random variables is uniformly distributed around its own mean value and has a given standard deviation. For instance, the number of stars in the Galaxy is assumed to be uniformly distributed around (say) 350 billions with a standard deviation of (say) 1 billion. Then, the resulting lognormal distribution of N is computed numerically by virtue of a MathCad file that the author has written. This shows that the mean value of the lognormal random variable N is actually of the same order as the classical N given by the ordinary Drake equation, as one might expect from a good statistical generalization.

An implementation and performance measurement of the progressive retry technique

NASA Technical Reports Server (NTRS)

Suri, Gaurav; Huang, Yennun; Wang, Yi-Min; Fuchs, W. Kent; Kintala, Chandra

1995-01-01

This paper describes a recovery technique called progressive retry for bypassing software faults in message-passing applications. The technique is implemented as reusable modules to provide application-level software fault tolerance. The paper describes the implementation of the technique and presents results from the application of progressive retry to two telecommunications systems. the results presented show that the technique is helpful in reducing the total recovery time for message-passing applications.

Perspective on Kraken Mare Shores

NASA Image and Video Library

2015-02-12

This Cassini Synthetic Aperture Radar (SAR) image is presented as a perspective view and shows a landscape near the eastern shoreline of Kraken Mare, a hydrocarbon sea in Titan's north polar region. This image was processed using a technique for handling noise that results in clearer views that can be easier for researchers to interpret. The technique, called despeckling, also is useful for producing altimetry data and 3-D views called digital elevation maps. Scientists have used a technique called radargrammetry to determine the altitude of surface features in this view at a resolution of approximately half a mile, or 1 kilometer. The altimetry reveals that the area is smooth overall, with a maximum amplitude of 0.75 mile (1.2 kilometers) in height. The topography also shows that all observed channels flow downhill. The presence of what scientists call "knickpoints" -- locations on a river where a sharp change in slope occurs -- might indicate stratification in the bedrock, erosion mechanisms at work or a particular way the surface responds to runoff events, such as floods following large storms. One such knickpoint is visible just above the lower left corner, where an area of bright slopes is seen. The image was obtained during a flyby of Titan on April 10, 2007. A more traditional radar image of this area on Titan is seen in PIA19046. http://photojournal.jpl.nasa.gov/catalog/PIA19051

Gene Profiling Technique to Accelerate Stem Cell Therapies for Eye Diseases

MedlinePlus

... like RPE. They also use a technique called quantitative RT-PCR to measure the expression of genes ... higher in iPS cells than mature RPE. But quantitative RT-PCR only permits the simultaneous measurement of ...

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

39 CFR 3050.1 - Definitions applicable to this part.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., mathematical, or statistical theory, precept, or assumption applied by the Postal Service in producing a... manipulation technique whose validity does not require the acceptance of a particular economic, mathematical, or statistical theory, precept, or assumption. A change in quantification technique should not change...

CMB EB and TB cross-spectrum estimation via pseudospectrum techniques

NASA Astrophysics Data System (ADS)

Grain, J.; Tristram, M.; Stompor, R.

2012-10-01

We discuss methods for estimating EB and TB spectra of the cosmic microwave background anisotropy maps covering limited sky area. Such odd-parity correlations are expected to vanish whenever parity is not broken. As this is indeed the case in the standard cosmologies, any evidence to the contrary would have a profound impact on our theories of the early Universe. Such correlations could also become a sensitive diagnostic of some particularly insidious instrumental systematics. In this work we introduce three different unbiased estimators based on the so-called standard and pure pseudo-spectrum techniques and later assess their performance by means of extensive Monte Carlo simulations performed for different experimental configurations. We find that a hybrid approach combining a pure estimate of B-mode multipoles with a standard one for E-mode (or T) multipoles, leads to the smallest error bars for both EB (or TB respectively) spectra as well as for the three other polarization-related angular power spectra (i.e., EE, BB, and TE). However, if both E and B multipoles are estimated using the pure technique, the loss of precision for the EB spectrum is not larger than ˜30%. Moreover, for the experimental configurations considered here, the statistical uncertainties-due to sampling variance and instrumental noise-of the pseudo-spectrum estimates is at most a factor ˜1.4 for TT, EE, and TE spectra and a factor ˜2 for BB, TB, and EB spectra, higher than the most optimistic Fisher estimate of the variance.

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

NASA Technical Reports Server (NTRS)

Lam, N.; Qiu, H.-I.; Quattrochi, Dale A.; Zhao, Wei

1997-01-01

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis.

PubMed

Martinez-Murcia, Francisco Jesús; Lai, Meng-Chuan; Górriz, Juan Manuel; Ramírez, Javier; Young, Adam M H; Deoni, Sean C L; Ecker, Christine; Lombardo, Michael V; Baron-Cohen, Simon; Murphy, Declan G M; Bullmore, Edward T; Suckling, John

2017-03-01

Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208-1223, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2012-01-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

3D-QSPR Method of Computational Technique Applied on Red Reactive Dyes by Using CoMFA Strategy

PubMed Central

Mahmood, Uzma; Rashid, Sitara; Ali, S. Ishrat; Parveen, Rasheeda; Zaheer-ul-Haq; Ambreen, Nida; Khan, Khalid Mohammed; Perveen, Shahnaz; Voelter, Wolfgang

2011-01-01

Cellulose fiber is a tremendous natural resource that has broad application in various productions including the textile industry. The dyes, which are commonly used for cellulose printing, are “reactive dyes” because of their high wet fastness and brilliant colors. The interaction of various dyes with the cellulose fiber depends upon the physiochemical properties that are governed by specific features of the dye molecule. The binding pattern of the reactive dye with cellulose fiber is called the ligand-receptor concept. In the current study, the three dimensional quantitative structure property relationship (3D-QSPR) technique was applied to understand the red reactive dyes interactions with the cellulose by the Comparative Molecular Field Analysis (CoMFA) method. This method was successfully utilized to predict a reliable model. The predicted model gives satisfactory statistical results and in the light of these, it was further analyzed. Additionally, the graphical outcomes (contour maps) help us to understand the modification pattern and to correlate the structural changes with respect to the absorptivity. Furthermore, the final selected model has potential to assist in understanding the charachteristics of the external test set. The study could be helpful to design new reactive dyes with better affinity and selectivity for the cellulose fiber. PMID:22272108

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

NASA Astrophysics Data System (ADS)

Fort, G.; Jourdain, B.; Lelièvre, T.; Stoltz, G.

2018-04-01

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang-Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

The Visual Analogue Scale for Rating, Ranking and Paired-Comparison (VAS-RRP): A new technique for psychological measurement.

PubMed

Sung, Yao-Ting; Wu, Jeng-Shin

2018-04-17

Traditionally, the visual analogue scale (VAS) has been proposed to overcome the limitations of ordinal measures from Likert-type scales. However, the function of VASs to overcome the limitations of response styles to Likert-type scales has not yet been addressed. Previous research using ranking and paired comparisons to compensate for the response styles of Likert-type scales has suffered from limitations, such as that the total score of ipsative measures is a constant that cannot be analyzed by means of many common statistical techniques. In this study we propose a new scale, called the Visual Analogue Scale for Rating, Ranking, and Paired-Comparison (VAS-RRP), which can be used to collect rating, ranking, and paired-comparison data simultaneously, while avoiding the limitations of each of these data collection methods. The characteristics, use, and analytic method of VAS-RRPs, as well as how they overcome the disadvantages of Likert-type scales, ranking, and VASs, are discussed. On the basis of analyses of simulated and empirical data, this study showed that VAS-RRPs improved reliability, response style bias, and parameter recovery. Finally, we have also designed a VAS-RRP Generator for researchers' construction and administration of their own VAS-RRPs.

Principle of the electrically induced Transient Current Technique

NASA Astrophysics Data System (ADS)

Bronuzzi, J.; Moll, M.; Bouvet, D.; Mapelli, A.; Sallese, J. M.

2018-05-01

In the field of detector development for High Energy Physics, the so-called Transient Current Technique (TCT) is used to characterize the electric field profile and the charge trapping inside silicon radiation detectors where particles or photons create electron-hole pairs in the bulk of a semiconductor device, as PiN diodes. In the standard approach, the TCT signal originates from the free carriers generated close to the surface of a silicon detector, by short pulses of light or by alpha particles. This work proposes a new principle of charge injection by means of lateral PN junctions implemented in one of the detector electrodes, called the electrical TCT (el-TCT). This technique is fully compatible with CMOS technology and therefore opens new perspectives for assessment of radiation detectors performances.

A Study on Predictive Analytics Application to Ship Machinery Maintenance

DTIC Science & Technology

2013-09-01

Looking at the nature of the time series forecasting method , it would be better applied to offline analysis . The application for real- time online...other system attributes in future. Two techniques of statistical analysis , mainly time series models and cumulative sum control charts, are discussed in...statistical tool employed for the two techniques of statistical analysis . Both time series forecasting as well as CUSUM control charts are shown to be

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis

PubMed Central

Bilgrami, Irma; Bain, Christopher; Webb, Geoffrey I.; Orosz, Judit; Pilcher, David

2017-01-01

Introduction Hospitals have seen a rise in Medical Emergency Team (MET) reviews. We hypothesised that the commonest MET calls result in similar treatments. Our aim was to design a pre-emptive management algorithm that allowed direct institution of treatment to patients without having to wait for attendance of the MET team and to model its potential impact on MET call incidence and patient outcomes. Methods Data was extracted for all MET calls from the hospital database. Association rule data mining techniques were used to identify the most common combinations of MET call causes, outcomes and therapies. Results There were 13,656 MET calls during the 34-month study period in 7936 patients. The most common MET call was for hypotension [31%, (2459/7936)]. These MET calls were strongly associated with the immediate administration of intra-venous fluid (70% [1714/2459] v 13% [739/5477] p<0.001), unless the patient was located on a respiratory ward (adjusted OR 0.41 [95%CI 0.25–0.67] p<0.001), had a cardiac cause for admission (adjusted OR 0.61 [95%CI 0.50–0.75] p<0.001) or was under the care of the heart failure team (adjusted OR 0.29 [95%CI 0.19–0.42] p<0.001). Modelling the effect of a pre-emptive management algorithm for immediate fluid administration without MET activation on data from a test period of 24 months following the study period, suggested it would lead to a 68.7% (2541/3697) reduction in MET calls for hypotension and a 19.6% (2541/12938) reduction in total METs without adverse effects on patients. Conclusion Routinely collected data and analytic techniques can be used to develop a pre-emptive management algorithm to administer intravenous fluid therapy to a specific group of hypotensive patients without the need to initiate a MET call. This could both lead to earlier treatment for the patient and less total MET calls. PMID:29281665

Semantic Importance Sampling for Statistical Model Checking

DTIC Science & Technology

2015-01-16

SMT calls while maintaining correctness. Finally, we implement SIS in a tool called osmosis and use it to verify a number of stochastic systems with...2 surveys related work. Section 3 presents background definitions and concepts. Section 4 presents SIS, and Section 5 presents our tool osmosis . In...which I∗M|=Φ(x) = 1. We do this by first randomly selecting a cube c from C∗ with uniform probability since each cube has equal probability 9 5. OSMOSIS

Measuring the effectiveness of patient-chosen reminder methods in a private orthodontic practice.

PubMed

Wegrzyniak, Lauren M; Hedderly, Deborah; Chaudry, Kishore; Bollu, Prashanti

2018-05-01

To evaluate the effectiveness of patient-chosen appointment reminder methods (phone call, e-mail, or SMS text) in reducing no-show rates. This was a retrospective case study that determined the correlation between patient-chosen appointment reminder methods and no-show rates in a private orthodontic practice. This study was conducted in a single office location of a multioffice private orthodontic practice using data gathered in 2015. The subjects were patients who self-selected the appointment reminder method (phone call, e-mail, or SMS text). Patient appointment data were collected over a 6-month period. Patient attendance was analyzed with descriptive statistics to determine any significant differences among patient-chosen reminder methods. There was a total of 1193 appointments with an average no-show rate of 2.43% across the three reminder methods. No statistically significant differences ( P = .569) were observed in the no-show rates between the three methods: phone call (3.49%), e-mail (2.68%), and SMS text (1.90%). The electronic appointment reminder methods (SMS text and e-mail) had lower no-show rates compared with the phone call method, with SMS text having the lowest no-show rate of 1.90%. However, since no significant differences were observed between the three patient-chosen reminder methods, providers may want to allow patients to choose their reminder method to decrease no-shows.

An intercomparison of a large ensemble of statistical downscaling methods for Europe: Overall results from the VALUE perfect predictor cross-validation experiment

NASA Astrophysics Data System (ADS)

Gutiérrez, Jose Manuel; Maraun, Douglas; Widmann, Martin; Huth, Radan; Hertig, Elke; Benestad, Rasmus; Roessler, Ole; Wibig, Joanna; Wilcke, Renate; Kotlarski, Sven

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. This framework is based on a user-focused validation tree, guiding the selection of relevant validation indices and performance measures for different aspects of the validation (marginal, temporal, spatial, multi-variable). Moreover, several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur (assessment of intrinsic performance, effect of errors inherited from the global models, effect of non-stationarity, etc.). The list of downscaling experiments includes 1) cross-validation with perfect predictors, 2) GCM predictors -aligned with EURO-CORDEX experiment- and 3) pseudo reality predictors (see Maraun et al. 2015, Earth's Future, 3, doi:10.1002/2014EF000259, for more details). The results of these experiments are gathered, validated and publicly distributed through the VALUE validation portal, allowing for a comprehensive community-open downscaling intercomparison study. In this contribution we describe the overall results from Experiment 1), consisting of a European wide 5-fold cross-validation (with consecutive 6-year periods from 1979 to 2008) using predictors from ERA-Interim to downscale precipitation and temperatures (minimum and maximum) over a set of 86 ECA&D stations representative of the main geographical and climatic regions in Europe. As a result of the open call for contribution to this experiment (closed in Dec. 2015), over 40 methods representative of the main approaches (MOS and Perfect Prognosis, PP) and techniques (linear scaling, quantile mapping, analogs, weather typing, linear and generalized regression, weather generators, etc.) were submitted, including information both data (downscaled values) and metadata (characterizing different aspects of the downscaling methods). This constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods. Here, we present an overall validation, analyzing marginal and temporal aspects to assess the intrinsic performance and added value of statistical downscaling methods at both annual and seasonal levels. This validation takes into account the different properties/limitations of different approaches and techniques (as reported in the provided metadata) in order to perform a fair comparison. It is pointed out that this experiment alone is not sufficient to evaluate the limitations of (MOS) bias correction techniques. Moreover, it also does not fully validate PP since we don't learn whether we have the right predictors and whether the PP assumption is valid. These problems will be analyzed in the subsequent community-open VALUE experiments 2) and 3), which will be open for participation along the present year.

Teaching Business Management to Engineers: The Impact of Interactive Lectures

ERIC Educational Resources Information Center

Rambocas, Meena; Sastry, Musti K. S.

2017-01-01

Some education specialists are challenging the use of traditional strategies in classrooms and are calling for the use of contemporary teaching and learning techniques. In response to these calls, many field experiments that compare different teaching and learning strategies have been conducted. However, to date, little is known on the outcomes of…

78 FR 69705 - 60-Day Notice of Proposed Information Collection: Mortgagee's Application for Partial Settlement

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-20

... calling the toll-free Federal Relay Service at (800) 877-8339. FOR FURTHER INFORMATION CONTACT: Steve... through TTY by calling the toll-free Federal Relay Service at (800) 877-8339. Copies of available... techniques or other forms of information technology, e.g., permitting electronic submission of responses. HUD...

Powerful Inference with the D-Statistic on Low-Coverage Whole-Genome Data.

PubMed

Soraggi, Samuele; Wiuf, Carsten; Albrechtsen, Anders

2018-02-02

The detection of ancient gene flow between human populations is an important issue in population genetics. A common tool for detecting ancient admixture events is the D-statistic. The D-statistic is based on the hypothesis of a genetic relationship that involves four populations, whose correctness is assessed by evaluating specific coincidences of alleles between the groups. When working with high-throughput sequencing data, calling genotypes accurately is not always possible; therefore, the D-statistic currently samples a single base from the reads of one individual per population. This implies ignoring much of the information in the data, an issue especially striking in the case of ancient genomes. We provide a significant improvement to overcome the problems of the D-statistic by considering all reads from multiple individuals in each population. We also apply type-specific error correction to combat the problems of sequencing errors, and show a way to correct for introgression from an external population that is not part of the supposed genetic relationship, and how this leads to an estimate of the admixture rate. We prove that the D-statistic is approximated by a standard normal distribution. Furthermore, we show that our method outperforms the traditional D-statistic in detecting admixtures. The power gain is most pronounced for low and medium sequencing depth (1-10×), and performances are as good as with perfectly called genotypes at a sequencing depth of 2×. We show the reliability of error correction in scenarios with simulated errors and ancient data, and correct for introgression in known scenarios to estimate the admixture rates. Copyright © 2018 Soraggi et al.

Secondary Analysis of Qualitative Data.

ERIC Educational Resources Information Center

Turner, Paul D.

The reanalysis of data to answer the original research question with better statistical techniques or to answer new questions with old data is not uncommon in quantitative studies. Meta analysis and research syntheses have increased with the increase in research using similar statistical analyses, refinements of analytical techniques, and the…

Computer program uses Monte Carlo techniques for statistical system performance analysis

NASA Technical Reports Server (NTRS)

Wohl, D. P.

1967-01-01

Computer program with Monte Carlo sampling techniques determines the effect of a component part of a unit upon the overall system performance. It utilizes the full statistics of the disturbances and misalignments of each component to provide unbiased results through simulated random sampling.

How much to trust the senses: Likelihood learning

PubMed Central

Sato, Yoshiyuki; Kording, Konrad P.

2014-01-01

Our brain often needs to estimate unknown variables from imperfect information. Our knowledge about the statistical distributions of quantities in our environment (called priors) and currently available information from sensory inputs (called likelihood) are the basis of all Bayesian models of perception and action. While we know that priors are learned, most studies of prior-likelihood integration simply assume that subjects know about the likelihood. However, as the quality of sensory inputs change over time, we also need to learn about new likelihoods. Here, we show that human subjects readily learn the distribution of visual cues (likelihood function) in a way that can be predicted by models of statistically optimal learning. Using a likelihood that depended on color context, we found that a learned likelihood generalized to new priors. Thus, we conclude that subjects learn about likelihood. PMID:25398975

Reanalysis of Tyrannosaurus rex Mass Spectra

PubMed Central

Bern, Marshall; Phinney, Brett S.; Goldberg, David

2009-01-01

Asara et al. reported the detection of collagen peptides in a 68-million-year-old T. rex bone by shotgun proteomics. This finding has been called into question as a possible statistical artifact. We reanalyze Asara et al.'s tandem mass spectra using a different search engine and different statistical tools. Our reanalysis shows a sample containing common laboratory contaminants, soil bacteria, and bird-like hemoglobin and collagen. PMID:19603827

Spatial Statistical Models and Optimal Survey Design for Rapid Geophysical characterization of UXO Sites

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

G. Ostrouchov; W.E.Doll; D.A.Wolf

2003-07-01

Unexploded ordnance(UXO)surveys encompass large areas, and the cost of surveying these areas can be high. Enactment of earlier protocols for sampling UXO sites have shown the shortcomings of these procedures and led to a call for development of scientifically defensible statistical procedures for survey design and analysis. This project is one of three funded by SERDP to address this need.

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

Gilbert, Richard O.

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Somemore » statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.« less

Influence of atmospheric properties on detection of wood-warbler nocturnal flight calls

NASA Astrophysics Data System (ADS)

Horton, Kyle G.; Stepanian, Phillip M.; Wainwright, Charlotte E.; Tegeler, Amy K.

2015-10-01

Avian migration monitoring can take on many forms; however, monitoring active nocturnal migration of land birds is limited to a few techniques. Avian nocturnal flight calls are currently the only method for describing migrant composition at the species level. However, as this method develops, more information is needed to understand the sources of variation in call detection. Additionally, few studies examine how detection probabilities differ under varying atmospheric conditions. We use nocturnal flight call recordings from captive individuals to explore the dependence of flight call detection on atmospheric temperature and humidity. Height or distance from origin had the largest influence on call detection, while temperature and humidity also influenced detectability at higher altitudes. Because flight call detection varies with both atmospheric conditions and flight height, improved monitoring across time and space will require correction for these factors to generate standardized metrics of songbird migration.

Directional frequency and recording (DIFAR) sensors in seafloor recorders to locate calling bowhead whales during their fall migration.

PubMed

Greene, Charles R; McLennan, Miles Wm; Norman, Robert G; McDonald, Trent L; Jakubczak, Ray S; Richardson, W John

2004-08-01

Bowhead whales, Balaena mysticetus, migrate west during fall approximately 10-75 km off the north coast of Alaska, passing the petroleum developments around Prudhoe Bay. Oil production operations on an artificial island 5 km offshore create sounds heard by some whales. As part of an effort to assess whether migrating whales deflect farther offshore at times with high industrial noise, an acoustical approach was selected for localizing calling whales. The technique incorporated DIFAR (directional frequency and recording) sonobuoy techniques. An array of 11 DASARs (directional autonomous seafloor acoustic recorders) was built and installed with unit-to-unit separation of 5 km. When two or more DASARs detected the same call, the whale location was determined from the bearing intersections. This article describes the acoustic methods used to determine the locations of the calling bowhead whales and shows the types and precision of the data acquired. Calibration transmissions at GPS-measured times and locations provided measures of the individual DASAR clock drift and directional orientation. The standard error of the bearing measurements at distances of 3-4 km was approximately 1.35 degrees after corrections for gain imbalance in the two directional sensors. During 23 days in 2002, 10,587 bowhead calls were detected and 8383 were localized.

Variable horizon in a peridynamic medium

DOE PAGES

Silling, Stewart A.; Littlewood, David J.; Seleson, Pablo

2015-12-10

Here, a notion of material homogeneity is proposed for peridynamic bodies with variable horizon but constant bulk properties. A relation is derived that scales the force state according to the position-dependent horizon while keeping the bulk properties unchanged. Using this scaling relation, if the horizon depends on position, artifacts called ghost forces may arise in a body under a homogeneous deformation. These artifacts depend on the second derivative of the horizon and can be reduced by employing a modified equilibrium equation using a new quantity called the partial stress. Bodies with piecewise constant horizon can be modeled without ghost forcesmore » by using a simpler technique called a splice. As a limiting case of zero horizon, both the partial stress and splice techniques can be used to achieve local-nonlocal coupling. Computational examples, including dynamic fracture in a one-dimensional model with local-nonlocal coupling, illustrate the methods.« less

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

Statistical moments in superposition models and strongly intensive measures

NASA Astrophysics Data System (ADS)

Broniowski, Wojciech; Olszewski, Adam

2017-06-01

First, we present a concise glossary of formulas for composition of standard, cumulant, factorial, and factorial cumulant moments in superposition (compound) models, where final particles are created via independent emission from a collection of sources. Explicit mathematical formulas for the composed moments are given to all orders. We discuss the composition laws for various types of moments via the generating-function methods and list the formulas for the unfolding of the unwanted fluctuations. Second, the technique is applied to the difference of the scaled multiplicities of two particle types. This allows for a systematic derivation and a simple algebraic interpretation of the so-called strongly intensive fluctuation measures. With the help of the formalism we obtain several new strongly intensive measures involving higher-rank moments. The reviewed as well as the new results may be useful in investigations of mechanisms of particle production and event-by-event fluctuations in high-energy nuclear and hadronic collisions, and in particular in the search for signatures of the QCD phase transition at a finite baryon density.

Food irradiation dosimetry by opti-chromic technique

NASA Astrophysics Data System (ADS)

Zhan-Jun, Liu; Radak, B. B.; McLaughlin, W. L.

The measurement of gamma-radiation quantities, e.g., absorbed dose in materials such as water, plastics, foodstuffs, is a convenient means of quality assurance in radiation processing. A new dosimetry system, called the "Opti-Chromic" dosimeter, is commercially available in large batches for use as a routine measurement system in the absorbed dose range 10 to 2x10 4 Gy. This dose range covers most food irradiation applications. A statistical evaluation was made of the reproducibility of this dosimeter for measuring doses appropriate for the disinfestation and shelf-life extension of many foods, namely 10 to 2x10 3 Gy. In addition, the small dosimeters were used to map absorbed dose distributions in boxes of foods having four different bulk densities (grapefruit, lemons, peanuts, and wheat bran). It is demonstrated that the dosimeters are rugged and stable enough to be used over a wide temperature and humidity range, and, in fact, can be placed in such environments as the inside of citrus fruits without adverse effects on their ability to give satisfactory dose assessment.

Changes in objective acoustic measurements and subjective voice complaints in call center customer-service advisors during one working day.

PubMed

Lehto, Laura; Laaksonen, Laura; Vilkman, Erkki; Alku, Paavo

2008-03-01

The aim of this study was to investigate how different acoustic parameters, extracted both from speech pressure waveforms and glottal flows, can be used in measuring vocal loading in modern working environments and how these parameters reflect the possible changes in the vocal function during a working day. In addition, correlations between objective acoustic parameters and subjective voice symptoms were addressed. The subjects were 24 female and 8 male customer-service advisors, who mainly use telephone during their working hours. Speech samples were recorded from continuous speech four times during a working day and voice symptom questionnaires were completed simultaneously. Among the various objective parameters, only F0 resulted in a statistically significant increase for both genders. No correlations between the changes in objective and subjective parameters appeared. However, the results encourage researchers within the field of occupational voice use to apply versatile measurement techniques in studying occupational voice loading.

Measurements in Transitional Boundary Layers Under High Free-Stream Turbulence and Strong Acceleration Conditions

NASA Technical Reports Server (NTRS)

Volino, Ralph J.; Simon, Terrence W.

1995-01-01

Measurements from transitional, heated boundary layers along a concave-curved test wall are presented and discussed. A boundary layer subject to low free-stream turbulence intensity (FSTI), which contains stationary streamwise (Gortler) vortices, is documented. The low FSTI measurements are followed by measurements in boundary layers subject to high (initially 8%) free-stream turbulence intensity and moderate to strong streamwise acceleration. Conditions were chosen to simulate those present on the downstream half of the pressure side of a gas turbine airfoil. Mean flow characteristics as well as turbulence statistics, including the turbulent shear stress, turbulent heat flux, and turbulent Prandtl number, are documented. A technique called "octant analysis" is introduced and applied to several cases from the literature as well as to data from the present study. Spectral analysis was applied to describe the effects of turbulence scales of different sizes during transition. To the authors'knowledge, this is the first detailed documentation of boundary layer transition under such high free-stream turbulence conditions.

Consistent Partial Least Squares Path Modeling via Regularization

PubMed Central

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present. PMID:29515491

On correct evaluation techniques of brightness enhancement effect measurement data

NASA Astrophysics Data System (ADS)

Kukačka, Leoš; Dupuis, Pascal; Motomura, Hideki; Rozkovec, Jiří; Kolář, Milan; Zissis, Georges; Jinno, Masafumi

2017-11-01

This paper aims to establish confidence intervals of the quantification of brightness enhancement effects resulting from the use of pulsing bright light. It is found that the methods used so far may yield significant bias in the published results, overestimating or underestimating the enhancement effect. The authors propose to use a linear algebra method called the total least squares. Upon an example dataset, it is shown that this method does not yield biased results. The statistical significance of the results is also computed. It is concluded over an observation set that the currently used linear algebra methods present many patterns of noise sensitivity. Changing algorithm details leads to inconsistent results. It is thus recommended to use the method with the lowest noise sensitivity. Moreover, it is shown that this method also permits one to obtain an estimate of the confidence interval. This paper neither aims to publish results about a particular experiment nor to draw any particular conclusion about existence or nonexistence of the brightness enhancement effect.

Improved Regolith-Landform and Geological Mapping using AIRSAR Data as an Aid to Mineral Exploration in the North-Eastern Goldfields Region, Western Australia

NASA Technical Reports Server (NTRS)

Tapley, Ian J.

1996-01-01

The distinctive contribution of AIRSAR data in characterizing the regolith-landforms in a relatively vegetation free environment are discussed. AIRSAR frame processed data were initially MAF-cleaned to enhance the signal content of the data before geocoding to AMG coordinates. Colors in a three frequency single polarization combination image C-, L- P- bands, and in an enhancement of pedestal height, relate directly to the scale of surface roughness of the various regolith units Examination of the AIRSAR enhancements reveals that in mafic terrain, and to a lesser extent, in felsic terrain, AIRSAR data provides discrimination between the principle geomorphic regimes, relict, erosional and depositional. A multivariate statistical technique called an all-possible subsets calculation was used to examine the degree of polarimetric separation between selected regolith-landforms for all combinations of the nine band AIRSAR radar. An unanticipated aspect of the research was the identification on the AIRSAR imagery of previously unmapped structural features.

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

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

Ahn, Tae-Hyuk; Chai, Juanjuan; Pan, Chongle

Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis. Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic readsmore » to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. In conclusion, the algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains. Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.« less

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

DOE PAGES

Ahn, Tae-Hyuk; Chai, Juanjuan; Pan, Chongle

2014-09-29

Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis. Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic readsmore » to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. In conclusion, the algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains. Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.« less

DrImpute: imputing dropout events in single cell RNA sequencing data.

PubMed

Gong, Wuming; Kwak, Il-Youp; Pota, Pruthvi; Koyano-Nakagawa, Naoko; Garry, Daniel J

2018-06-08

The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological noise. Because of the low number of RNA transcriptomes and the stochastic nature of the gene expression pattern, there is a high chance of missing nonzero entries as zero, which are called dropout events. We develop DrImpute to impute dropout events in scRNA-seq data. We show that DrImpute has significantly better performance on the separation of the dropout zeros from true zeros than existing imputation algorithms. We also demonstrate that DrImpute can significantly improve the performance of existing tools for clustering, visualization and lineage reconstruction of nine published scRNA-seq datasets. DrImpute can serve as a very useful addition to the currently existing statistical tools for single cell RNA-seq analysis. DrImpute is implemented in R and is available at https://github.com/gongx030/DrImpute .

Statistical reconstruction for cosmic ray muon tomography.

PubMed

Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J

2007-08-01

Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.

Technique for estimation of streamflow statistics in mineral areas of interest in Afghanistan

USGS Publications Warehouse

Olson, Scott A.; Mack, Thomas J.

2011-01-01

A technique for estimating streamflow statistics at ungaged stream sites in areas of mineral interest in Afghanistan using drainage-area-ratio relations of historical streamflow data was developed and is documented in this report. The technique can be used to estimate the following streamflow statistics at ungaged sites: (1) 7-day low flow with a 10-year recurrence interval, (2) 7-day low flow with a 2-year recurrence interval, (3) daily mean streamflow exceeded 90 percent of the time, (4) daily mean streamflow exceeded 80 percent of the time, (5) mean monthly streamflow for each month of the year, (6) mean annual streamflow, and (7) minimum monthly streamflow for each month of the year. Because they are based on limited historical data, the estimates of streamflow statistics at ungaged sites are considered preliminary.

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from homogeneous groundwaters in the Great Artesian Basin, Australia

NASA Astrophysics Data System (ADS)

O'Shea, Bethany; Jankowski, Jerzy

2006-12-01

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright

Establishing Benchmarks for Outcome Indicators: A Statistical Approach to Developing Performance Standards.

ERIC Educational Resources Information Center

Henry, Gary T.; And Others

1992-01-01

A statistical technique is presented for developing performance standards based on benchmark groups. The benchmark groups are selected using a multivariate technique that relies on a squared Euclidean distance method. For each observation unit (a school district in the example), a unique comparison group is selected. (SLD)

Antismoking television advertising and socioeconomic variations in calls to Quitline.

PubMed

Siahpush, Mohammad; Wakefield, Melanie; Spittal, Matt; Durkin, Sarah

2007-04-01

To assess the socioeconomic variations in call rates to the Quitline (Victoria, Australia) and in the impact of anti-tobacco television advertising on call rates. The outcome measure was the number of calls to the Quitline in Victoria for each week for each socioeconomic group for the period January 2001 to March 2004. Socioeconomic status (SES) was derived from the caller's postcode using the Index of Socioeconomic Disadvantage provided by the Australian Bureau of Statistics. The exposure measure was weekly Target Audience Rating Points (TARPs, a standard measure of television advertising weight) for anti-tobacco advertising broadcast in Victoria over the same period. Negative binomial regression was used to examine the interaction of SES and TARPs in their effect on the number of Quitline calls. SES and call rates were positively associated. Adjusted call rate was 57% (95% CI 45% to 69%) higher in the highest than the lowest SES quintile. SES differences in call rates were stable over time. In the study period, the effect of the presence or increasing levels of antismoking TARPs on call rates did not vary across categories of SES. In the study period, different SES groups had a similar level of responsiveness to antismoking television advertisements, at least as measured by the rate of calls to the Quitline. However, the present media campaigns are not likely to diminish SES differences in call rates, and more needs to be done to encourage disadvantaged groups to call the Quitline.

Antismoking television advertising and socioeconomic variations in calls to Quitline

PubMed Central

Siahpush, Mohammad; Wakefield, Melanie; Spittal, Matt; Durkin, Sarah

2007-01-01

Objective To assess the socioeconomic variations in call rates to the Quitline (Victoria, Australia) and in the impact of anti‐tobacco television advertising on call rates. Design The outcome measure was the number of calls to the Quitline in Victoria for each week for each socioeconomic group for the period January 2001 to March 2004. Socioeconomic status (SES) was derived from the caller's postcode using the Index of Socioeconomic Disadvantage provided by the Australian Bureau of Statistics. The exposure measure was weekly Target Audience Rating Points (TARPs, a standard measure of television advertising weight) for anti‐tobacco advertising broadcast in Victoria over the same period. Negative binomial regression was used to examine the interaction of SES and TARPs in their effect on the number of Quitline calls. Results SES and call rates were positively associated. Adjusted call rate was 57% (95% CI 45% to 69%) higher in the highest than the lowest SES quintile. SES differences in call rates were stable over time. In the study period, the effect of the presence or increasing levels of antismoking TARPs on call rates did not vary across categories of SES. Conclusions In the study period, different SES groups had a similar level of responsiveness to antismoking television advertisements, at least as measured by the rate of calls to the Quitline. However, the present media campaigns are not likely to diminish SES differences in call rates, and more needs to be done to encourage disadvantaged groups to call the Quitline. PMID:17372288

Uncovering Pompeii: Examining Evidence.

ERIC Educational Resources Information Center

Yell, Michael M.

2001-01-01

Presents a lesson plan on Pompeii (Italy) for middle school students that utilizes a teaching technique called interactive presentation. Describes the technique's five phases: (1) discrepant event inquiry; (2) discussion/presentation; (3) cooperative learning activity; (4) writing for understanding activity; and (5) whole-class discussion and…

Alarm Fatigue vs User Expectations Regarding Context-Aware Alarm Handling in Hospital Environments Using CallMeSmart.

PubMed

Solvoll, Terje; Arntsen, Harald; Hartvigsen, Gunnar

2017-01-01

Surveys and research show that mobile communication systems in hospital settings are old and cause frequent interruptions. In the quest to remedy this, an Android based communication system called CallMeSmart tries to encapsulate most of the frequent communication into one hand held device focusing on reducing interruptions and at the same time make the workday easier for healthcare workers. The objective of CallMeSmart is to use context-awareness techniques to automatically monitor the availability of physicians' and nurses', and use this information to prevent or route phone calls, text messages, pages and alarms that would otherwise compromise patient care. In this paper, we present the results from interviewing nurses on alarm fatigue and their expectations regarding context-aware alarm handling using CallMeSmart.

Experimental Mathematics and Computational Statistics

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

Bailey, David H.; Borwein, Jonathan M.

2009-04-30

The field of statistics has long been noted for techniques to detect patterns and regularities in numerical data. In this article we explore connections between statistics and the emerging field of 'experimental mathematics'. These includes both applications of experimental mathematics in statistics, as well as statistical methods applied to computational mathematics.

Engaging with the Art & Science of Statistics

ERIC Educational Resources Information Center

Peters, Susan A.

2010-01-01

How can statistics clearly be mathematical and yet distinct from mathematics? The answer lies in the reality that statistics is both an art and a science, and both aspects are important for teaching and learning statistics. Statistics is a mathematical science in that it applies mathematical theories and techniques. Mathematics provides the…

Using telephony data to facilitate discovery of clinical workflows.

PubMed

Rucker, Donald W

2017-04-19

Discovery of clinical workflows to target for redesign using methods such as Lean and Six Sigma is difficult. VoIP telephone call pattern analysis may complement direct observation and EMR-based tools in understanding clinical workflows at the enterprise level by allowing visualization of institutional telecommunications activity. To build an analytic framework mapping repetitive and high-volume telephone call patterns in a large medical center to their associated clinical units using an enterprise unified communications server log file and to support visualization of specific call patterns using graphical networks. Consecutive call detail records from the medical center's unified communications server were parsed to cross-correlate telephone call patterns and map associated phone numbers to a cost center dictionary. Hashed data structures were built to allow construction of edge and node files representing high volume call patterns for display with an open source graph network tool. Summary statistics for an analysis of exactly one week's call detail records at a large academic medical center showed that 912,386 calls were placed with a total duration of 23,186 hours. Approximately half of all calling called number pairs had an average call duration under 60 seconds and of these the average call duration was 27 seconds. Cross-correlation of phone calls identified by clinical cost center can be used to generate graphical displays of clinical enterprise communications. Many calls are short. The compact data transfers within short calls may serve as automation or re-design targets. The large absolute amount of time medical center employees were engaged in VoIP telecommunications suggests that analysis of telephone call patterns may offer additional insights into core clinical workflows.

A Multidisciplinary Approach for Teaching Statistics and Probability

ERIC Educational Resources Information Center

Rao, C. Radhakrishna

1971-01-01

The author presents a syllabus for an introductory (first year after high school) course in statistics and probability and some methods of teaching statistical techniques. The description comes basically from the procedures used at the Indian Statistical Institute, Calcutta. (JG)

[Non-medical applications for brain MRI: Ethical considerations].

PubMed

Sarrazin, S; Fagot-Largeault, A; Leboyer, M; Houenou, J

2015-04-01

The recent neuroimaging techniques offer the possibility to better understand complex cognitive processes that are involved in mental disorders and thus have become cornerstone tools for research in psychiatry. The performances of functional magnetic resonance imaging are not limited to medical research and are used in non-medical fields. These recent applications represent new challenges for bioethics. In this article we aim at discussing the new ethical issues raised by the applications of the latest neuroimaging technologies to non-medical fields. We included a selection of peer-reviewed English medical articles after a search on NCBI Pubmed database and Google scholar from 2000 to 2013. We screened bibliographical tables for supplementary references. Websites of governmental French institutions implicated in ethical questions were also screened for governmental reports. Findings of brain areas supporting emotional responses and regulation have been used for marketing research, also called neuromarketing. The discovery of different brain activation patterns in antisocial disorder has led to changes in forensic psychiatry with the use of imaging techniques with unproven validity. Automated classification algorithms and multivariate statistical analyses of brain images have been applied to brain-reading techniques, aiming at predicting unconscious neural processes in humans. We finally report the current position of the French legislation recently revised and discuss the technical limits of such techniques. In the near future, brain imaging could find clinical applications in psychiatry as diagnostic or predictive tools. However, the latest advances in brain imaging are also used in non-scientific fields raising key ethical questions. Involvement of neuroscientists, psychiatrists, physicians but also of citizens in neuroethics discussions is crucial to challenge the risk of unregulated uses of brain imaging. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Integrating Statistical and Expert Knowledge to Develop Phenoregions for the Continental United States

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Biondi, F.; Bradford, J. B.; Foster, J. R.; Betancourt, J. L.; Foster, J. R.; Biondi, F.; Bradford, J. B.; Henebry, G. M.; Post, E.; Koenig, W.; Hoffman, F. M.; de Beurs, K.; Hoffman, F. M.; Kumar, J.; Hargrove, W. W.; Norman, S. P.; Brooks, B. G.

2016-12-01

Vegetated ecosystems exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and weather disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) every eight days at 250 m resolution for the period 2000-2015 to develop phenological signatures of emergent ecological regimes called phenoregions. We employed a "Big Data" classification approach on a supercomputer, specifically applying an unsupervised data mining technique, to this large collection of NDVI measurements to develop annual maps of phenoregions. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency of occurrence. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. We will present the phenoregions methodology and resulting maps for the CONUS, describe the "label-stealing" technique for ascribing biome characteristics to phenoregions, and introduce a new polar plotting scheme for processing NDVI data by localized seasonality.

Improving Service Delivery in a County Health Department WIC Clinic: An Application of Statistical Process Control Techniques

PubMed Central

Boe, Debra Thingstad; Parsons, Helen

2009-01-01

Local public health agencies are challenged to continually improve service delivery, yet they frequently operate with constrained resources. Quality improvement methods and techniques such as statistical process control are commonly used in other industries, and they have recently been proposed as a means of improving service delivery and performance in public health settings. We analyzed a quality improvement project undertaken at a local Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) clinic to reduce waiting times and improve client satisfaction with a walk-in nutrition education service. We used statistical process control techniques to evaluate initial process performance, implement an intervention, and assess process improvements. We found that implementation of these techniques significantly reduced waiting time and improved clients' satisfaction with the WIC service. PMID:19608964

Cockpit Resource Management (CRM) for FAR Parts 91 and 135 operators

NASA Technical Reports Server (NTRS)

Schwartz, Douglas

1987-01-01

The why, what, and how of CRM at Flight Safety International (FSI)--that is, the philosophy behind the program, the content of the program, and some insight regarding how it delivers that to the pilot is presented. A few of the concepts that are part of the program are discussed. This includes a view of statistics called the Safety Window, the concept of situational awareness, and an approach to training that we called the Cockpit Management Concept (CMC).

78 FR 70957 - 60-Day Notice of Proposed Information Collection: HUD-Owned Real Estate Good Neighbor Next Door...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-27

... calling the toll-free Federal Relay Service at (800) 877-8339. FOR FURTHER INFORMATION CONTACT: Ivery W... number through TTY by calling the toll-free Federal Relay Service at (800) 877-8339. Copies of available... automated collection techniques or other forms of information technology, e.g., permitting electronic...

78 FR 67384 - 60-Day Notice of Proposed Information Collection: FHA-Insured Mortgage Loan Servicing Involving...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-12

... hearing or speech impairments may access this number through TTY by calling the toll-free Federal Relay... calling the toll-free Federal Relay Service at (800) 877-8339. Copies of available documents submitted to... techniques or other forms of information technology, e.g., permitting electronic submission of responses. HUD...

78 FR 75364 - 60-Day Notice of Proposed Information Collection: Application for FHA Insured Mortgages

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-11

... through TTY by calling the toll-free Federal Relay Service at (800) 877-8339. FOR FURTHER INFORMATION... through TTY by calling the toll-free Federal Relay Service at (800) 877-8339. Copies of available... techniques or other forms of information technology, e.g., permitting electronic submission of responses. HUD...

Encourage Students to Read through the Use of Data Visualization

ERIC Educational Resources Information Center

Bandeen, Heather M.; Sawin, Jason E.

2012-01-01

Instructors are always looking for new ways to engage students in reading assignments. The authors present a few techniques that rely on a web-based data visualization tool called Wordle (wordle.net). Wordle creates word frequency representations called word clouds. The larger a word appears within a cloud, the more frequently it occurs within a…

Statistical Techniques to Analyze Pesticide Data Program Food Residue Observations.

PubMed

Szarka, Arpad Z; Hayworth, Carol G; Ramanarayanan, Tharacad S; Joseph, Robert S I

2018-06-26

The U.S. EPA conducts dietary-risk assessments to ensure that levels of pesticides on food in the U.S. food supply are safe. Often these assessments utilize conservative residue estimates, maximum residue levels (MRLs), and a high-end estimate derived from registrant-generated field-trial data sets. A more realistic estimate of consumers' pesticide exposure from food may be obtained by utilizing residues from food-monitoring programs, such as the Pesticide Data Program (PDP) of the U.S. Department of Agriculture. A substantial portion of food-residue concentrations in PDP monitoring programs are below the limits of detection (left-censored), which makes the comparison of regulatory-field-trial and PDP residue levels difficult. In this paper, we present a novel adaption of established statistical techniques, the Kaplan-Meier estimator (K-M), the robust regression on ordered statistic (ROS), and the maximum-likelihood estimator (MLE), to quantify the pesticide-residue concentrations in the presence of heavily censored data sets. The examined statistical approaches include the most commonly used parametric and nonparametric methods for handling left-censored data that have been used in the fields of medical and environmental sciences. This work presents a case study in which data of thiamethoxam residue on bell pepper generated from registrant field trials were compared with PDP-monitoring residue values. The results from the statistical techniques were evaluated and compared with commonly used simple substitution methods for the determination of summary statistics. It was found that the maximum-likelihood estimator (MLE) is the most appropriate statistical method to analyze this residue data set. Using the MLE technique, the data analyses showed that the median and mean PDP bell pepper residue levels were approximately 19 and 7 times lower, respectively, than the corresponding statistics of the field-trial residues.

Comparison of VRX CT scanners geometries

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Melnyk, Roman; Duckworth, Christopher N.; Russ, Stephan; Jordan, Lawrence M.; Laughter, Joseph S.

2001-06-01

A technique called Variable-Resolution X-ray (VRX) detection greatly increases the spatial resolution in computed tomography (CT) and digital radiography (DR) as the field size decreases. The technique is based on a principle called `projective compression' that allows both the resolution element and the sampling distance of a CT detector to scale with the subject or field size. For very large (40 - 50 cm) field sizes, resolution exceeding 2 cy/mm is possible and for very small fields, microscopy is attainable with resolution exceeding 100 cy/mm. This paper compares the benefits obtainable with two different VRX detector geometries: the single-arm geometry and the dual-arm geometry. The analysis is based on Monte Carlo simulations and direct calculations. The results of this study indicate that the dual-arm system appears to have more advantages than the single-arm technique.

Spectrum transformation for divergent iterations

NASA Technical Reports Server (NTRS)

Gupta, Murli M.

1991-01-01

Certain spectrum transformation techniques are described that can be used to transform a diverging iteration into a converging one. Two techniques are considered called spectrum scaling and spectrum enveloping and how to obtain the optimum values of the transformation parameters is discussed. Numerical examples are given to show how this technique can be used to transform diverging iterations into converging ones; this technique can also be used to accelerate the convergence of otherwise convergent iterations.

Optimization of Online Searching by Pre-Recording the Search Statements: A Technique for the HP-2645A Terminal.

ERIC Educational Resources Information Center

Oberhauser, O. C.; Stebegg, K.

1982-01-01

Describes the terminal's capabilities, ways to store and call up lines of statements, cassette tapes needed during searches, and master tape's use for login storage. Advantages of the technique and two sources are listed. (RBF)

Development of a mix design process for cold-in-place rehabilitation using foamed asphalt.

DOT National Transportation Integrated Search

2003-12-01

This study evaluates one of the recycling techniques used to rehabilitate pavement, called Cold In-Place Recycling (CIR). CIR is one of the fastest growing road rehabilitation techniques because it is quick and cost-effective. The document reports on...

Curve fitting and modeling with splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Fitting multidimensional splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

This report demonstrates the successful application of statistical variable selection techniques to fit splines. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs using the B-spline basis were developed, and the one for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Classification by diagnosing all absorption features (CDAF) for the most abundant minerals in airborne hyperspectral images

NASA Astrophysics Data System (ADS)

Mobasheri, Mohammad Reza; Ghamary-Asl, Mohsen

2011-12-01

Imaging through hyperspectral technology is a powerful tool that can be used to spectrally identify and spatially map materials based on their specific absorption characteristics in electromagnetic spectrum. A robust method called Tetracorder has shown its effectiveness at material identification and mapping, using a set of algorithms within an expert system decision-making framework. In this study, using some stages of Tetracorder, a technique called classification by diagnosing all absorption features (CDAF) is introduced. This technique enables one to assign a class to the most abundant mineral in each pixel with high accuracy. The technique is based on the derivation of information from reflectance spectra of the image. This can be done through extraction of spectral absorption features of any minerals from their respected laboratory-measured reflectance spectra, and comparing it with those extracted from the pixels in the image. The CDAF technique has been executed on the AVIRIS image where the results show an overall accuracy of better than 96%.

Two-state Markov-chain Poisson nature of individual cellphone call statistics

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Xie, Wen-Jie; Li, Ming-Xia; Zhou, Wei-Xing; Sornette, Didier

2016-07-01

Unfolding the burst patterns in human activities and social interactions is a very important issue especially for understanding the spreading of disease and information and the formation of groups and organizations. Here, we conduct an in-depth study of the temporal patterns of cellphone conversation activities of 73 339 anonymous cellphone users, whose inter-call durations are Weibull distributed. We find that the individual call events exhibit a pattern of bursts, that high activity periods are alternated with low activity periods. In both periods, the number of calls are exponentially distributed for individuals, but power-law distributed for the population. Together with the exponential distributions of inter-call durations within bursts and of the intervals between consecutive bursts, we demonstrate that the individual call activities are driven by two independent Poisson processes, which can be combined within a minimal model in terms of a two-state first-order Markov chain, giving significant fits for nearly half of the individuals. By measuring directly the distributions of call rates across the population, which exhibit power-law tails, we purport the existence of power-law distributions, via the ‘superposition of distributions’ mechanism. Our findings shed light on the origins of bursty patterns in other human activities.

Statistical Tests of Reliability of NDE

NASA Technical Reports Server (NTRS)

Baaklini, George Y.; Klima, Stanley J.; Roth, Don J.; Kiser, James D.

1987-01-01

Capabilities of advanced material-testing techniques analyzed. Collection of four reports illustrates statistical method for characterizing flaw-detecting capabilities of sophisticated nondestructive evaluation (NDE). Method used to determine reliability of several state-of-the-art NDE techniques for detecting failure-causing flaws in advanced ceramic materials considered for use in automobiles, airplanes, and space vehicles.

Statistical Techniques for Efficient Indexing and Retrieval of Document Images

ERIC Educational Resources Information Center

Bhardwaj, Anurag

2010-01-01

We have developed statistical techniques to improve the performance of document image search systems where the intermediate step of OCR based transcription is not used. Previous research in this area has largely focused on challenges pertaining to generation of small lexicons for processing handwritten documents and enhancement of poor quality…

Are conventional statistical techniques exhaustive for defining metal background concentrations in harbour sediments? A case study: The Coastal Area of Bari (Southeast Italy).

PubMed

Mali, Matilda; Dell'Anna, Maria Michela; Mastrorilli, Piero; Damiani, Leonardo; Ungaro, Nicola; Belviso, Claudia; Fiore, Saverio

2015-11-01

Sediment contamination by metals poses significant risks to coastal ecosystems and is considered to be problematic for dredging operations. The determination of the background values of metal and metalloid distribution based on site-specific variability is fundamental in assessing pollution levels in harbour sediments. The novelty of the present work consists of addressing the scope and limitation of analysing port sediments through the use of conventional statistical techniques (such as: linear regression analysis, construction of cumulative frequency curves and the iterative 2σ technique), that are commonly employed for assessing Regional Geochemical Background (RGB) values in coastal sediments. This study ascertained that although the tout court use of such techniques in determining the RGB values in harbour sediments seems appropriate (the chemical-physical parameters of port sediments fit well with statistical equations), it should nevertheless be avoided because it may be misleading and can mask key aspects of the study area that can only be revealed by further investigations, such as mineralogical and multivariate statistical analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

NASA Technical Reports Server (NTRS)

Zimmerman, G. A.; Olsen, E. T.

1992-01-01

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Linguistic Diversity and Traffic Accidents: Lessons from Statistical Studies of Cultural Traits

PubMed Central

Roberts, Seán; Winters, James

2013-01-01

The recent proliferation of digital databases of cultural and linguistic data, together with new statistical techniques becoming available has lead to a rise in so-called nomothetic studies [1]–[8]. These seek relationships between demographic variables and cultural traits from large, cross-cultural datasets. The insights from these studies are important for understanding how cultural traits evolve. While these studies are fascinating and are good at generating testable hypotheses, they may underestimate the probability of finding spurious correlations between cultural traits. Here we show that this kind of approach can find links between such unlikely cultural traits as traffic accidents, levels of extra-martial sex, political collectivism and linguistic diversity. This suggests that spurious correlations, due to historical descent, geographic diffusion or increased noise-to-signal ratios in large datasets, are much more likely than some studies admit. We suggest some criteria for the evaluation of nomothetic studies and some practical solutions to the problems. Since some of these studies are receiving media attention without a widespread understanding of the complexities of the issue, there is a risk that poorly controlled studies could affect policy. We hope to contribute towards a general skepticism for correlational studies by demonstrating the ease of finding apparently rigorous correlations between cultural traits. Despite this, we see well-controlled nomothetic studies as useful tools for the development of theories. PMID:23967132

Linguistic diversity and traffic accidents: lessons from statistical studies of cultural traits.

PubMed

Roberts, Seán; Winters, James

2013-01-01

The recent proliferation of digital databases of cultural and linguistic data, together with new statistical techniques becoming available has lead to a rise in so-called nomothetic studies [1]-[8]. These seek relationships between demographic variables and cultural traits from large, cross-cultural datasets. The insights from these studies are important for understanding how cultural traits evolve. While these studies are fascinating and are good at generating testable hypotheses, they may underestimate the probability of finding spurious correlations between cultural traits. Here we show that this kind of approach can find links between such unlikely cultural traits as traffic accidents, levels of extra-martial sex, political collectivism and linguistic diversity. This suggests that spurious correlations, due to historical descent, geographic diffusion or increased noise-to-signal ratios in large datasets, are much more likely than some studies admit. We suggest some criteria for the evaluation of nomothetic studies and some practical solutions to the problems. Since some of these studies are receiving media attention without a widespread understanding of the complexities of the issue, there is a risk that poorly controlled studies could affect policy. We hope to contribute towards a general skepticism for correlational studies by demonstrating the ease of finding apparently rigorous correlations between cultural traits. Despite this, we see well-controlled nomothetic studies as useful tools for the development of theories.

Meat Quality Assessment by Electronic Nose (Machine Olfaction Technology)

PubMed Central

Ghasemi-Varnamkhasti, Mahdi; Mohtasebi, Seyed Saeid; Siadat, Maryam; Balasubramanian, Sundar

2009-01-01

Over the last twenty years, newly developed chemical sensor systems (so called “electronic noses”) have made odor analyses possible. These systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odors. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odor quality evaluation of food packaging material. This paper describes the applications of these systems for meat quality assessment, where fast detection methods are essential for appropriate product management. The results suggest the possibility of using this new technology in meat handling. PMID:22454572

Personalised news filtering and recommendation system using Chi-square statistics-based K-nearest neighbour (χ2SB-KNN) model

NASA Astrophysics Data System (ADS)

Adeniyi, D. A.; Wei, Z.; Yang, Y.

2017-10-01

Recommendation problem has been extensively studied by researchers in the field of data mining, database and information retrieval. This study presents the design and realisation of an automated, personalised news recommendations system based on Chi-square statistics-based K-nearest neighbour (χ2SB-KNN) model. The proposed χ2SB-KNN model has the potential to overcome computational complexity and information overloading problems, reduces runtime and speeds up execution process through the use of critical value of χ2 distribution. The proposed recommendation engine can alleviate scalability challenges through combined online pattern discovery and pattern matching for real-time recommendations. This work also showcases the development of a novel method of feature selection referred to as Data Discretisation-Based feature selection method. This is used for selecting the best features for the proposed χ2SB-KNN algorithm at the preprocessing stage of the classification procedures. The implementation of the proposed χ2SB-KNN model is achieved through the use of a developed in-house Java program on an experimental website called OUC newsreaders' website. Finally, we compared the performance of our system with two baseline methods which are traditional Euclidean distance K-nearest neighbour and Naive Bayesian techniques. The result shows a significant improvement of our method over the baseline methods studied.

Meteorological Development Laboratory Student Career Experience Program

NASA Astrophysics Data System (ADS)

McCalla, C., Sr.

2007-12-01

The National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) provides weather, hydrologic, and climate forecasts and warnings for the protection of life and property and the enhancement of the national economy. The NWS's Meteorological Development Laboratory (MDL) supports this mission by developing meteorological prediction methods. Given this mission, NOAA, NWS, and MDL all have a need to continually recruit talented scientists. One avenue for recruiting such talented scientist is the Student Career Experience Program (SCEP). Through SCEP, MDL offers undergraduate and graduate students majoring in meteorology, computer science, mathematics, oceanography, physics, and statistics the opportunity to alternate full-time paid employment with periods of full-time study. Using SCEP as a recruiting vehicle, MDL has employed students who possess some of the very latest technical skills and knowledge needed to make meaningful contributions to projects within the lab. MDL has recently expanded its use of SCEP and has increased the number of students (sometimes called co- ops) in its program. As a co-op, a student can expect to develop and implement computer based scientific techniques, participate in the development of statistical algorithms, assist in the analysis of meteorological data, and verify forecasts. This presentation will focus on describing recruitment, projects, and the application process related to MDL's SCEP. In addition, this presentation will also briefly explore the career paths of students who successfully completed the program.

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

Recall of past use of mobile phone handsets.

PubMed

Parslow, R C; Hepworth, S J; McKinney, P A

2003-01-01

Previous studies investigating health effects of mobile phones have based their estimation of exposure on self-reported levels of phone use. This UK validation study assesses the accuracy of reported voice calls made from mobile handsets. Data collected by postal questionnaire from 93 volunteers was compared to records obtained prospectively over 6 months from four network operators. Agreement was measured for outgoing calls using the kappa statistic, log-linear modelling, Spearman correlation coefficient and graphical methods. Agreement for number of calls gained moderate classification (kappa = 0.39) with better agreement for duration (kappa = 0.50). Log-linear modelling produced similar results. The Spearman correlation coefficient was 0.48 for number of calls and 0.60 for duration. Graphical agreement methods demonstrated patterns of over-reporting call numbers (by a factor of 1.7) and duration (by a factor of 2.8). These results suggest that self-reported mobile phone use may not fully represent patterns of actual use. This has implications for calculating exposures from questionnaire data.

Dating Tectonic Activity on Mercury’s Large-Scale Lobate-Scarp Thrust Faults

NASA Astrophysics Data System (ADS)

Barlow, Nadine G.; E Banks, Maria

2017-10-01

Mercury’s widespread large-scale lobate-scarp thrust faults reveal that the planet’s tectonic history has been dominated by global contraction, primarily due to cooling of its interior. Constraining the timing and duration of this contraction provides key insight into Mercury’s thermal and geologic evolution. We combine two techniques to enhance the statistical validity of size-frequency distribution crater analyses and constrain timing of the 1) earliest and 2) most recent detectable activity on several of Mercury’s largest lobate-scarp thrust faults. We use the sizes of craters directly transected by or superposed on the edge of the scarp face to define a count area around the scarp, a method we call the Modified Buffered Crater Counting Technique (MBCCT). We developed the MBCCT to avoid the issue of a near-zero scarp width since feature widths are included in area calculations of the commonly used Buffered Crater Counting Technique (BCCT). Since only craters directly intersecting the scarp face edge conclusively show evidence of crosscutting relations, we increase the number of craters in our analysis (and reduce uncertainties) by using the morphologic degradation state (i.e. relative age) of these intersecting craters to classify other similarly degraded craters within the count area (i.e., those with the same relative age) as superposing or transected. The resulting crater counts are divided into two categories: transected craters constrain the earliest possible activity and superposed craters constrain the most recent detectable activity. Absolute ages are computed for each population using the Marchi et al. [2009] model production function. A test of the Blossom lobate scarp indicates the MBCCT gives statistically equivalent results to the BCCT. We find that all scarps in this study crosscut surfaces Tolstojan or older in age (>~3.7 Ga). The most recent detectable activity along lobate-scarp thrust faults ranges from Calorian to Kuiperian (~3.7 Ga to present). Our results complement previous relative-age studies with absolute ages and indicate global contraction continued over the last ~3-4 Gyr. At least some thrust fault activity occurred on Mercury in relatively recent times (<280 Ma).

Detailed statistical contact angle analyses; "slow moving" drops on inclining silicon-oxide surfaces.

PubMed

Schmitt, M; Groß, K; Grub, J; Heib, F

2015-06-01

Contact angle determination by sessile drop technique is essential to characterise surface properties in science and in industry. Different specific angles can be observed on every solid which are correlated with the advancing or the receding of the triple line. Different procedures and definitions for the determination of specific angles exist which are often not comprehensible or reproducible. Therefore one of the most important things in this area is to build standard, reproducible and valid methods for determining advancing/receding contact angles. This contribution introduces novel techniques to analyse dynamic contact angle measurements (sessile drop) in detail which are applicable for axisymmetric and non-axisymmetric drops. Not only the recently presented fit solution by sigmoid function and the independent analysis of the different parameters (inclination, contact angle, velocity of the triple point) but also the dependent analysis will be firstly explained in detail. These approaches lead to contact angle data and different access on specific contact angles which are independent from "user-skills" and subjectivity of the operator. As example the motion behaviour of droplets on flat silicon-oxide surfaces after different surface treatments is dynamically measured by sessile drop technique when inclining the sample plate. The triple points, the inclination angles, the downhill (advancing motion) and the uphill angles (receding motion) obtained by high-precision drop shape analysis are independently and dependently statistically analysed. Due to the small covered distance for the dependent analysis (<0.4mm) and the dominance of counted events with small velocity the measurements are less influenced by motion dynamics and the procedure can be called "slow moving" analysis. The presented procedures as performed are especially sensitive to the range which reaches from the static to the "slow moving" dynamic contact angle determination. They are characterised by small deviations of the computed values. Additional to the detailed introduction of this novel analytical approaches plus fit solution special motion relations for the drop on inclined surfaces and detailed relations about the reactivity of the freshly cleaned silicon wafer surface resulting in acceleration behaviour (reactive de-wetting) are presented. Copyright © 2014 Elsevier Inc. All rights reserved.