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

Apte, A; Veeraraghavan, H; Oh, J

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features andmore » (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.« less

Manx Gaelic: The Manx Gaelic Language in Education in the Isle of Man. Regional Dossiers Series

ERIC Educational Resources Information Center

McArdle, Fiona, Comp.; Teare, Robert, Comp.

2016-01-01

This regional dossier aims at providing a concise description of and basic statistics on minority language education in a specific region of Europe--the Isle of Man. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative…

Sorbian: The Sorbian Language in Education in Germany, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Brezan, Beate, Comp.; Nowak, Meto, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

North Frisian: The North Frisian Language in Education in Germany, 3rd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Walker, Alastair G. H., Comp.

2015-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Swedish: The Swedish Language in Education in Finland, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Østern, Anna-Lena, Comp.; Harju-Luukkainen, Heidi, Comp.

2013-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Ladin: The Ladin Language in Education in Italy, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Verra, Roland, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Galician: The Galician Language in Education in Spain, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Costas, Xosé-Henrique, Comp.; Expósito-Loureiro, Andrea, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Welsh: The Welsh Language in Education in the UK, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Jones, Meirion Prys, Comp.; Jones, Ceinwen, Comp.

2014-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Irish: The Irish Language in Education in the Republic of Ireland, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Ó Murchú, Helen, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Asturian: The Asturian Language in Education in Spain, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

González-Riaño, Xosé Antón, Comp.; Fernández-Costales, Alberto, Comp.

2014-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Statistical-mechanics theory of active mode locking with noise.

PubMed

Gordon, Ariel; Fischer, Baruch

2004-05-01

Actively mode-locked lasers with noise are studied employing statistical mechanics. A mapping of the system to the spherical model (related to the Ising model) of ferromagnets in one dimension that has an exact solution is established. It gives basic features, such as analytical expressions for the correlation function between modes, and the widths and shapes of the pulses [different from the Kuizenga-Siegman expression; IEEE J. Quantum Electron. QE-6, 803 (1970)] and reveals the susceptibility to noise of mode ordering compared with passive mode locking.

Impact of Hearing Aid Technology on Outcomes in Daily Life II: Speech Understanding and Listening Effort.

PubMed

Johnson, Jani A; Xu, Jingjing; Cox, Robyn M

2016-01-01

Modern hearing aid (HA) devices include a collection of acoustic signal-processing features designed to improve listening outcomes in a variety of daily auditory environments. Manufacturers market these features at successive levels of technological sophistication. The features included in costlier premium hearing devices are designed to result in further improvements to daily listening outcomes compared with the features included in basic hearing devices. However, independent research has not substantiated such improvements. This research was designed to explore differences in speech-understanding and listening-effort outcomes for older adults using premium-feature and basic-feature HAs in their daily lives. For this participant-blinded, repeated, crossover trial 45 older adults (mean age 70.3 years) with mild-to-moderate sensorineural hearing loss wore each of four pairs of bilaterally fitted HAs for 1 month. HAs were premium- and basic-feature devices from two major brands. After each 1-month trial, participants' speech-understanding and listening-effort outcomes were evaluated in the laboratory and in daily life. Three types of speech-understanding and listening-effort data were collected: measures of laboratory performance, responses to standardized self-report questionnaires, and participant diary entries about daily communication. The only statistically significant superiority for the premium-feature HAs occurred for listening effort in the loud laboratory condition and was demonstrated for only one of the tested brands. The predominant complaint of older adults with mild-to-moderate hearing impairment is difficulty understanding speech in various settings. The combined results of all the outcome measures used in this research suggest that, when fitted using scientifically based practices, both premium- and basic-feature HAs are capable of providing considerable, but essentially equivalent, improvements to speech understanding and listening effort in daily life for this population. For HA providers to make evidence-based recommendations to their clientele with hearing impairment it is essential that further independent research investigates the relative benefit/deficit of different levels of hearing technology across brands and manufacturers in these and other real-world listening domains.

IT Control Deficiencies That Affect the Financial Reporting of Companies since the Enactment of the Sarbanes Oxley Act

ERIC Educational Resources Information Center

Harper, Roosevelt

2014-01-01

This research study examined the specific categories of IT control deficiencies and their related effects on financial reporting. The approach to this study was considered non-experimental, an approach sometimes called descriptive. Descriptive statistics are used to describe the basic features of the data in a study, providing simple summaries…

Nenets, Khanty and Selkup: The Nenets, Khanty and Selkup Language in Education in the Yamal Region in Russia. Regional Dossiers Series

ERIC Educational Resources Information Center

Laptander, Roza Ivanovna, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

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

Utilization of satellite data for inventorying prairie ponds and lakes

NASA Technical Reports Server (NTRS)

Work, E. A., Jr.; Gilmer, D. S.

1976-01-01

ERTS-1 data were used in mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single near-infrared waveband. On the basis of these results, thematic maps and statistics relating to open surface water were obtained. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

The mzqLibrary – An open source Java library supporting the HUPO‐PSI quantitative proteomics standard

PubMed Central

Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M.; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R.

2015-01-01

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML‐based format, capable of representing data about two‐dimensional features from LC‐MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java‐based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)‐level quantification values from peptide‐level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC‐MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in‐built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq‐lib/. PMID:26037908

The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

PubMed

Qi, Da; Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R

2015-09-01

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting Macroscale Effects Through Nanoscale Features

DTIC Science & Technology

2012-01-01

errors become incorrectly computed by the basic OLS technique. To test for the presence of heteroscedasticity the Breusch - Pagan / Cook-Weisberg test ...is employed with the test statistics distributed as 2 with the degrees of freedom equal to the number of regressors. The Breusch - Pagan / Cook...between shock sensitivity and Sm does not exhibit any heteroscedasticity. The Breusch - Pagan / Cook-Weisberg test provides 2(1)=1.73, which

Asymmetric statistical features of the Chinese domestic and international gold price fluctuation

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhao, Yingchao; Han, Yan

2015-05-01

Analyzing the statistical features of fluctuation is remarkably significant for financial risk identification and measurement. In this study, the asymmetric detrended fluctuation analysis (A-DFA) method was applied to evaluate asymmetric multifractal scaling behaviors in the Shanghai and New York gold markets. Our findings showed that the multifractal features of the Chinese and international gold spot markets were asymmetric. The gold return series persisted longer in an increasing trend than in a decreasing trend. Moreover, the asymmetric degree of multifractals in the Chinese and international gold markets decreased with the increase in fluctuation range. In addition, the empirical analysis using sliding window technology indicated that multifractal asymmetry in the Chinese and international gold markets was characterized by its time-varying feature. However, the Shanghai and international gold markets basically shared a similar asymmetric degree evolution pattern. The American subprime mortgage crisis (2008) and the European debt crisis (2010) enhanced the asymmetric degree of the multifractal features of the Chinese and international gold markets. Furthermore, we also make statistical tests for the results of multifractatity and asymmetry, and discuss the origin of them. Finally, results of the empirical analysis using the threshold autoregressive conditional heteroskedasticity (TARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models exhibited that good news had a more significant effect on the cyclical fluctuation of the gold market than bad news. Moreover, good news exerted a more significant effect on the Chinese gold market than on the international gold market.

Objects and categories: feature statistics and object processing in the ventral stream.

PubMed

Tyler, Lorraine K; Chiu, Shannon; Zhuang, Jie; Randall, Billi; Devereux, Barry J; Wright, Paul; Clarke, Alex; Taylor, Kirsten I

2013-10-01

Recognizing an object involves more than just visual analyses; its meaning must also be decoded. Extensive research has shown that processing the visual properties of objects relies on a hierarchically organized stream in ventral occipitotemporal cortex, with increasingly more complex visual features being coded from posterior to anterior sites culminating in the perirhinal cortex (PRC) in the anteromedial temporal lobe (aMTL). The neurobiological principles of the conceptual analysis of objects remain more controversial. Much research has focused on two neural regions-the fusiform gyrus and aMTL, both of which show semantic category differences, but of different types. fMRI studies show category differentiation in the fusiform gyrus, based on clusters of semantically similar objects, whereas category-specific deficits, specifically for living things, are associated with damage to the aMTL. These category-specific deficits for living things have been attributed to problems in differentiating between highly similar objects, a process that involves the PRC. To determine whether the PRC and the fusiform gyri contribute to different aspects of an object's meaning, with differentiation between confusable objects in the PRC and categorization based on object similarity in the fusiform, we carried out an fMRI study of object processing based on a feature-based model that characterizes the degree of semantic similarity and difference between objects and object categories. Participants saw 388 objects for which feature statistic information was available and named the objects at the basic level while undergoing fMRI scanning. After controlling for the effects of visual information, we found that feature statistics that capture similarity between objects formed category clusters in fusiform gyri, such that objects with many shared features (typical of living things) were associated with activity in the lateral fusiform gyri whereas objects with fewer shared features (typical of nonliving things) were associated with activity in the medial fusiform gyri. Significantly, a feature statistic reflecting differentiation between highly similar objects, enabling object-specific representations, was associated with bilateral PRC activity. These results confirm that the statistical characteristics of conceptual object features are coded in the ventral stream, supporting a conceptual feature-based hierarchy, and integrating disparate findings of category responses in fusiform gyri and category deficits in aMTL into a unifying neurocognitive framework.

Bag-of-features approach for improvement of lung tissue classification in diffuse lung disease

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

Many automated techniques have been proposed to classify diffuse lung disease patterns. Most of the techniques utilize texture analysis approaches with second and higher order statistics, and show successful classification result among various lung tissue patterns. However, the approaches do not work well for the patterns with inhomogeneous texture distribution within a region of interest (ROI), such as reticular and honeycombing patterns, because the statistics can only capture averaged feature over the ROI. In this work, we have introduced the bag-of-features approach to overcome this difficulty. In the approach, texture images are represented as histograms or distributions of a few basic primitives, which are obtained by clustering local image features. The intensity descriptor and the Scale Invariant Feature Transformation (SIFT) descriptor are utilized to extract the local features, which have significant discriminatory power due to their specificity to a particular image class. In contrast, the drawback of the local features is lack of invariance under translation and rotation. We improved the invariance by sampling many local regions so that the distribution of the local features is unchanged. We evaluated the performance of our system in the classification task with 5 image classes (ground glass, reticular, honeycombing, emphysema, and normal) using 1109 ROIs from 211 patients. Our system achieved high classification accuracy of 92.8%, which is superior to that of the conventional system with the gray level co-occurrence matrix (GLCM) feature especially for inhomogeneous texture patterns.

Keywords and Co-Occurrence Patterns in the Voynich Manuscript: An Information-Theoretic Analysis

PubMed Central

Montemurro, Marcelo A.; Zanette, Damián H.

2013-01-01

The Voynich manuscript has remained so far as a mystery for linguists and cryptologists. While the text written on medieval parchment -using an unknown script system- shows basic statistical patterns that bear resemblance to those from real languages, there are features that suggested to some researches that the manuscript was a forgery intended as a hoax. Here we analyse the long-range structure of the manuscript using methods from information theory. We show that the Voynich manuscript presents a complex organization in the distribution of words that is compatible with those found in real language sequences. We are also able to extract some of the most significant semantic word-networks in the text. These results together with some previously known statistical features of the Voynich manuscript, give support to the presence of a genuine message inside the book. PMID:23805215

Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy.

PubMed

Vargas-Rodriguez, Everardo; Guzman-Chavez, Ana Dinora; Baeza-Serrato, Roberto

2018-06-04

In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.

The Impact of Natural Hazards such as Turbulent Wind Gusts on the Wind Energy Conversion Process

NASA Astrophysics Data System (ADS)

Wächter, M.; Hölling, M.; Milan, P.; Morales, A.; Peinke, J.

2012-12-01

Wind turbines operate in the atmospheric boundary layer, where they are exposed to wind gusts and other types of natural hazards. As the response time of wind turbines is typically in the range of seconds, they are affected by the small scale intermittent properties of the turbulent wind. We show evidence that basic features which are known for small-scale homogeneous isotropic turbulence, and in particular the well-known intermittency problem, have an important impact on the wind energy conversion process. Intermittent statistics include high probabilities of extreme events which can be related to wind gusts and other types of natural hazards. As a summarizing result we find that atmospheric turbulence imposes its intermittent features on the complete wind energy conversion process. Intermittent turbulence features are not only present in atmospheric wind, but are also dominant in the loads on the turbine, i.e. rotor torque and thrust, and in the electrical power output signal. We conclude that profound knowledge of turbulent statistics and the application of suitable numerical as well as experimental methods are necessary to grasp these unique features and quantify their effects on all stages of wind energy conversion.

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

PubMed Central

Liu, Yiming; Huang, Nai-Lun; Zeng, Fufu; Lin, Fang-Ying

2014-01-01

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment. PMID:25032231

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.

Quantitative research.

PubMed

Watson, Roger

2015-04-01

This article describes the basic tenets of quantitative research. The concepts of dependent and independent variables are addressed and the concept of measurement and its associated issues, such as error, reliability and validity, are explored. Experiments and surveys – the principal research designs in quantitative research – are described and key features explained. The importance of the double-blind randomised controlled trial is emphasised, alongside the importance of longitudinal surveys, as opposed to cross-sectional surveys. Essential features of data storage are covered, with an emphasis on safe, anonymous storage. Finally, the article explores the analysis of quantitative data, considering what may be analysed and the main uses of statistics in analysis.

Adaptive variable-length coding for efficient compression of spacecraft television data.

NASA Technical Reports Server (NTRS)

Rice, R. F.; Plaunt, J. R.

1971-01-01

An adaptive variable length coding system is presented. Although developed primarily for the proposed Grand Tour missions, many features of this system clearly indicate a much wider applicability. Using sample to sample prediction, the coding system produces output rates within 0.25 bit/picture element (pixel) of the one-dimensional difference entropy for entropy values ranging from 0 to 8 bit/pixel. This is accomplished without the necessity of storing any code words. Performance improvements of 0.5 bit/pixel can be simply achieved by utilizing previous line correlation. A Basic Compressor, using concatenated codes, adapts to rapid changes in source statistics by automatically selecting one of three codes to use for each block of 21 pixels. The system adapts to less frequent, but more dramatic, changes in source statistics by adjusting the mode in which the Basic Compressor operates on a line-to-line basis. Furthermore, the compression system is independent of the quantization requirements of the pulse-code modulation system.

A Set of Handwriting Features for Use in Automated Writer Identification.

PubMed

Miller, John J; Patterson, Robert Bradley; Gantz, Donald T; Saunders, Christopher P; Walch, Mark A; Buscaglia, JoAnn

2017-05-01

A writer's biometric identity can be characterized through the distribution of physical feature measurements ("writer's profile"); a graph-based system that facilitates the quantification of these features is described. To accomplish this quantification, handwriting is segmented into basic graphical forms ("graphemes"), which are "skeletonized" to yield the graphical topology of the handwritten segment. The graph-based matching algorithm compares the graphemes first by their graphical topology and then by their geometric features. Graphs derived from known writers can be compared against graphs extracted from unknown writings. The process is computationally intensive and relies heavily upon statistical pattern recognition algorithms. This article focuses on the quantification of these physical features and the construction of the associated pattern recognition methods for using the features to discriminate among writers. The graph-based system described in this article has been implemented in a highly accurate and approximately language-independent biometric recognition system of writers of cursive documents. © 2017 American Academy of Forensic Sciences.

Analysis of Variance in Statistical Image Processing

NASA Astrophysics Data System (ADS)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Semantic memory: a feature-based analysis and new norms for Italian.

PubMed

Montefinese, Maria; Ambrosini, Ettore; Fairfield, Beth; Mammarella, Nicola

2013-06-01

Semantic norms for properties produced by native speakers are valuable tools for researchers interested in the structure of semantic memory and in category-specific semantic deficits in individuals following brain damage. The aims of this study were threefold. First, we sought to extend existing semantic norms by adopting an empirical approach to category (Exp. 1) and concept (Exp. 2) selection, in order to obtain a more representative set of semantic memory features. Second, we extensively outlined a new set of semantic production norms collected from Italian native speakers for 120 artifactual and natural basic-level concepts, using numerous measures and statistics following a feature-listing task (Exp. 3b). Finally, we aimed to create a new publicly accessible database, since only a few existing databases are publicly available online.

Classification of emotional states from electrocardiogram signals: a non-linear approach based on hurst

PubMed Central

2013-01-01

Background Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals. Methods Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature ‘Hurst’ was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers – Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm. Results Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively. Conclusions The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. PMID:23680041

Statistics at a glance.

PubMed

Ector, Hugo

2010-12-01

I still remember my first book on statistics: "Elementary statistics with applications in medicine and the biological sciences" by Frederick E. Croxton. For me, it has been the start of pursuing understanding statistics in daily life and in medical practice. It was the first volume in a long row of books. In his introduction, Croxton pretends that"nearly everyone involved in any aspect of medicine needs to have some knowledge of statistics". The reality is that for many clinicians, statistics are limited to a "P < 0.05 = ok". I do not blame my colleagues who omit the paragraph on statistical methods. They have never had the opportunity to learn concise and clear descriptions of the key features. I have experienced how some authors can describe difficult methods in a well understandable language. Others fail completely. As a teacher, I tell my students that life is impossible without a basic knowledge of statistics. This feeling has resulted in an annual seminar of 90 minutes. This tutorial is the summary of this seminar. It is a summary and a transcription of the best pages I have detected.

[Prevalence and features of coeliac disease in the Mediterranean area of Spain].

PubMed

Navalón-Ramon, E; Juan-García, Y; Pinzón-Rivadeneira, A

The aim of this study is to determine the prevalence of coeliac disease in patients of a basic health area in Valencia, on the Mediterranean coast, and describe their sociodemographic and clinical features. A descriptive, cross-sectional, observational study was conducted on a target population of the inhabitants of the Basic Health Area 14 th , Health Department Xàtiva-Ontinyent, in Valencia, comprising the municipalities of Ontinyent, Aielo de Malferit, and Fontanars dels Alforins. the patient belongs to a quota of Primary Care in the basic health area and the diagnosis of coeliac disease was active in the computerised medical records. the patient did not have any serology or intestinal biopsy compatible with coeliac disease. The study included 115 patients, selected to complete an interviewer-administered questionnaire. As 9 patients did not respond, the study was performed with 106 people. The prevalence of coeliac disease is 0.26%, and higher among women than among men (2.31: 1), with a statistically significant difference. The mean age of the patients was 29.71 years. The mean diagnostic delay was 5.15 years, and among the paediatric population it was 0.68 years. There were no statistically significant differences between patients (60) born in spring and summer, and the 46 born in autumn and winter. The prevalence of coeliac disease among first-degree relatives was 7.06%. Coeliac disease is an underdiagnosed condition in our environment, especially among adults, so knowledge and awareness about this disease by general practitioners is necessary. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Have Basic Mathematical Skills Grown Obsolete in the Computer Age: Assessing Basic Mathematical Skills and Forecasting Performance in a Business Statistics Course

ERIC Educational Resources Information Center

Noser, Thomas C.; Tanner, John R.; Shah, Situl

2008-01-01

The purpose of this study was to measure the comprehension of basic mathematical skills of students enrolled in statistics classes at a large regional university, and to determine if the scores earned on a basic math skills test are useful in forecasting student performance in these statistics classes, and to determine if students' basic math…

Selecting the most appropriate inferential statistical test for your quantitative research study.

PubMed

Bettany-Saltikov, Josette; Whittaker, Victoria Jane

2014-06-01

To discuss the issues and processes relating to the selection of the most appropriate statistical test. A review of the basic research concepts together with a number of clinical scenarios is used to illustrate this. Quantitative nursing research generally features the use of empirical data which necessitates the selection of both descriptive and statistical tests. Different types of research questions can be answered by different types of research designs, which in turn need to be matched to a specific statistical test(s). Discursive paper. This paper discusses the issues relating to the selection of the most appropriate statistical test and makes some recommendations as to how these might be dealt with. When conducting empirical quantitative studies, a number of key issues need to be considered. Considerations for selecting the most appropriate statistical tests are discussed and flow charts provided to facilitate this process. When nursing clinicians and researchers conduct quantitative research studies, it is crucial that the most appropriate statistical test is selected to enable valid conclusions to be made. © 2013 John Wiley & Sons Ltd.

The horse-collar aurora - A frequent pattern of the aurora in quiet times

NASA Technical Reports Server (NTRS)

Hones, E. W., Jr.; Craven, J. D.; Frank, L. A.; Evans, D. S.; Newell, P. T.

1989-01-01

The frequent appearance of the 'horse-collar aurora' pattern in quiet-time DE 1 images is reported, presenting a two-hour image sequence that displays the basic features and shows that it sometimes evolves toward the theta configuration. There is some evidence for interplanetary magnetic field B(y) influence on the temporal development of the pattern. A preliminary statistical analysis finds the pattern appearing in one-third or more of the image sequences recorded during quiet times.

Compressing random microstructures via stochastic Wang tilings.

PubMed

Novák, Jan; Kučerová, Anna; Zeman, Jan

2012-10-01

This Rapid Communication presents a stochastic Wang tiling-based technique to compress or reconstruct disordered microstructures on the basis of given spatial statistics. Unlike the existing approaches based on a single unit cell, it utilizes a finite set of tiles assembled by a stochastic tiling algorithm, thereby allowing to accurately reproduce long-range orientation orders in a computationally efficient manner. Although the basic features of the method are demonstrated for a two-dimensional particulate suspension, the present framework is fully extensible to generic multidimensional media.

Impact of Hearing Aid Technology on Outcomes in Daily Life III: Localization.

PubMed

Johnson, Jani A; Xu, Jingjing; Cox, Robyn M

Compared to basic-feature hearing aids, premium-feature hearing aids have more advanced technologies and sophisticated features. The objective of this study was to explore the difference between premium-feature and basic-feature hearing aids in horizontal sound localization in both laboratory and daily life environments. We hypothesized that premium-feature hearing aids would yield better localization performance than basic-feature hearing aids. Exemplars of premium-feature and basic-feature hearing aids from two major manufacturers were evaluated. Forty-five older adults (mean age 70.3 years) with essentially symmetrical mild to moderate sensorineural hearing loss were bilaterally fitted with each of the four pairs of hearing aids. Each pair of hearing aids was worn during a 4-week field trial and then evaluated using laboratory localization tests and a standardized questionnaire. Laboratory localization tests were conducted in a sound-treated room with a 360°, 24-loudspeaker array. Test stimuli were high frequency and low frequency filtered short sentences. The localization test in quiet was designed to assess the accuracy of front/back localization, while the localization test in noise was designed to assess the accuracy of locating sound sources throughout a 360° azimuth in the horizontal plane. Laboratory data showed that unaided localization was not significantly different from aided localization when all hearing aids were combined. Questionnaire data showed that aided localization was significantly better than unaided localization in everyday situations. Regarding the difference between premium-feature and basic-feature hearing aids, laboratory data showed that, overall, the premium-feature hearing aids yielded more accurate localization than the basic-feature hearing aids when high-frequency stimuli were used, and the listening environment was quiet. Otherwise, the premium-feature and basic-feature hearing aids yielded essentially the same performance in other laboratory tests and in daily life. The findings were consistent for both manufacturers. Laboratory tests for two of six major manufacturers showed that premium-feature hearing aids yielded better localization performance than basic-feature hearing aids in one out of four laboratory conditions. There was no difference between the two feature levels in self-reported everyday localization. Effectiveness research with different hearing aid technologies is necessary, and more research with other manufacturers' products is needed. Furthermore, these results confirm previous observations that research findings in laboratory conditions might not translate to everyday life.

Receiver operating characteristic (ROC) curves: review of methods with applications in diagnostic medicine

NASA Astrophysics Data System (ADS)

Obuchowski, Nancy A.; Bullen, Jennifer A.

2018-04-01

Receiver operating characteristic (ROC) analysis is a tool used to describe the discrimination accuracy of a diagnostic test or prediction model. While sensitivity and specificity are the basic metrics of accuracy, they have many limitations when characterizing test accuracy, particularly when comparing the accuracies of competing tests. In this article we review the basic study design features of ROC studies, illustrate sample size calculations, present statistical methods for measuring and comparing accuracy, and highlight commonly used ROC software. We include descriptions of multi-reader ROC study design and analysis, address frequently seen problems of verification and location bias, discuss clustered data, and provide strategies for testing endpoints in ROC studies. The methods are illustrated with a study of transmission ultrasound for diagnosing breast lesions.

Retrocausal Effects As A Consequence of Orthodox Quantum Mechanics Refined To Accommodate The Principle Of Sufficient Reason

NASA Astrophysics Data System (ADS)

Stapp, Henry P.

2011-11-01

The principle of sufficient reason asserts that anything that happens does so for a reason: no definite state of affairs can come into being unless there is a sufficient reason why that particular thing should happen. This principle is usually attributed to Leibniz, although the first recorded Western philosopher to use it was Anaximander of Miletus. The demand that nature be rational, in the sense that it be compatible with the principle of sufficient reason, conflicts with a basic feature of contemporary orthodox physical theory, namely the notion that nature's response to the probing action of an observer is determined by pure chance, and hence on the basis of absolutely no reason at all. This appeal to pure chance can be deemed to have no rational fundamental place in reason-based Western science. It is argued here, on the basis of the other basic principles of quantum physics, that in a world that conforms to the principle of sufficient reason, the usual quantum statistical rules will naturally emerge at the pragmatic level, in cases where the reason behind nature's choice of response is unknown, but that the usual statistics can become biased in an empirically manifest way when the reason for the choice is empirically identifiable. It is shown here that if the statistical laws of quantum mechanics were to be biased in this way then the basically forward-in-time unfolding of empirical reality described by orthodox quantum mechanics would generate the appearances of backward-time-effects of the kind that have been reported in the scientific literature.

M.S.L.A.P. Modular Spectral Line Analysis Program documentation

NASA Technical Reports Server (NTRS)

Joseph, Charles L.; Jenkins, Edward B.

1991-01-01

MSLAP is a software for analyzing spectra, providing the basic structure to identify spectral features, to make quantitative measurements of this features, and to store the measurements for convenient access. MSLAP can be used to measure not only the zeroth moment (equivalent width) of a profile, but also the first and second moments. Optical depths and the corresponding column densities across the profile can be measured as well for sufficiently high resolution data. The software was developed for an interactive, graphical analysis where the computer carries most of the computational and data organizational burden and the investigator is responsible only for all judgement decisions. It employs sophisticated statistical techniques for determining the best polynomial fit to the continuum and for calculating the uncertainties.

Integration of basic sciences and clinical sciences in oral radiology education for dental students.

PubMed

Baghdady, Mariam T; Carnahan, Heather; Lam, Ernest W N; Woods, Nicole N

2013-06-01

Educational research suggests that cognitive processing in diagnostic radiology requires a solid foundation in the basic sciences and knowledge of the radiological changes associated with disease. Although it is generally assumed that dental students must acquire both sets of knowledge, little is known about the most effective way to teach them. Currently, the basic and clinical sciences are taught separately. This study was conducted to compare the diagnostic accuracy of students when taught basic sciences segregated or integrated with clinical features. Predoctoral dental students (n=51) were taught four confusable intrabony abnormalities using basic science descriptions integrated with the radiographic features or taught segregated from the radiographic features. The students were tested with diagnostic images, and memory tests were performed immediately after learning and one week later. On immediate and delayed testing, participants in the integrated basic science group outperformed those from the segregated group. A main effect of learning condition was found to be significant (p<0.05). The results of this study support the critical role of integrating biomedical knowledge in diagnostic radiology and shows that teaching basic sciences integrated with clinical features produces higher diagnostic accuracy in novices than teaching basic sciences segregated from clinical features.

A Wave Chaotic Study of Quantum Graphs with Microwave Networks

NASA Astrophysics Data System (ADS)

Fu, Ziyuan

Quantum graphs provide a setting to test the hypothesis that all ray-chaotic systems show universal wave chaotic properties. I study the quantum graphs with a wave chaotic approach. Here, an experimental setup consisting of a microwave coaxial cable network is used to simulate quantum graphs. Some basic features and the distributions of impedance statistics are analyzed from experimental data on an ensemble of tetrahedral networks. The random coupling model (RCM) is applied in an attempt to uncover the universal statistical properties of the system. Deviations from RCM predictions have been observed in that the statistics of diagonal and off-diagonal impedance elements are different. Waves trapped due to multiple reflections on bonds between nodes in the graph most likely cause the deviations from universal behavior in the finite-size realization of a quantum graph. In addition, I have done some investigations on the Random Coupling Model, which are useful for further research.

Solar Photovoltaic DC Systems: Basics and Safety: Preprint

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

McNutt, Peter F; Sekulic, William R; Dreifuerst, Gary

Solar Photovoltaic (PV) systems are common and growing with 42.4 GW installed capacity in U.S. (almost 15 GW added in 2016). This paper will help electrical workers, and emergency responders understand the basic operating principles and hazards of PV DC arrays. We briefly discuss the following aspects of solar photovoltaic (PV) DC systems: the effects of solar radiation and temperature on output power; PV module testing standards; common system configurations; a simple PV array sizing example; NEC guidelines and other safety features; DC array commissioning, periodic maintenance and testing; arc-flash hazard potential; how electrical workers and emergency responders can andmore » do work safely around PV arrays; do moonlight and artificial lighting pose a real danger; typical safe operating procedures; and other potential DC-system hazards to be aware of. We also present some statistics on PV DC array electrical incidents and injuries. Safe PV array operation is possible with a good understanding of PV DC arrays basics and having good safe operating procedures in place.« less

Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction

PubMed Central

Cruz Zurian, Heber; Atefi, Seyed Reza; Seoane Martinez, Fernando; Lukowicz, Paul

2017-01-01

In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human-robot interactions. The sensor covers a 20-by-20 cm2 area with 400 sensitive points and samples at 50 Hz per point. We defined seven gestures which are inspired by the social and emotional interactions of typical people to people or pet scenarios. We conducted two groups of mutually blinded experiments, involving 29 participants in total. The data processing algorithm first reduces the spatial complexity to frame descriptors, and temporal features are calculated through basic statistical representations and wavelet analysis. Various classifiers are evaluated and the feature calculation algorithms are analyzed in details to determine each stage and segments’ contribution. The best performing feature-classifier combination can recognize the gestures with a 93.3% accuracy from a known group of participants, and 89.1% from strangers. PMID:29120389

Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction.

PubMed

Zhou, Bo; Altamirano, Carlos Andres Velez; Zurian, Heber Cruz; Atefi, Seyed Reza; Billing, Erik; Martinez, Fernando Seoane; Lukowicz, Paul

2017-11-09

In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human-robot interactions. The sensor covers a 20-by-20 cm 2 area with 400 sensitive points and samples at 50 Hz per point. We defined seven gestures which are inspired by the social and emotional interactions of typical people to people or pet scenarios. We conducted two groups of mutually blinded experiments, involving 29 participants in total. The data processing algorithm first reduces the spatial complexity to frame descriptors, and temporal features are calculated through basic statistical representations and wavelet analysis. Various classifiers are evaluated and the feature calculation algorithms are analyzed in details to determine each stage and segments' contribution. The best performing feature-classifier combination can recognize the gestures with a 93 . 3 % accuracy from a known group of participants, and 89 . 1 % from strangers.

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

NASA Astrophysics Data System (ADS)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

Multivariate assessment of event-related potentials with the t-CWT method.

PubMed

Bostanov, Vladimir

2015-11-05

Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain-computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single-trial ERPs. Multivariate ERP assessment can be facilitated by feature extraction methods. One such method is t-CWT, a mathematical-statistical algorithm based on the continuous wavelet transform (CWT) and Student's t-test. This article begins with a geometric primer on some basic concepts of multivariate statistics as applied to ERP assessment in general and to the t-CWT method in particular. Further, it presents for the first time a detailed, step-by-step, formal mathematical description of the t-CWT algorithm. A new multivariate outlier rejection procedure based on principal component analysis in the frequency domain is presented as an important pre-processing step. The MATLAB and GNU Octave implementation of t-CWT is also made publicly available for the first time as free and open source code. The method is demonstrated on some example ERP data obtained in a passive oddball paradigm. Finally, some conceptually novel applications of the multivariate approach in general and of the t-CWT method in particular are suggested and discussed. Hopefully, the publication of both the t-CWT source code and its underlying mathematical algorithm along with a didactic geometric introduction to some basic concepts of multivariate statistics would make t-CWT more accessible to both users and developers in the field of neuroscience research.

Mid-level perceptual features distinguish objects of different real-world sizes.

PubMed

Long, Bria; Konkle, Talia; Cohen, Michael A; Alvarez, George A

2016-01-01

Understanding how perceptual and conceptual representations are connected is a fundamental goal of cognitive science. Here, we focus on a broad conceptual distinction that constrains how we interact with objects--real-world size. Although there appear to be clear perceptual correlates for basic-level categories (apples look like other apples, oranges look like other oranges), the perceptual correlates of broader categorical distinctions are largely unexplored, i.e., do small objects look like other small objects? Because there are many kinds of small objects (e.g., cups, keys), there may be no reliable perceptual features that distinguish them from big objects (e.g., cars, tables). Contrary to this intuition, we demonstrated that big and small objects have reliable perceptual differences that can be extracted by early stages of visual processing. In a series of visual search studies, participants found target objects faster when the distractor objects differed in real-world size. These results held when we broadly sampled big and small objects, when we controlled for low-level features and image statistics, and when we reduced objects to texforms--unrecognizable textures that loosely preserve an object's form. However, this effect was absent when we used more basic textures. These results demonstrate that big and small objects have reliably different mid-level perceptual features, and suggest that early perceptual information about broad-category membership may influence downstream object perception, recognition, and categorization processes. (c) 2015 APA, all rights reserved).

Optimal Prediction in the Retina and Natural Motion Statistics

NASA Astrophysics Data System (ADS)

Salisbury, Jared M.; Palmer, Stephanie E.

2016-03-01

Almost all behaviors involve making predictions. Whether an organism is trying to catch prey, avoid predators, or simply move through a complex environment, the organism uses the data it collects through its senses to guide its actions by extracting from these data information about the future state of the world. A key aspect of the prediction problem is that not all features of the past sensory input have predictive power, and representing all features of the external sensory world is prohibitively costly both due to space and metabolic constraints. This leads to the hypothesis that neural systems are optimized for prediction. Here we describe theoretical and computational efforts to define and quantify the efficient representation of the predictive information by the brain. Another important feature of the prediction problem is that the physics of the world is diverse enough to contain a wide range of possible statistical ensembles, yet not all inputs are probable. Thus, the brain might not be a generalized predictive machine; it might have evolved to specifically solve the prediction problems most common in the natural environment. This paper summarizes recent results on predictive coding and optimal predictive information in the retina and suggests approaches for quantifying prediction in response to natural motion. Basic statistics of natural movies reveal that general patterns of spatiotemporal correlation are present across a wide range of scenes, though individual differences in motion type may be important for optimal processing of motion in a given ecological niche.

Predicting Cortical Dark/Bright Asymmetries from Natural Image Statistics and Early Visual Transforms

PubMed Central

Cooper, Emily A.; Norcia, Anthony M.

2015-01-01

The nervous system has evolved in an environment with structure and predictability. One of the ubiquitous principles of sensory systems is the creation of circuits that capitalize on this predictability. Previous work has identified predictable non-uniformities in the distributions of basic visual features in natural images that are relevant to the encoding tasks of the visual system. Here, we report that the well-established statistical distributions of visual features -- such as visual contrast, spatial scale, and depth -- differ between bright and dark image components. Following this analysis, we go on to trace how these differences in natural images translate into different patterns of cortical input that arise from the separate bright (ON) and dark (OFF) pathways originating in the retina. We use models of these early visual pathways to transform natural images into statistical patterns of cortical input. The models include the receptive fields and non-linear response properties of the magnocellular (M) and parvocellular (P) pathways, with their ON and OFF pathway divisions. The results indicate that there are regularities in visual cortical input beyond those that have previously been appreciated from the direct analysis of natural images. In particular, several dark/bright asymmetries provide a potential account for recently discovered asymmetries in how the brain processes visual features, such as violations of classic energy-type models. On the basis of our analysis, we expect that the dark/bright dichotomy in natural images plays a key role in the generation of both cortical and perceptual asymmetries. PMID:26020624

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

NASA Technical Reports Server (NTRS)

Coggeshall, M. E.; Hoffer, R. M.

1973-01-01

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

Children's identification of graphic symbols representing four basic emotions: comparison of Afrikaans-speaking and Sepedi-speaking children.

PubMed

DeKlerk, Hester M; Dada, Shakila; Alant, Erna

2014-01-01

Speech language pathologists recommend graphic symbols for AAC users to facilitate communication, including labelling and expressing emotions. The purpose of the current study was to describe and compare how 5- to 6-year-old Afrikaans- and Sepedi-speaking children identify and choose graphic symbols to depict four basic emotions, specifically happy, sad, afraid, and angry. Ninety participants were asked to select the graphic symbol from a 16-matrix communication overlay that would represent the emotion in response to 24 vignettes. The results of the t-tests indicated that the differences between the two groups' selection of target symbols to represent the four emotions are statistically significant. The results of the study indicate that children from different language groups may not perceive graphic symbols in the same way. The Afrikaans-speaking participants more often choose target symbols to represent target basic emotions than did the Sepedi-speaking participants. The most preferred symbols per emotion were identified and these different symbols were analysed in terms of facial features that distinguish them. Readers of this article will (1) recognise the importance of expressing basic emotions for children, particularly those that use AAC, (2) identify the possible limitations of line drawings for expressing and labelling basic emotions in typically developing children and (3) recognise the importance of cultural influences on recognition of basic emotions. Copyright © 2014 Elsevier Inc. All rights reserved.

Retrocausal Effects as a Consequence of Quantum Mechanics Refined to Accommodate the Principle of Sufficient Reason

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

Stapp, Henry P.

2011-05-10

The principle of sufficient reason asserts that anything that happens does so for a reason: no definite state of affairs can come into being unless there is a sufficient reason why that particular thing should happen. This principle is usually attributed to Leibniz, although the first recorded Western philosopher to use it was Anaximander of Miletus. The demand that nature be rational, in the sense that it be compatible with the principle of sufficient reason, conflicts with a basic feature of contemporary orthodox physical theory, namely the notion that nature's response to the probing action of an observer is determinedmore » by pure chance, and hence on the basis of absolutely no reason at all. This appeal to pure chance can be deemed to have no rational fundamental place in reason-based Western science. It is argued here, on the basis of the other basic principles of quantum physics, that in a world that conforms to the principle of sufficient reason, the usual quantum statistical rules will naturally emerge at the pragmatic level, in cases where the reason behind nature's choice of response is unknown, but that the usual statistics can become biased in an empirically manifest way when the reason for the choice is empirically identifiable. It is shown here that if the statistical laws of quantum mechanics were to be biased in this way then the basically forward-in-time unfolding of empirical reality described by orthodox quantum mechanics would generate the appearances of backward-time-effects of the kind that have been reported in the scientific literature.« less

Tendency to occupy a statistically dominant spatial state of the flow as a driving force for turbulent transition.

PubMed

Chekmarev, Sergei F

2013-03-01

The transition from laminar to turbulent fluid motion occurring at large Reynolds numbers is generally associated with the instability of the laminar flow. On the other hand, since the turbulent flow characteristically appears in the form of spatially localized structures (e.g., eddies) filling the flow field, a tendency to occupy such a structured state of the flow cannot be ruled out as a driving force for turbulent transition. To examine this possibility, we propose a simple analytical model that treats the flow as a collection of localized spatial structures, each of which consists of elementary cells in which the behavior of the particles (atoms or molecules) is uncorrelated. This allows us to introduce the Reynolds number, associating it with the ratio between the total phase volume for the system and that for the elementary cell. Using the principle of maximum entropy to calculate the most probable size distribution of the localized structures, we show that as the Reynolds number increases, the elementary cells group into the localized structures, which successfully explains turbulent transition and some other general properties of turbulent flows. An important feature of the present model is that a bridge between the spatial-statistical description of the flow and hydrodynamic equations is established. We show that the basic assumptions underlying the model, i.e., that the particles are indistinguishable and elementary volumes of phase space exist in which the state of the particles is uncertain, are involved in the derivation of the Navier-Stokes equation. Taking into account that the model captures essential features of turbulent flows, this suggests that the driving force for the turbulent transition is basically the same as in the present model, i.e., the tendency of the system to occupy a statistically dominant state plays a key role. The instability of the flow at high Reynolds numbers can then be a mechanism to initiate structural rearrangement of the flow to find this state.

Complex Topographic Feature Ontology Patterns

USGS Publications Warehouse

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

Investigating the limitations of tree species classification using the Combined Cluster and Discriminant Analysis method for low density ALS data from a dense forest region in Aggtelek (Hungary)

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Deák, Márton; Kovács, József; Székely, Balázs; Kelemen, Kristóf; Standovár, Tibor

2016-04-01

Airborne Laser Scanning (ALS) is a widely used technology for forestry classification applications. However, single tree detection and species classification from low density ALS point cloud is limited in a dense forest region. In this study we investigate the division of a forest into homogenous groups at stand level. The study area is located in the Aggtelek karst region (Northeast Hungary) with a complex relief topography. The ALS dataset contained only 4 discrete echoes (at 2-4 pt/m2 density) from the study area during leaf-on season. Ground-truth measurements about canopy closure and proportion of tree species cover are available for every 70 meter in 500 square meter circular plots. In the first step, ALS data were processed and geometrical and intensity based features were calculated into a 5×5 meter raster based grid. The derived features contained: basic statistics of relative height, canopy RMS, echo ratio, openness, pulse penetration ratio, basic statistics of radiometric feature. In the second step the data were investigated using Combined Cluster and Discriminant Analysis (CCDA, Kovács et al., 2014). The CCDA method first determines a basic grouping for the multiple circle shaped sampling locations using hierarchical clustering and then for the arising grouping possibilities a core cycle is executed comparing the goodness of the investigated groupings with random ones. Out of these comparisons difference values arise, yielding information about the optimal grouping out of the investigated ones. If sub-groups are then further investigated, one might even find homogeneous groups. We found that low density ALS data classification into homogeneous groups are highly dependent on canopy closure, and the proportion of the dominant tree species. The presented results show high potential using CCDA for determination of homogenous separable groups in LiDAR based tree species classification. Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP), data evaluation: 'Multipurpose assessment serving forest biodiversity conservation in the Carpathian region of Hungary', Swiss-Hungarian Cooperation Programme (SH/4/13 Project). BS contributed as an Alexander von Humboldt Research Fellow. J. Kovács, S. Kovács, N. Magyar, P. Tanos, I. G. Hatvani, and A. Anda (2014), Classification into homogeneous groups using combined cluster and discriminant analysis, Environmental Modelling & Software, 57, 52-59.

feets: feATURE eXTRACTOR for tIME sERIES

NASA Astrophysics Data System (ADS)

Cabral, Juan; Sanchez, Bruno; Ramos, Felipe; Gurovich, Sebastián; Granitto, Pablo; VanderPlas, Jake

2018-06-01

feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).

Scale-invariant feature extraction of neural network and renormalization group flow

NASA Astrophysics Data System (ADS)

Iso, Satoshi; Shiba, Shotaro; Yokoo, Sumito

2018-05-01

Theoretical understanding of how a deep neural network (DNN) extracts features from input images is still unclear, but it is widely believed that the extraction is performed hierarchically through a process of coarse graining. It reminds us of the basic renormalization group (RG) concept in statistical physics. In order to explore possible relations between DNN and RG, we use the restricted Boltzmann machine (RBM) applied to an Ising model and construct a flow of model parameters (in particular, temperature) generated by the RBM. We show that the unsupervised RBM trained by spin configurations at various temperatures from T =0 to T =6 generates a flow along which the temperature approaches the critical value Tc=2.2 7 . This behavior is the opposite of the typical RG flow of the Ising model. By analyzing various properties of the weight matrices of the trained RBM, we discuss why it flows towards Tc and how the RBM learns to extract features of spin configurations.

Hybrid ANN optimized artificial fish swarm algorithm based classifier for classification of suspicious lesions in breast DCE-MRI

NASA Astrophysics Data System (ADS)

Janaki Sathya, D.; Geetha, K.

2017-12-01

Automatic mass or lesion classification systems are developed to aid in distinguishing between malignant and benign lesions present in the breast DCE-MR images, the systems need to improve both the sensitivity and specificity of DCE-MR image interpretation in order to be successful for clinical use. A new classifier (a set of features together with a classification method) based on artificial neural networks trained using artificial fish swarm optimization (AFSO) algorithm is proposed in this paper. The basic idea behind the proposed classifier is to use AFSO algorithm for searching the best combination of synaptic weights for the neural network. An optimal set of features based on the statistical textural features is presented. The investigational outcomes of the proposed suspicious lesion classifier algorithm therefore confirm that the resulting classifier performs better than other such classifiers reported in the literature. Therefore this classifier demonstrates that the improvement in both the sensitivity and specificity are possible through automated image analysis.

Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.

NASA Astrophysics Data System (ADS)

Campo, D.; Quintero, O. L.; Bastidas, M.

2016-04-01

We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.

Water Interfaces, Solvation, and Spectroscopy

NASA Astrophysics Data System (ADS)

Geissler, Phillip L.

2013-04-01

Liquid water consistently expands our appreciation of the rich statistical mechanics that can emerge from simple molecular constituents. Here I review several interrelated areas of recent work on aqueous systems that aim to explore and explain this richness by revealing molecular arrangements, their thermodynamic origins, and the timescales on which they change. Vibrational spectroscopy of OH stretching features prominently in these discussions, with an emphasis on efforts to establish connections between spectroscopic signals and statistics of intermolecular structure. For bulk solutions, the results of these efforts largely verify and enrich existing physical pictures of hydrogen-bond network connectivity, dynamics, and response. For water at interfaces, such pictures are still emerging. As an important example I discuss the solvation of small ions at the air-water interface, whose surface propensities challenge a basic understanding of how aqueous fluctuations accommodate solutes in heterogeneous environments.

Teaching Basic Probability in Undergraduate Statistics or Management Science Courses

ERIC Educational Resources Information Center

Naidu, Jaideep T.; Sanford, John F.

2017-01-01

Standard textbooks in core Statistics and Management Science classes present various examples to introduce basic probability concepts to undergraduate business students. These include tossing of a coin, throwing a die, and examples of that nature. While these are good examples to introduce basic probability, we use improvised versions of Russian…

An intelligent system based on fuzzy probabilities for medical diagnosis– a study in aphasia diagnosis*

PubMed Central

Moshtagh-Khorasani, Majid; Akbarzadeh-T, Mohammad-R; Jahangiri, Nader; Khoobdel, Mehdi

2009-01-01

BACKGROUND: Aphasia diagnosis is particularly challenging due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. METHODS: Fuzzy probability is proposed here as the basic framework for handling the uncertainties in medical diagnosis and particularly aphasia diagnosis. To efficiently construct this fuzzy probabilistic mapping, statistical analysis is performed that constructs input membership functions as well as determines an effective set of input features. RESULTS: Considering the high sensitivity of performance measures to different distribution of testing/training sets, a statistical t-test of significance is applied to compare fuzzy approach results with NN results as well as author's earlier work using fuzzy logic. The proposed fuzzy probability estimator approach clearly provides better diagnosis for both classes of data sets. Specifically, for the first and second type of fuzzy probability classifiers, i.e. spontaneous speech and comprehensive model, P-values are 2.24E-08 and 0.0059, respectively, strongly rejecting the null hypothesis. CONCLUSIONS: The technique is applied and compared on both comprehensive and spontaneous speech test data for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. Statistical analysis confirms that the proposed approach can significantly improve accuracy using fewer Aphasia features. PMID:21772867

Statistics for nuclear engineers and scientists. Part 1. Basic statistical inference

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

Beggs, W.J.

1981-02-01

This report is intended for the use of engineers and scientists working in the nuclear industry, especially at the Bettis Atomic Power Laboratory. It serves as the basis for several Bettis in-house statistics courses. The objectives of the report are to introduce the reader to the language and concepts of statistics and to provide a basic set of techniques to apply to problems of the collection and analysis of data. Part 1 covers subjects of basic inference. The subjects include: descriptive statistics; probability; simple inference for normally distributed populations, and for non-normal populations as well; comparison of two populations; themore » analysis of variance; quality control procedures; and linear regression analysis.« less

The articulation of integration of clinical and basic sciences in concept maps: differences between experienced and resident groups.

PubMed

Vink, Sylvia; van Tartwijk, Jan; Verloop, Nico; Gosselink, Manon; Driessen, Erik; Bolk, Jan

2016-08-01

To determine the content of integrated curricula, clinical concepts and the underlying basic science concepts need to be made explicit. Preconstructed concept maps are recommended for this purpose. They are mainly constructed by experts. However, concept maps constructed by residents are hypothesized to be less complex, to reveal more tacit basic science concepts and these basic science concepts are expected to be used for the organization of the maps. These hypotheses are derived from studies about knowledge development of individuals. However, integrated curricula require a high degree of cooperation between clinicians and basic scientists. This study examined whether there are consistent variations regarding the articulation of integration when groups of experienced clinicians and basic scientists and groups of residents and basic scientists-in-training construct concept maps. Seven groups of three clinicians and basic scientists on experienced level and seven such groups on resident level constructed concept maps illuminating clinical problems. They were guided by instructions that focused them on articulation of integration. The concept maps were analysed by features that described integration. Descriptive statistics showed consistent variations between the two expertise levels. The concept maps of the resident groups exceeded those of the experienced groups in articulated integration. First, they used significantly more links between clinical and basic science concepts. Second, these links connected basic science concepts with a greater variety of clinical concepts than the experienced groups. Third, although residents did not use significantly more basic science concepts, they used them significantly more frequent to organize the clinical concepts. The conclusion was drawn that not all hypotheses could be confirmed and that the resident concept maps were more elaborate than expected. This article discusses the implications for the role that residents and basic scientists-in-training might play in the construction of preconstructed concept maps and the development of integrated curricula.

The general/specific breakdown of semantic memory and the nature of superordinate knowledge: insights from superordinate and basic-level feature norms.

PubMed

Marques, J Frederico

2007-12-01

The deterioration of semantic memory usually proceeds from more specific to more general superordinate categories, although rarer cases of superordinate knowledge impairment have also been reported. The nature of superordinate knowledge and the explanation of these two semantic impairments were evaluated from the analysis of superordinate and basic-level feature norms. The results show that, in comparison to basic-level concepts, superordinate concepts are not generally less informative and have similar feature distinctiveness and proportion of individual sensory features, but their features are less shared by their members. Results are in accord with explanations based on feature connection weights and/or concept confusability for the superordinate advantage cases. Results especially support an explanation for superordinate impairments in terms of higher semantic control requirements as related to features being less shared between concept members. Implications for patients with semantic impairments are also discussed.

An engineering, multiscale constitutive model for fiber-forming collagen in tension.

PubMed

Annovazzi, Lorella; Genna, Francesco

2010-01-01

This work proposes a nonlinear constitutive model for a single collagen fiber. Fiber-forming collagen can exhibit different hierarchies of basic units, called fascicles, bundles, fibrils, microfibrils, and so forth, down to the molecular (tropocollagen) level. Exploiting the fact that at each hierarchy level the microstructure can be seen, at least approximately, as that of a wavy, or crimped, extensible cable, the proposed stress-strain model considers a given number of levels, each of which contributes to the overall mechanical behavior according to its own geometrical features (crimp, or waviness), as well as to the basic mechanical properties of the tropocollagen. The crimp features at all levels are assumed to be random variables, whose statistical integration furnishes a stress-strain curve for a collagen fiber. The soundness of this model-the first, to the Authors' knowledge, to treat a single collagen fiber as a microstructured nonlinear structural element-is checked by its application to collagen fibers for which experimental results are available: rat tail tendon, periodontal ligament, and engineered ones. Here, no attempt is made to obtain a stress-strain law for generic collagenous tissues, which exhibit specific features, often much more complex than those of a single fiber. However, it is trivial to observe that the availability of a sound, microstructurally based constitutive law for a single collagen fiber (but applicable at any sub-level, or to any other material with a similar microstructure) is essential for assembling complex constitutive models for any collagenous fibrous tissue.

National policies for technical change: Where are the increasing returns to economic research?

PubMed Central

Pavitt, Keith

1996-01-01

Improvements over the past 30 years in statistical data, analysis, and related theory have strengthened the basis for science and technology policy by confirming the importance of technical change in national economic performance. But two important features of scientific and technological activities in the Organization for Economic Cooperation and Development countries are still not addressed adequately in mainstream economics: (i) the justification of public funding for basic research and (ii) persistent international differences in investment in research and development and related activities. In addition, one major gap is now emerging in our systems of empirical measurement—the development of software technology, especially in the service sector. There are therefore dangers of diminishing returns to the usefulness of economic research, which continues to rely completely on established theory and established statistical sources. Alternative propositions that deserve serious consideration are: (i) the economic usefulness of basic research is in the provision of (mainly tacit) skills rather than codified and applicable information; (ii) in developing and exploiting technological opportunities, institutional competencies are just as important as the incentive structures that they face; and (iii) software technology developed in traditional service sectors may now be a more important locus of technical change than software technology developed in “high-tech” manufacturing. PMID:8917481

Development and validation of a machine learning algorithm and hybrid system to predict the need for life-saving interventions in trauma patients.

PubMed

Liu, Nehemiah T; Holcomb, John B; Wade, Charles E; Batchinsky, Andriy I; Cancio, Leopoldo C; Darrah, Mark I; Salinas, José

2014-02-01

Accurate and effective diagnosis of actual injury severity can be problematic in trauma patients. Inherent physiologic compensatory mechanisms may prevent accurate diagnosis and mask true severity in many circumstances. The objective of this project was the development and validation of a multiparameter machine learning algorithm and system capable of predicting the need for life-saving interventions (LSIs) in trauma patients. Statistics based on means, slopes, and maxima of various vital sign measurements corresponding to 79 trauma patient records generated over 110,000 feature sets, which were used to develop, train, and implement the system. Comparisons among several machine learning models proved that a multilayer perceptron would best implement the algorithm in a hybrid system consisting of a machine learning component and basic detection rules. Additionally, 295,994 feature sets from 82 h of trauma patient data showed that the system can obtain 89.8 % accuracy within 5 min of recorded LSIs. Use of machine learning technologies combined with basic detection rules provides a potential approach for accurately assessing the need for LSIs in trauma patients. The performance of this system demonstrates that machine learning technology can be implemented in a real-time fashion and potentially used in a critical care environment.

A Mediation Model to Explain the Role of Mathematics Skills and Probabilistic Reasoning on Statistics Achievement

ERIC Educational Resources Information Center

Primi, Caterina; Donati, Maria Anna; Chiesi, Francesca

2016-01-01

Among the wide range of factors related to the acquisition of statistical knowledge, competence in basic mathematics, including basic probability, has received much attention. In this study, a mediation model was estimated to derive the total, direct, and indirect effects of mathematical competence on statistics achievement taking into account…

a Weighted Closed-Form Solution for Rgb-D Data Registration

NASA Astrophysics Data System (ADS)

Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.

2016-06-01

Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.

Detecting opinion spams through supervised boosting approach.

PubMed

Hazim, Mohamad; Anuar, Nor Badrul; Ab Razak, Mohd Faizal; Abdullah, Nor Aniza

2018-01-01

Product reviews are the individual's opinions, judgement or belief about a certain product or service provided by certain companies. Such reviews serve as guides for these companies to plan and monitor their business ventures in terms of increasing productivity or enhancing their product/service qualities. Product reviews can also increase business profits by convincing future customers about the products which they have interest in. In the mobile application marketplace such as Google Playstore, reviews and star ratings are used as indicators of the application quality. However, among all these reviews, hereby also known as opinions, spams also exist, to disrupt the online business balance. Previous studies used the time series and neural network approach (which require a lot of computational power) to detect these opinion spams. However, the detection performance can be restricted in terms of accuracy because the approach focusses on basic, discrete and document level features only thereby, projecting little statistical relationships. Aiming to improve the detection of opinion spams in mobile application marketplace, this study proposes using statistical based features that are modelled through the supervised boosting approach such as the Extreme Gradient Boost (XGBoost) and the Generalized Boosted Regression Model (GBM) to evaluate two multilingual datasets (i.e. English and Malay language). From the evaluation done, it was found that the XGBoost is most suitable for detecting opinion spams in the English dataset while the GBM Gaussian is most suitable for the Malay dataset. The comparative analysis also indicates that the implementation of the proposed statistical based features had achieved a detection accuracy rate of 87.43 per cent on the English dataset and 86.13 per cent on the Malay dataset.

A statistical evaluation and comparison of VISSR Atmospheric Sounder (VAS) data

NASA Technical Reports Server (NTRS)

Jedlovec, G. J.

1984-01-01

In order to account for the temporal and spatial discrepancies between the VAS and rawinsonde soundings, the rawinsonde data were adjusted to a common hour of release where the new observation time corresponded to the satellite scan time. Both the satellite and rawinsonde observations of the basic atmospheric parameters (T Td, and Z) were objectively analyzed to a uniform grid maintaining the same mesoscale structure in each data set. The performance of each retrieval algorithm in producing accurate and representative soundings was evaluated using statistical parameters such as the mean, standard deviation, and root mean square of the difference fields for each parameter and grid level. Horizontal structure was also qualitatively evaluated by examining atmospheric features on constant pressure surfaces. An analysis of the vertical structure of the atmosphere were also performed by looking at colocated and grid mean vertical profiles of both the satellite and rawinsonde data sets. Highlights of these results are presented.

Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

NASA Astrophysics Data System (ADS)

Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

2017-12-01

The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire

PubMed Central

Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-01-01

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra, extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. PMID:29589829

Utilization of satellite data for inventorying prairie ponds and lakes

USGS Publications Warehouse

Work, E.A.; Gilmer, D.S.

1976-01-01

By using data acquired by LANDSAT-1 (formerly ERTS- 1), studies were conducted in extracting information necessary for formulating management decisions relating to migratory waterfowl. Management decisions are based in part on an assessment ofhabitat characteristics, specifically numbers, distribution, and quality of ponds and lakes in the prime breeding range. This paper reports on a study concerned with mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single nearinfrared waveband. The results of this recognition were thematic maps and statistics relating to open surface water. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices.

PubMed

Lisk, Kristina; Agur, Anne M R; Woods, Nicole N

2016-06-01

Integration of basic and clinical science knowledge is increasingly being recognized as important for practice in the health professions. The concept of 'cognitive integration' places emphasis on the value of basic science in providing critical connections to clinical signs and symptoms while accounting for the fact that clinicians may not spontaneously articulate their use of basic science knowledge in clinical reasoning. In this study we used a diagnostic justification test to explore the impact of integrated basic science instruction on novices' diagnostic reasoning process. Participants were allocated to an integrated basic science or clinical science training group. The integrated basic science group was taught the clinical features along with the underlying causal mechanisms of four musculoskeletal pathologies while the clinical science group was taught only the clinical features. Participants completed a diagnostic accuracy test immediately after initial learning, and one week later a diagnostic accuracy and justification test. The results showed that novices who learned the integrated causal mechanisms had superior diagnostic accuracy and better understanding of the relative importance of key clinical features. These findings further our understanding of cognitive integration by providing evidence of the specific changes in clinical reasoning when basic and clinical sciences are integrated during learning.

Basic Radar Altimetry Toolbox and Radar Altimetry Tutorial: Tools for all Altimetry Users

NASA Astrophysics Data System (ADS)

Rosmorduc, Vinca; Benveniste, J.; Breebaart, L.; Bronner, E.; Dinardo, S.; Earith, D.; Lucas, B. M.; Maheu, C.; Niejmeier, S.; Picot, N.

2013-09-01

The Basic Radar Altimetry Toolbox is an "all- altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data, including the next mission to be launched, Saral.It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. Nearly 2000 people downloaded it (January 2012), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 to 4. Others are under development, some are in discussion for the future.The Basic Radar Altimetry Toolbox is able:- to read most distributed radar altimetry data, including the one from future missions like Saral, Jason-3- to perform some processing, data editing and statistic, - and to visualize the results.It can be used at several levels/several ways, including as an educational tool, with the graphical user interface.As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data.BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. More than 2000 people downloaded it (as of end of September 2012), with many "newcomers" to altimetry among them, and teachers/students. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 and 3. Others are envisioned, some are in discussion.

Interpretation of the results of statistical measurements. [search for basic probability model

NASA Technical Reports Server (NTRS)

Olshevskiy, V. V.

1973-01-01

For random processes, the calculated probability characteristic, and the measured statistical estimate are used in a quality functional, which defines the difference between the two functions. Based on the assumption that the statistical measurement procedure is organized so that the parameters for a selected model are optimized, it is shown that the interpretation of experimental research is a search for a basic probability model.

On Learning Cluster Coefficient of Private Networks

PubMed Central

Wang, Yue; Wu, Xintao; Zhu, Jun; Xiang, Yang

2013-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we treat a graph statistics as a function f and develop a divide and conquer approach to enforce differential privacy. The basic procedure of this approach is to first decompose the target computation f into several less complex unit computations f1, …, fm connected by basic mathematical operations (e.g., addition, subtraction, multiplication, division), then perturb the output of each fi with Laplace noise derived from its own sensitivity value and the distributed privacy threshold εi, and finally combine those perturbed fi as the perturbed output of computation f. We examine how various operations affect the accuracy of complex computations. When unit computations have large global sensitivity values, we enforce the differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We illustrate our approach by using clustering coefficient, which is a popular statistics used in social network analysis. Empirical evaluations on five real social networks and various synthetic graphs generated from three random graph models show the developed divide and conquer approach outperforms the direct approach. PMID:24429843

[Features of the structure and parameters of the intra-alveolar septa in residents of Western Siberia].

PubMed

Shishkin, G S; Ustiuzhaninova, N V

1998-01-01

In inhabitants of Novosibirsk and Moscow district intraalveolar septum, the basic functional element of the lung consists of interstitial connective tissue and capillar network, limited with basement membranes, on which cells of epithelial lining are placed. There are no principal differences in septal structure between individuals from both regions. The majority of morphometric parameters are statistically similar, although certain peculiarities were noted in human subjects from Siberia, the most important of which is that air-blood barrier in them is 33% thinner than those in inhabitants of Moscow district. Majority of capillaries possess the air-blood barrier from both sides. This increases diffous capacity of the lungs and blood oxygenation level.

Research progress on expansive soil cracks under changing environment.

PubMed

Shi, Bei-xiao; Zheng, Cheng-feng; Wu, Jin-kun

2014-01-01

Engineering problems shunned previously rise to the surface gradually with the activities of reforming the natural world in depth, the problem of expansive soil crack under the changing environment becoming a control factor of expansive soil slope stability. The problem of expansive soil crack has gradually become a research hotspot, elaborates the occurrence and development of cracks from the basic properties of expansive soil, and points out the role of controlling the crack of expansive soil strength. We summarize the existing research methods and results of expansive soil crack characteristics. Improving crack measurement and calculation method and researching the crack depth measurement, statistical analysis method, crack depth and surface feature relationship will be the future direction.

Unraveling multiple changes in complex climate time series using Bayesian inference

NASA Astrophysics Data System (ADS)

Berner, Nadine; Trauth, Martin H.; Holschneider, Matthias

2016-04-01

Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of observations. Unraveling such transitions yields essential information for the understanding of the observed system. The precise detection and basic characterization of underlying changes is therefore of particular importance in environmental sciences. We present a kernel-based Bayesian inference approach to investigate direct as well as indirect climate observations for multiple generic transition events. In order to develop a diagnostic approach designed to capture a variety of natural processes, the basic statistical features of central tendency and dispersion are used to locally approximate a complex time series by a generic transition model. A Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of such a transition. To systematically investigate time series for multiple changes occurring at different temporal scales, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. Thus, based on a generic transition model a probability expression is derived that is capable to indicate multiple changes within a complex time series. We discuss the method's performance by investigating direct and indirect climate observations. The approach is applied to environmental time series (about 100 a), from the weather station in Tuscaloosa, Alabama, and confirms documented instrumentation changes. Moreover, the approach is used to investigate a set of complex terrigenous dust records from the ODP sites 659, 721/722 and 967 interpreted as climate indicators of the African region of the Plio-Pleistocene period (about 5 Ma). The detailed inference unravels multiple transitions underlying the indirect climate observations coinciding with established global climate events.

Spontaneous ultraweak photon emission from biological systems and the endogenous light field.

PubMed

Schwabl, Herbert; Klima, Herbert

2005-04-01

Still one of the most astonishing biological electromagnetic phenomena is the ultraweak photon emission (UPE) from living systems. Organisms and tissues spontaneously emit measurable intensities of light, i.e. photons in the visible part of the electromagnetic spectrum (380-780 nm), in the range from 1 to 1,000 photons x s-1 x cm-2, depending on their condition and vitality. It is important not to confuse UPE from living systems with other biogenic light emitting processes such as bioluminescence or chemiluminescence. This article examines with basic considerations from physics on the quantum nature of photons the empirical phenomenon of UPE. This leads to the description of the non-thermal origin of this radiation. This is in good correspondence with the modern understanding of life phenomena as dissipative processes far from thermodynamic equilibrium. UPE also supports the understanding of life sustaining processes as basically driven by electromagnetic fields. The basic features of UPE, like intensity and spectral distribution, are known in principle for many experimental situations. The UPE of human leukocytes contributes to an endogenous light field of about 1011 photons x s-1 which can be influenced by certain factors. Further research is needed to reveal the statistical properties of UPE and in consequence to answer questions about the underlying mechanics of the biological system. In principle, statistical properties of UPE allow to reconstruct phase-space dynamics of the light emitting structures. Many open questions remain until a proper understanding of the electromagnetic interaction of the human organism can be achieved: which structures act as receptors and emitters for electromagnetic radiation? How is electromagnetic information received and processed within cells?

Directly observable optical properties of sprites in Central Europe

NASA Astrophysics Data System (ADS)

Bór, József

2013-04-01

Luminous optical emissions accompanying streamer-based natural electric breakdown processes initiating in the mesosphere are called sprites. 489 sprite events have been observed with a TV frame rate video system in Central Europe from Sopron (47.68N, 16.58E, 230 m MSL), Hungary between 2007 and 2009. On the basis of these observations, characteristic morphological properties of sprites, i.e. basic forms (e.g. column, carrot, angel, etc.) as well as common morphological features (e.g. tendrils, glows, puffs, beads, etc.), have been identified. Probable time sequences of streamer propagation directions were associated with each of the basic sprite forms. It is speculated that different sequences of streamer propagation directions can result in very similar final sprite shapes. The number and type variety of sprite elements appearing in an event as well as the total optical duration of an event was analyzed statistically. Jellyfish and dancing sprite events were considered as special subsets of sprite clusters. It was found that more than 90% of the recorded sprite elements appeared in clusters rather than alone and more than half of the clusters contained more than one basic sprite forms. The analysis showed that jellyfish sprites and clusters of column sprites featuring glows and tendrils do not tend to have optical lifetimes longer than 80 ms. Such very long optical lifetimes have not been observed in sprite clusters containing more than 25 elements of any type, either. In contrast to clusters containing sprite entities of only one form, sprite events showing more sprite forms seem to have extended optical durations more likely. The need for further investigation and for finding theoretical concepts to link these observations to electric conditions ambient for sprite formation is emphasized.

Applied Problems and Use of Technology in an Aligned Way in Basic Courses in Probability and Statistics for Engineering Students--A Way to Enhance Understanding and Increase Motivation

ERIC Educational Resources Information Center

Zetterqvist, Lena

2017-01-01

Researchers and teachers often recommend motivating exercises and use of mathematics or statistics software for the teaching of basic courses in probability and statistics. Our courses are given to large groups of engineering students at Lund Institute of Technology. We found that the mere existence of real-life data and technology in a course…

A basic introduction to statistics for the orthopaedic surgeon.

PubMed

Bertrand, Catherine; Van Riet, Roger; Verstreken, Frederik; Michielsen, Jef

2012-02-01

Orthopaedic surgeons should review the orthopaedic literature in order to keep pace with the latest insights and practices. A good understanding of basic statistical principles is of crucial importance to the ability to read articles critically, to interpret results and to arrive at correct conclusions. This paper explains some of the key concepts in statistics, including hypothesis testing, Type I and Type II errors, testing of normality, sample size and p values.

A hierarchical classification method for finger knuckle print recognition

NASA Astrophysics Data System (ADS)

Kong, Tao; Yang, Gongping; Yang, Lu

2014-12-01

Finger knuckle print has recently been seen as an effective biometric technique. In this paper, we propose a hierarchical classification method for finger knuckle print recognition, which is rooted in traditional score-level fusion methods. In the proposed method, we firstly take Gabor feature as the basic feature for finger knuckle print recognition and then a new decision rule is defined based on the predefined threshold. Finally, the minor feature speeded-up robust feature is conducted for these users, who cannot be recognized by the basic feature. Extensive experiments are performed to evaluate the proposed method, and experimental results show that it can achieve a promising performance.

Using Data Mining to Teach Applied Statistics and Correlation

ERIC Educational Resources Information Center

Hartnett, Jessica L.

2016-01-01

This article describes two class activities that introduce the concept of data mining and very basic data mining analyses. Assessment data suggest that students learned some of the conceptual basics of data mining, understood some of the ethical concerns related to the practice, and were able to perform correlations via the Statistical Package for…

Simple Data Sets for Distinct Basic Summary Statistics

ERIC Educational Resources Information Center

Lesser, Lawrence M.

2011-01-01

It is important to avoid ambiguity with numbers because unfortunate choices of numbers can inadvertently make it possible for students to form misconceptions or make it difficult for teachers to tell if students obtained the right answer for the right reason. Therefore, it is important to make sure when introducing basic summary statistics that…

Persian Basic Course: Volume III, Lessons 29-38.

ERIC Educational Resources Information Center

Defense Language Inst., Monterey, CA.

The third of 10 volumes of a basic course in Persian is presented that is designed for use in the Defense Language Institute's intensive programs for native English speakers. The central feature of the daily lesson is the structured dialogue, which systematically incorporates a number of grammatical features. Grammar is not explained through…

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

PubMed

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Progress in Turbulence Detection via GNSS Occultation Data

NASA Technical Reports Server (NTRS)

Cornman, L. B.; Goodrich, R. K.; Axelrad, P.; Barlow, E.

2012-01-01

The increased availability of radio occultation (RO) data offers the ability to detect and study turbulence in the Earth's atmosphere. An analysis of how RO data can be used to determine the strength and location of turbulent regions is presented. This includes the derivation of a model for the power spectrum of the log-amplitude and phase fluctuations of the permittivity (or index of refraction) field. The bulk of the paper is then concerned with the estimation of the model parameters. Parameter estimators are introduced and some of their statistical properties are studied. These estimators are then applied to simulated log-amplitude RO signals. This includes the analysis of global statistics derived from a large number of realizations, as well as case studies that illustrate various specific aspects of the problem. Improvements to the basic estimation methods are discussed, and their beneficial properties are illustrated. The estimation techniques are then applied to real occultation data. Only two cases are presented, but they illustrate some of the salient features inherent in real data.

Variations in intensity statistics for representational and abstract art, and for art from the Eastern and Western hemispheres.

PubMed

Graham, Daniel J; Field, David J

2008-01-01

Two recent studies suggest that natural scenes and paintings show similar statistical properties. But does the content or region of origin of an artwork affect its statistical properties? We addressed this question by having judges place paintings from a large, diverse collection of paintings into one of three subject-matter categories using a forced-choice paradigm. Basic statistics for images whose caterogization was agreed by all judges showed no significant differences between those judged to be 'landscape' and 'portrait/still-life', but these two classes differed from paintings judged to be 'abstract'. All categories showed basic spatial statistical regularities similar to those typical of natural scenes. A test of the full painting collection (140 images) with respect to the works' place of origin (provenance) showed significant differences between Eastern works and Western ones, differences which we find are likely related to the materials and the choice of background color. Although artists deviate slightly from reproducing natural statistics in abstract art (compared to representational art), the great majority of human art likely shares basic statistical limitations. We argue that statistical regularities in art are rooted in the need to make art visible to the eye, not in the inherent aesthetic value of natural-scene statistics, and we suggest that variability in spatial statistics may be generally imposed by manufacture.

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire.

PubMed

Han, Shuting; Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-03-28

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra , extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. © 2018, Han et al.

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

NASA Technical Reports Server (NTRS)

Poulton, C. E.

1975-01-01

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Building Damage Extraction Triggered by Earthquake Using the Uav Imagery

NASA Astrophysics Data System (ADS)

Li, S.; Tang, H.

2018-04-01

When extracting building damage information, we can only determine whether the building is collapsed using the post-earthquake satellite images. Even the satellite images have the sub-meter resolution, the identification of slightly damaged buildings is still a challenge. As the complementary data to satellite images, the UAV images have unique advantages, such as stronger flexibility and higher resolution. In this paper, according to the spectral feature of UAV images and the morphological feature of the reconstructed point clouds, the building damage was classified into four levels: basically intact buildings, slightly damaged buildings, partially collapsed buildings and totally collapsed buildings, and give the rules of damage grades. In particular, the slightly damaged buildings are determined using the detected roof-holes. In order to verify the approach, we conduct experimental simulations in the cases of Wenchuan and Ya'an earthquakes. By analyzing the post-earthquake UAV images of the two earthquakes, the building damage was classified into four levels, and the quantitative statistics of the damaged buildings is given in the experiments.

Basic statistics (the fundamental concepts).

PubMed

Lim, Eric

2014-12-01

An appreciation and understanding of statistics is import to all practising clinicians, not simply researchers. This is because mathematics is the fundamental basis to which we base clinical decisions, usually with reference to the benefit in relation to risk. Unless a clinician has a basic understanding of statistics, he or she will never be in a position to question healthcare management decisions that have been handed down from generation to generation, will not be able to conduct research effectively nor evaluate the validity of published evidence (usually making an assumption that most published work is either all good or all bad). This article provides a brief introduction to basic statistical methods and illustrates its use in common clinical scenarios. In addition, pitfalls of incorrect usage have been highlighted. However, it is not meant to be a substitute for formal training or consultation with a qualified and experienced medical statistician prior to starting any research project.

Strong nonadditivity as a key structure-activity relationship feature: distinguishing structural changes from assay artifacts.

PubMed

Kramer, Christian; Fuchs, Julian E; Liedl, Klaus R

2015-03-23

Nonadditivity in protein-ligand affinity data represents highly instructive structure-activity relationship (SAR) features that indicate structural changes and have the potential to guide rational drug design. At the same time, nonadditivity is a challenge for both basic SAR analysis as well as many ligand-based data analysis techniques such as Free-Wilson Analysis and Matched Molecular Pair analysis, since linear substituent contribution models inherently assume additivity and thus do not work in such cases. While structural causes for nonadditivity have been analyzed anecdotally, no systematic approaches to interpret and use nonadditivity prospectively have been developed yet. In this contribution, we lay the statistical framework for systematic analysis of nonadditivity in a SAR series. First, we develop a general metric to quantify nonadditivity. Then, we demonstrate the non-negligible impact of experimental uncertainty that creates apparent nonadditivity, and we introduce techniques to handle experimental uncertainty. Finally, we analyze public SAR data sets for strong nonadditivity and use recourse to the original publications and available X-ray structures to find structural explanations for the nonadditivity observed. We find that all cases of strong nonadditivity (ΔΔpKi and ΔΔpIC50 > 2.0 log units) with sufficient structural information to generate reasonable hypothesis involve changes in binding mode. With the appropriate statistical basis, nonadditivity analysis offers a variety of new attempts for various areas in computer-aided drug design, including the validation of scoring functions and free energy perturbation approaches, binding pocket classification, and novel features in SAR analysis tools.

Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) Tutorial

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

C. L. Smith; S. T. Beck; S. T. Wood

2008-08-01

The Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) refers to a set of computer programs that were developed to create and analyze probabilistic risk assessment (PRAs). This volume is the tutorial manual for the SAPHIRE system. In this document, a series of lessons are provided that guide the user through basic steps common to most analyses preformed with SAPHIRE. The tutorial is divided into two major sections covering both basic and advanced features. The section covering basic topics contains lessons that lead the reader through development of a probabilistic hypothetical problem involving a vehicle accident, highlighting the program’smore » most fundamental features. The advanced features section contains additional lessons that expand on fundamental analysis features of SAPHIRE and provide insights into more complex analysis techniques. Together, these two elements provide an overview into the operation and capabilities of the SAPHIRE software.« less

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking

PubMed Central

Peel, Hayden J.; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A.

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features. PMID:29725292

Perceptual Discrimination of Basic Object Features Is Not Facilitated When Priming Stimuli Are Prevented From Reaching Awareness by Means of Visual Masking.

PubMed

Peel, Hayden J; Sperandio, Irene; Laycock, Robin; Chouinard, Philippe A

2018-01-01

Our understanding of how form, orientation and size are processed within and outside of awareness is limited and requires further investigation. Therefore, we investigated whether or not the visual discrimination of basic object features can be influenced by subliminal processing of stimuli presented beforehand. Visual masking was used to render stimuli perceptually invisible. Three experiments examined if visible and invisible primes could facilitate the subsequent feature discrimination of visible targets. The experiments differed in the kind of perceptual discrimination that participants had to make. Namely, participants were asked to discriminate visual stimuli on the basis of their form, orientation, or size. In all three experiments, we demonstrated reliable priming effects when the primes were visible but not when the primes were made invisible. Our findings underscore the importance of conscious awareness in facilitating the perceptual discrimination of basic object features.

Fieldcrest Cannon, Inc. Advanced Technical Preparation. Statistical Process Control (SPC). PRE-SPC I. Instructor Book.

ERIC Educational Resources Information Center

Averitt, Sallie D.

This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator…

From Research to Practice: Basic Mathematics Skills and Success in Introductory Statistics

ERIC Educational Resources Information Center

Lunsford, M. Leigh; Poplin, Phillip

2011-01-01

Based on previous research of Johnson and Kuennen (2006), we conducted a study to determine factors that would possibly predict student success in an introductory statistics course. Our results were similar to Johnson and Kuennen in that we found students' basic mathematical skills, as measured on a test created by Johnson and Kuennen, were a…

Improving EMG based classification of basic hand movements using EMD.

PubMed

Sapsanis, Christos; Georgoulas, George; Tzes, Anthony; Lymberopoulos, Dimitrios

2013-01-01

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

Grouping and Emergent Features in Vision: Toward a Theory of Basic Gestalts

ERIC Educational Resources Information Center

Pomerantz, James R.; Portillo, Mary C.

2011-01-01

Gestalt phenomena are often so powerful that mere demonstrations can confirm their existence, but Gestalts have proven hard to define and measure. Here we outline a theory of basic Gestalts (TBG) that defines Gestalts as emergent features (EFs). The logic relies on discovering wholes that are more discriminable than are the parts from which they…

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency

PubMed Central

Chen, Yuhan; Wang, Shengjun

2017-01-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases. PMID:28961235

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

PubMed

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases.

A Survey of Introductory Statistics Courses at University Faculties of Pharmaceutical Sciences in Japan.

PubMed

Matsumura, Mina; Nakayama, Takuto; Sozu, Takashi

2016-01-01

A survey of introductory statistics courses at Japanese medical schools was published as a report in 2014. To obtain a complete understanding of the way in which statistics is taught at the university level in Japan, it is important to extend this survey to related fields, including pharmacy, dentistry, and nursing. The current study investigates the introductory statistics courses offered by faculties of pharmaceutical sciences (six-year programs) at Japanese universities, comparing the features of these courses with those studied in the survey of medical schools. We collected relevant data from the online syllabi of statistics courses published on the websites of 71 universities. The survey items included basic course information (for example, the course names, the targeted student grades, the number of credits, and course classification), textbooks, handouts, the doctoral subject and employment status of each lecturer, and course contents. The period surveyed was July-September 2015. We found that these 71 universities offered a total of 128 statistics courses. There were 67 course names, the most common of which was "biostatistics (iryou toukeigaku)." About half of the courses were designed for first- or second-year students. Students earned fewer than two credits. There were 62 different types of textbooks. The lecturers held doctoral degrees in 18 different subjects, the most common being a doctorate in pharmacy or science. Some course content differed, reflecting the lecturers' academic specialties. The content of introductory statistics courses taught in pharmaceutical science programs also differed slightly from the equivalent content taught in medical schools.

Multispectral processing based on groups of resolution elements

NASA Technical Reports Server (NTRS)

Richardson, W.; Gleason, J. M.

1975-01-01

Several nine-point rules are defined and compared with previously studied rules. One of the rules performed well in boundary areas, but with reduced efficiency in field interiors; another combined best performance on field interiors with good sensitivity to boundary detail. The basic threshold gradient and some modifications were investigated as a means of boundary point detection. The hypothesis testing methods of closed-boundary formation were also tested and evaluated. An analysis of the boundary detection problem was initiated, employing statistical signal detection and parameter estimation techniques to analyze various formulations of the problem. These formulations permit the atmospheric and sensor system effects on the data to be thoroughly analyzed. Various boundary features and necessary assumptions can also be investigated in this manner.

Brownian dynamics of self-regulated particles with additional degrees of freedom: Symmetry breaking and homochirality

NASA Astrophysics Data System (ADS)

Bhattacharyya, Debankur; Paul, Shibashis; Ghosh, Shyamolina; Ray, Deb Shankar

2018-04-01

We consider the Brownian motion of a collection of particles each with an additional degree of freedom. The degree of freedom of a particle (or, in general, a molecule) can assume distinct values corresponding to certain states or conformations. The time evolution of the additional degree of freedom of a particle is guided by those of its neighbors as well as the temperature of the system. We show that the local averaging over these degrees of freedom results in emergence of a collective order in the dynamics in the form of selection or dominance of one of the isomers leading to a symmetry-broken state. Our statistical model captures the basic features of homochirality, e.g., autocatalysis and chiral inhibition.

Memory of Gender and Gait Direction from Biological Motion: Gender Fades Away but Directions Stay

ERIC Educational Resources Information Center

Poom, Leo

2012-01-01

The delayed discrimination methodology has been used to demonstrate a high-fidelity nondecaying visual short-term memory (VSTM) for so-called preattentive basic features. In the current Study, I show that the nondecaying high VSTM precision is not restricted to basic features by using the same method to measure memory precision for gait direction…

Descriptive data analysis.

PubMed

Thompson, Cheryl Bagley

2009-01-01

This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training

PubMed Central

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer. PMID:26873777

Dominant region: a basic feature for group motion analysis and its application to teamwork evaluation in soccer games

NASA Astrophysics Data System (ADS)

Taki, Tsuyoshi; Hasegawa, Jun-ichi

1998-12-01

This paper proposes a basic feature for quantitative measurement and evaluation of group behavior of persons. This feature called 'dominant region' is a kind of sphere of influence for each person in the group. The dominant region is defined as a region in where the person can arrive earlier than any other persons and can be formulated as Voronoi region modified by replacing the distance function with a time function. This time function is calculated based on a computational model of moving ability of the person. As an application of the dominant region, we present a motion analysis system of soccer games. The purpose of this system is to evaluate the teamwork quantitatively based on movement of all the players in the game. From experiments using motion pictures of actual games, it is suggested that the proposed feature is useful for measurement and evaluation of group behavior in team sports. This basic feature may be applied to other team ball games, such as American football, basketball, handball and water polo.

Quantitative Hyperspectral Reflectance Imaging

PubMed Central

Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

2008-01-01

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

ECG Identification System Using Neural Network with Global and Local Features

ERIC Educational Resources Information Center

Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

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)

Applications of statistics to medical science (1) Fundamental concepts.

PubMed

Watanabe, Hiroshi

2011-01-01

The conceptual framework of statistical tests and statistical inferences are discussed, and the epidemiological background of statistics is briefly reviewed. This study is one of a series in which we survey the basics of statistics and practical methods used in medical statistics. Arguments related to actual statistical analysis procedures will be made in subsequent papers.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

A Comparison of Computer-Assisted Instruction and the Traditional Method of Teaching Basic Statistics

ERIC Educational Resources Information Center

Ragasa, Carmelita Y.

2008-01-01

The objective of the study is to determine if there is a significant difference in the effects of the treatment and control groups on achievement as well as on attitude as measured by the posttest. A class of 38 sophomore college students in the basic statistics taught with the use of computer-assisted instruction and another class of 15 students…

Cause and Effect: Testing a Mechanism and Method for the Cognitive Integration of Basic Science.

PubMed

Kulasegaram, Kulamakan; Manzone, Julian C; Ku, Cheryl; Skye, Aimee; Wadey, Veronica; Woods, Nicole N

2015-11-01

Methods of integrating basic science with clinical knowledge are still debated in medical training. One possibility is increasing the spatial and temporal proximity of clinical content to basic science. An alternative model argues that teaching must purposefully expose relationships between the domains. The authors compared different methods of integrating basic science: causal explanations linking basic science to clinical features, presenting both domains separately but in proximity, and simply presenting clinical features First-year undergraduate health professions students were randomized to four conditions: (1) science-causal explanations (SC), (2) basic science before clinical concepts (BC), (3) clinical concepts before basic science (CB), and (4) clinical features list only (FL). Based on assigned conditions, participants were given explanations for four disorders in neurology or rheumatology followed by a memory quiz and diagnostic test consisting of 12 cases which were repeated after one week. Ninety-four participants completed the study. No difference was found on memory test performance, but on the diagnostic test, a condition by time interaction was found (F[3,88] = 3.05, P < .03, ηp = 0.10). Although all groups had similar immediate performance, the SC group had a minimal decrease in performance on delayed testing; the CB and FL groups had the greatest decreases. These results suggest that creating proximity between basic science and clinical concepts may not guarantee cognitive integration. Although cause-and-effect explanations may not be possible for all domains, making explicit and specific connections between domains will likely facilitate the benefits of integration for learners.

Back to basics: an introduction to statistics.

PubMed

Halfens, R J G; Meijers, J M M

2013-05-01

In the second in the series, Professor Ruud Halfens and Dr Judith Meijers give an overview of statistics, both descriptive and inferential. They describe the first principles of statistics, including some relevant inferential tests.

A novel algorithm to detect glaucoma risk using texton and local configuration pattern features extracted from fundus images.

PubMed

Acharya, U Rajendra; Bhat, Shreya; Koh, Joel E W; Bhandary, Sulatha V; Adeli, Hojjat

2017-09-01

Glaucoma is an optic neuropathy defined by characteristic damage to the optic nerve and accompanying visual field deficits. Early diagnosis and treatment are critical to prevent irreversible vision loss and ultimate blindness. Current techniques for computer-aided analysis of the optic nerve and retinal nerve fiber layer (RNFL) are expensive and require keen interpretation by trained specialists. Hence, an automated system is highly desirable for a cost-effective and accurate screening for the diagnosis of glaucoma. This paper presents a new methodology and a computerized diagnostic system. Adaptive histogram equalization is used to convert color images to grayscale images followed by convolution of these images with Leung-Malik (LM), Schmid (S), and maximum response (MR4 and MR8) filter banks. The basic microstructures in typical images are called textons. The convolution process produces textons. Local configuration pattern (LCP) features are extracted from these textons. The significant features are selected using a sequential floating forward search (SFFS) method and ranked using the statistical t-test. Finally, various classifiers are used for classification of images into normal and glaucomatous classes. A high classification accuracy of 95.8% is achieved using six features obtained from the LM filter bank and the k-nearest neighbor (kNN) classifier. A glaucoma integrative index (GRI) is also formulated to obtain a reliable and effective system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

NASA Astrophysics Data System (ADS)

Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

2017-08-01

This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

How language production shapes language form and comprehension

PubMed Central

MacDonald, Maryellen C.

2012-01-01

Language production processes can provide insight into how language comprehension works and language typology—why languages tend to have certain characteristics more often than others. Drawing on work in memory retrieval, motor planning, and serial order in action planning, the Production-Distribution-Comprehension (PDC) account links work in the fields of language production, typology, and comprehension: (1) faced with substantial computational burdens of planning and producing utterances, language producers implicitly follow three biases in utterance planning that promote word order choices that reduce these burdens, thereby improving production fluency. (2) These choices, repeated over many utterances and individuals, shape the distributions of utterance forms in language. The claim that language form stems in large degree from producers' attempts to mitigate utterance planning difficulty is contrasted with alternative accounts in which form is driven by language use more broadly, language acquisition processes, or producers' attempts to create language forms that are easily understood by comprehenders. (3) Language perceivers implicitly learn the statistical regularities in their linguistic input, and they use this prior experience to guide comprehension of subsequent language. In particular, they learn to predict the sequential structure of linguistic signals, based on the statistics of previously-encountered input. Thus, key aspects of comprehension behavior are tied to lexico-syntactic statistics in the language, which in turn derive from utterance planning biases promoting production of comparatively easy utterance forms over more difficult ones. This approach contrasts with classic theories in which comprehension behaviors are attributed to innate design features of the language comprehension system and associated working memory. The PDC instead links basic features of comprehension to a different source: production processes that shape language form. PMID:23637689

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Understanding Statistical Concepts and Terms in Context: The GovStat Ontology and the Statistical Interactive Glossary.

ERIC Educational Resources Information Center

Haas, Stephanie W.; Pattuelli, Maria Cristina; Brown, Ron T.

2003-01-01

Describes the Statistical Interactive Glossary (SIG), an enhanced glossary of statistical terms supported by the GovStat ontology of statistical concepts. Presents a conceptual framework whose components articulate different aspects of a term's basic explanation that can be manipulated to produce a variety of presentations. The overarching…

Probability, statistics, and computational science.

PubMed

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.

PubMed

Li, Chuan; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Cabrera, Diego

2016-06-17

Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs) are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM). The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults.

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning

PubMed Central

Li, Chuan; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Cabrera, Diego

2016-01-01

Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs) are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM). The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults. PMID:27322273

Fish: A New Computer Program for Friendly Introductory Statistics Help

ERIC Educational Resources Information Center

Brooks, Gordon P.; Raffle, Holly

2005-01-01

All introductory statistics students must master certain basic descriptive statistics, including means, standard deviations and correlations. Students must also gain insight into such complex concepts as the central limit theorem and standard error. This article introduces and describes the Friendly Introductory Statistics Help (FISH) computer…

Grouping and emergent features in vision: toward a theory of basic Gestalts.

PubMed

Pomerantz, James R; Portillo, Mary C

2011-10-01

Gestalt phenomena are often so powerful that mere demonstrations can confirm their existence, but Gestalts have proven hard to define and measure. Here we outline a theory of basic Gestalts (TBG) that defines Gestalts as emergent features (EFs). The logic relies on discovering wholes that are more discriminable than are the parts from which they are built. These wholes contain EFs that can act as basic features in human vision. As context is added to a visual stimulus, a hierarchy of EFs appears. Starting with a single dot and adding a second yields the first two potential EFs: the proximity (distance) and orientation (angle) between the two dots. A third dot introduces two more potential EFs: symmetry and linearity; a fourth dot produces surroundedness. This hierarchy may extend to collinearity, parallelism, closure, and more. We use the magnitude of Configural Superiority Effects to measure the salience of EFs on a common scale, potentially letting us compare the strengths of various grouping principles. TBG appears promising, with our initial experiments establishing and quantifying at least three basic EFs in human vision.

Many roads to synchrony: natural time scales and their algorithms.

PubMed

James, Ryan G; Mahoney, John R; Ellison, Christopher J; Crutchfield, James P

2014-04-01

We consider two important time scales-the Markov and cryptic orders-that monitor how an observer synchronizes to a finitary stochastic process. We show how to compute these orders exactly and that they are most efficiently calculated from the ε-machine, a process's minimal unifilar model. Surprisingly, though the Markov order is a basic concept from stochastic process theory, it is not a probabilistic property of a process. Rather, it is a topological property and, moreover, it is not computable from any finite-state model other than the ε-machine. Via an exhaustive survey, we close by demonstrating that infinite Markov and infinite cryptic orders are a dominant feature in the space of finite-memory processes. We draw out the roles played in statistical mechanical spin systems by these two complementary length scales.

The role of the airline transportation network in the prediction and predictability of global epidemics.

PubMed

Colizza, Vittoria; Barrat, Alain; Barthélemy, Marc; Vespignani, Alessandro

2006-02-14

The systematic study of large-scale networks has unveiled the ubiquitous presence of connectivity patterns characterized by large-scale heterogeneities and unbounded statistical fluctuations. These features affect dramatically the behavior of the diffusion processes occurring on networks, determining the ensuing statistical properties of their evolution pattern and dynamics. In this article, we present a stochastic computational framework for the forecast of global epidemics that considers the complete worldwide air travel infrastructure complemented with census population data. We address two basic issues in global epidemic modeling: (i) we study the role of the large scale properties of the airline transportation network in determining the global diffusion pattern of emerging diseases; and (ii) we evaluate the reliability of forecasts and outbreak scenarios with respect to the intrinsic stochasticity of disease transmission and traffic flows. To address these issues we define a set of quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern. These measures may be used for the analysis of containment policies and epidemic risk assessment.

Toward automated classification of consumers' cancer-related questions with a new taxonomy of expected answer types.

PubMed

McRoy, Susan; Jones, Sean; Kurmally, Adam

2016-09-01

This article examines methods for automated question classification applied to cancer-related questions that people have asked on the web. This work is part of a broader effort to provide automated question answering for health education. We created a new corpus of consumer-health questions related to cancer and a new taxonomy for those questions. We then compared the effectiveness of different statistical methods for developing classifiers, including weighted classification and resampling. Basic methods for building classifiers were limited by the high variability in the natural distribution of questions and typical refinement approaches of feature selection and merging categories achieved only small improvements to classifier accuracy. Best performance was achieved using weighted classification and resampling methods, the latter yielding an accuracy of F1 = 0.963. Thus, it would appear that statistical classifiers can be trained on natural data, but only if natural distributions of classes are smoothed. Such classifiers would be useful for automated question answering, for enriching web-based content, or assisting clinical professionals to answer questions. © The Author(s) 2015.

Statistical Analysis of Bus Networks in India

PubMed Central

2016-01-01

In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590

Moderate point: Balanced entropy and enthalpy contributions in soft matter

NASA Astrophysics Data System (ADS)

He, Baoji; Wang, Yanting

2017-03-01

Various soft materials share some common features, such as significant entropic effect, large fluctuations, sensitivity to thermodynamic conditions, and mesoscopic characteristic spatial and temporal scales. However, no quantitative definitions have yet been provided for soft matter, and the intrinsic mechanisms leading to their common features are unclear. In this work, from the viewpoint of statistical mechanics, we show that soft matter works in the vicinity of a specific thermodynamic state named moderate point, at which entropy and enthalpy contributions among substates along a certain order parameter are well balanced or have a minimal difference. Around the moderate point, the order parameter fluctuation, the associated response function, and the spatial correlation length maximize, which explains the large fluctuation, the sensitivity to thermodynamic conditions, and mesoscopic spatial and temporal scales of soft matter, respectively. Possible applications to switching chemical bonds or allosteric biomachines determining their best working temperatures are also briefly discussed. Project supported by the National Basic Research Program of China (Grant No. 2013CB932804) and the National Natural Science Foundation of China (Grant Nos. 11274319 and 11421063).

CADDIS Volume 4. Data Analysis: Basic Principles & Issues

EPA Pesticide Factsheets

Use of inferential statistics in causal analysis, introduction to data independence and autocorrelation, methods to identifying and control for confounding variables, references for the Basic Principles section of Data Analysis.

Examining the effect of self-explanation on cognitive integration of basic and clinical sciences in novices.

PubMed

Lisk, Kristina; Agur, Anne M R; Woods, Nicole N

2017-12-01

Several studies have shown that cognitive integration of basic and clinical sciences supports diagnostic reasoning in novices; however, there has been limited exploration of the ways in which educators can translate this model of mental activity into sound instructional strategies. The use of self-explanation during learning has the potential to promote and support the development of integrated knowledge by encouraging novices to elaborate on the causal relationship between clinical features and basic science mechanisms. To explore the effect of this strategy, we compared diagnostic efficacy of teaching students (n = 71) the clinical features of four musculoskeletal pathologies using either (1) integrated causal basic science descriptions (BaSci group); (2) integrated causal basic science descriptions combined with self-explanation prompts (SE group); (3) basic science mechanisms segregated from the clinical features (SG group). All participants completed a diagnostic accuracy test immediately after learning and 1-week later. The results showed that the BaSci group performed significantly better compared to the SE (p = 0.019) and SG groups (p = 0.004); however, no difference was observed between the SE and SG groups (p = 0.91). We hypothesize that the structure of the self-explanation task may not have supported the development of a holistic conceptual understanding of each disease. These findings suggest that integration strategies need to be carefully structured and applied in ways that support the holistic story created by integrated basic science instruction in order to foster conceptual coherence and to capitalize on the benefits of cognition integration.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Are We Able to Pass the Mission of Statistics to Students?

ERIC Educational Resources Information Center

Hindls, Richard; Hronová, Stanislava

2015-01-01

The article illustrates our long term experience in teaching statistics for non-statisticians, especially for students of economics and humanities. The article is focused on some problems of the basic course that can weaken the interest in statistics or lead to false use of statistic methods.

Conceptual Hierarchies in a Flat Attractor Network

PubMed Central

O’Connor, Christopher M.; Cree, George S.; McRae, Ken

2009-01-01

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory. PMID:19543434

[Effects of Self-directed Feedback Practice using Smartphone Videos on Basic Nursing Skills, Confidence in Performance and Learning Satisfaction].

PubMed

Lee, Seul Gi; Shin, Yun Hee

2016-04-01

This study was done to verify effects of a self-directed feedback practice using smartphone videos on nursing students' basic nursing skills, confidence in performance and learning satisfaction. In this study an experimental study with a post-test only control group design was used. Twenty-nine students were assigned to the experimental group and 29 to the control group. Experimental treatment was exchanging feedback on deficiencies through smartphone recorded videos of nursing practice process taken by peers during self-directed practice. Basic nursing skills scores were higher for all items in the experimental group compared to the control group, and differences were statistically significant ["Measuring vital signs" (t=-2.10, p=.039); "Wearing protective equipment when entering and exiting the quarantine room and the management of waste materials" (t=-4.74, p<.001) "Gavage tube feeding" (t=-2.70, p=.009)]. Confidence in performance was higher in the experimental group compared to the control group, but the differences were not statistically significant. However, after the complete practice, there was a statistically significant difference in overall performance confidence (t=-3.07. p=.003). Learning satisfaction was higher in the experimental group compared to the control group, but the difference was not statistically significant (t=-1.67, p=.100). Results of this study indicate that self-directed feedback practice using smartphone videos can improve basic nursing skills. The significance is that it can help nursing students gain confidence in their nursing skills for the future through improvement of basic nursing skills and performance of quality care, thus providing patients with safer care.

Provision of Pre-Primary Education as a Basic Right in Tanzania: Reflections from Policy Documents

ERIC Educational Resources Information Center

Mtahabwa, Lyabwene

2010-01-01

This study sought to assess provision of pre-primary education in Tanzania as a basic right through analyses of relevant policy documents. Documents which were published over the past decade were considered, including educational policies, action plans, national papers, the "Basic Education Statistics in Tanzania" documents, strategy…

Chinese lexical networks: The structure, function and formation

NASA Astrophysics Data System (ADS)

Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

2012-11-01

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

An Independent Evaluation of the Technical Features of the Basic Reading Inventory

ERIC Educational Resources Information Center

Bieber, Gregg; Hulac, David M.; Schweinle, William

2015-01-01

The present study investigated some psychometric properties of the Basic Reading Inventory (BRI), a widely used informal reading inventory. The BRI and Dynamic Indicators of Basic Early Literacy Skills (DIBELS) probes were administered to 149 third, fourth, and fifth graders. Test--retest and alternate forms reliability analyses indicated adequate…

A crash course on data analysis in asteroseismology

NASA Astrophysics Data System (ADS)

Appourchaux, Thierry

2014-02-01

In this course, I try to provide a few basics required for performing data analysis in asteroseismology. First, I address how one can properly treat times series: the sampling, the filtering effect, the use of Fourier transform, the associated statistics. Second, I address how one can apply statistics for decision making and for parameter estimation either in a frequentist of a Bayesian framework. Last, I review how these basic principle have been applied (or not) in asteroseismology.

Writing a Scientific Paper II. Communication by Graphics

NASA Astrophysics Data System (ADS)

Sterken, C.

2011-07-01

This paper discusses facets of visual communication by way of images, graphs, diagrams and tabular material. Design types and elements of graphical images are presented, along with advice on how to create graphs, and on how to read graphical illustrations. This is done in astronomical context, using case studies and historical examples of good and bad graphics. Design types of graphs (scatter and vector plots, histograms, pie charts, ternary diagrams and three-dimensional surface graphs) are explicated, as well as the major components of graphical images (axes, legends, textual parts, etc.). The basic features of computer graphics (image resolution, vector images, bitmaps, graphical file formats and file conversions) are explained, as well as concepts of color models and of color spaces (with emphasis on aspects of readability of color graphics by viewers suffering from color-vision deficiencies). Special attention is given to the verity of graphical content, and to misrepresentations and errors in graphics and associated basic statistics. Dangers of dot joining and curve fitting are discussed, with emphasis on the perception of linearity, the issue of nonsense correlations, and the handling of outliers. Finally, the distinction between data, fits and models is illustrated.

An Integrated Intranet and Dynamic Database Application for the Security Manager at Naval Postgraduate School

DTIC Science & Technology

2002-09-01

Basic for Applications ( VBA ) 6.0 as macros may not be supported in 8 future versions of Access. Access 2000 offers Internet- related features for...security features from Microsoft’s SQL Server. [1] 3. System Requirements Access 2000 is a resource-intensive application as are all Office 2000...1] • Modules – Functions and procedures written in the Visual Basic for Applications ( VBA ) programming language. The capabilities of modules

On Ruch's Principle of Decreasing Mixing Distance in classical statistical physics

NASA Astrophysics Data System (ADS)

Busch, Paul; Quadt, Ralf

1990-10-01

Ruch's Principle of Decreasing Mixing Distance is reviewed as a statistical physical principle and its basic suport and geometric interpretation, the Ruch-Schranner-Seligman theorem, is generalized to be applicable to a large representative class of classical statistical systems.

Acoustics of snoring and automatic snore sound detection in children.

PubMed

Çavuşoğlu, M; Poets, C F; Urschitz, M S

2017-10-31

Acoustic analyses of snoring sounds have been used to objectively assess snoring and applied in various clinical problems for adult patients. Such studies require highly automatized tools to analyze the sound recordings of the whole night's sleep, in order to extract clinically relevant snore- related statistics. The existing techniques and software used for adults are not efficiently applicable to snoring sounds in children, basically because of different acoustic signal properties. In this paper, we present a broad range of acoustic characteristics of snoring sounds in children (N  =  38) in comparison to adult (N  =  30) patients. Acoustic characteristics of the signals were calculated, including frequency domain representations, spectrogram-based characteristics, spectral envelope analysis, formant structures and loudness of the snoring sounds. We observed significant differences in spectral features, formant structures and loudness of the snoring signals of children compared to adults that may arise from the diversity of the upper airway anatomy as the principal determinant of the snore sound generation mechanism. Furthermore, based on the specific audio features of snoring children, we proposed a novel algorithm for the automatic detection of snoring sounds from ambient acoustic data specifically in a pediatric population. The respiratory sounds were recorded using a pair of microphones and a multi-channel data acquisition system simultaneously with full-night polysomnography during sleep. Brief sound chunks of 0.5 s were classified as either belonging to a snoring event or not with a multi-layer perceptron, which was trained in a supervised fashion using stochastic gradient descent on a large hand-labeled dataset using frequency domain features. The method proposed here has been used to extract snore-related statistics that can be calculated from the detected snore episodes for the whole night's sleep, including number of snore episodes (total snoring time), ratio of snore to whole sleep time, variation of snoring rate, regularity of snoring episodes in time and amplitude and snore loudness. These statistics will ultimately serve as a clinical tool providing information for the objective evaluation of snoring for several clinical applications.

Dose fractionation theorem in 3-D reconstruction (tomography)

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

Glaeser, R.M.

It is commonly assumed that the large number of projections for single-axis tomography precludes its application to most beam-labile specimens. However, Hegerl and Hoppe have pointed out that the total dose required to achieve statistical significance for each voxel of a computed 3-D reconstruction is the same as that required to obtain a single 2-D image of that isolated voxel, at the same level of statistical significance. Thus a statistically significant 3-D image can be computed from statistically insignificant projections, as along as the total dosage that is distributed among these projections is high enough that it would have resultedmore » in a statistically significant projection, if applied to only one image. We have tested this critical theorem by simulating the tomographic reconstruction of a realistic 3-D model created from an electron micrograph. The simulations verify the basic conclusions of high absorption, signal-dependent noise, varying specimen contrast and missing angular range. Furthermore, the simulations demonstrate that individual projections in the series of fractionated-dose images can be aligned by cross-correlation because they contain significant information derived from the summation of features from different depths in the structure. This latter information is generally not useful for structural interpretation prior to 3-D reconstruction, owing to the complexity of most specimens investigated by single-axis tomography. These results, in combination with dose estimates for imaging single voxels and measurements of radiation damage in the electron microscope, demonstrate that it is feasible to use single-axis tomography with soft X-ray microscopy of frozen-hydrated specimens.« less

Center for Prostate Disease Research

MedlinePlus

... 2017 Cancer Statistics programs Clinical Research Program Synopsis Leadership Multi-Disciplinary Clinic Staff Listing 2017 Cancer Statistics Basic Science Research Program Synopsis Leadership Gene Expression Data Research Achievements Staff Listing Lab ...

Basic Aerospace Education Library

ERIC Educational Resources Information Center

Journal of Aerospace Education, 1975

1975-01-01

Lists the most significant resource items on aerospace education which are presently available. Includes source books, bibliographies, directories, encyclopedias, dictionaries, audiovisuals, curriculum/planning guides, aerospace statistics, aerospace education statistics and newsletters. (BR)

Multiple-solution problems in a statistics classroom: an example

NASA Astrophysics Data System (ADS)

Chu, Chi Wing; Chan, Kevin L. T.; Chan, Wai-Sum; Kwong, Koon-Shing

2017-11-01

The mathematics education literature shows that encouraging students to develop multiple solutions for given problems has a positive effect on students' understanding and creativity. In this paper, we present an example of multiple-solution problems in statistics involving a set of non-traditional dice. In particular, we consider the exact probability mass distribution for the sum of face values. Four different ways of solving the problem are discussed. The solutions span various basic concepts in different mathematical disciplines (sample space in probability theory, the probability generating function in statistics, integer partition in basic combinatorics and individual risk model in actuarial science) and thus promotes upper undergraduate students' awareness of knowledge connections between their courses. All solutions of the example are implemented using the R statistical software package.

Do smokers want to know more about the cigarettes they smoke? Results from the EDUCATE study.

PubMed

Bansal, Maansi A; Cummings, K Michael; Hyland, Andrew; Bauer, Joseph E; Hastrup, Janice L; Steger, Craig

2004-12-01

The present study (a) assessed smokers' receptivity to receiving information about the product features of their cigarette brand, (b) tested whether the use of targeted (personalized), brand-specific information affected participants' attention to the information, and (c) tested whether attention to the targeted information affected participants' beliefs about the product features and their smoking behavior. The study population included current cigarette smokers who called the New York State Smokers' Quit Line seeking assistance to stop smoking in February and March 2003. Subjects were randomized to one of three experimental groups. Group 1 received telephone counseling and the quit line's stop-smoking booklet, which included information on ingredients found in cigarettes. Group 2 received the same intervention as Group 1 plus a basic brochure with a generic cover. Group 3 received the same intervention as Group 2 except that the cover to the brochure was targeted to individual cigarette brand and type. All smokers who called the quit line were receptive to receiving information about their cigarette brand. In a 6-week follow-up interview, 60% of those who received the targeted product information brochure recalled receiving it vs. 51% of those who received the identical guide with the nontargeted cover. Recall of the material discussed in the brochure was slightly higher (not statistically significant) among subjects who received the brochure with the targeted cover compared with the same brochure with a basic cover. Regardless of whether the brochure was targeted, smokers' beliefs about different product features or their smoking behavior were not affected measurably, although those who reported reading some or all of the brochure had higher levels of awareness regarding low-tar, filtered, and no-additive cigarettes. Smokers are receptive to receiving information about their cigarette brand, but either persistent efforts or possibly more potent interventions to personalize the information are needed to ensure that they recall information about the cigarette brand they smoke.

Feature Statistics Modulate the Activation of Meaning during Spoken Word Processing

ERIC Educational Resources Information Center

Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.

2016-01-01

Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in ("distinctiveness/sharedness") and likelihood of co-occurrence ("correlational…

Statistical and Measurement Properties of Features Used in Essay Assessment. Research Report. ETS RR-04-21

ERIC Educational Resources Information Center

Haberman, Shelby J.

2004-01-01

Statistical and measurement properties are examined for features used in essay assessment to determine the generalizability of the features across populations, prompts, and individuals. Data are employed from TOEFL® and GMAT® examinations and from writing for Criterion?.

Statistical classification approach to discrimination between weak earthquakes and quarry blasts recorded by the Israel Seismic Network

NASA Astrophysics Data System (ADS)

Kushnir, A. F.; Troitsky, E. V.; Haikin, L. M.; Dainty, A.

1999-06-01

A semi-automatic procedure has been developed to achieve statistically optimum discrimination between earthquakes and explosions at local or regional distances based on a learning set specific to a given region. The method is used for step-by-step testing of candidate discrimination features to find the optimum (combination) subset of features, with the decision taken on a rigorous statistical basis. Linear (LDF) and Quadratic (QDF) Discriminant Functions based on Gaussian distributions of the discrimination features are implemented and statistically grounded; the features may be transformed by the Box-Cox transformation z=(1/ α)( yα-1) to make them more Gaussian. Tests of the method were successfully conducted on seismograms from the Israel Seismic Network using features consisting of spectral ratios between and within phases. Results showed that the QDF was more effective than the LDF and required five features out of 18 candidates for the optimum set. It was found that discrimination improved with increasing distance within the local range, and that eliminating transformation of the features and failing to correct for noise led to degradation of discrimination.

The Basic/Essential Skills Taxonomy. Second Edition--Revised.

ERIC Educational Resources Information Center

Snyder, Lester M., Jr.

This revision of the "Basic/Essential Skills Taxonomy" exhibits changes based on use of the original taxonomy in the field. It features more precise definitions of the levels of key words and phrases, the deletion of some science items that ranged above basic skills, the combination of the language arts sections from the original two parts, and…

Texture Classification by Texton: Statistical versus Binary

PubMed Central

Guo, Zhenhua; Zhang, Zhongcheng; Li, Xiu; Li, Qin; You, Jane

2014-01-01

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. PMID:24520346

The Statistical Power of Planned Comparisons.

ERIC Educational Resources Information Center

Benton, Roberta L.

Basic principles underlying statistical power are examined; and issues pertaining to effect size, sample size, error variance, and significance level are highlighted via the use of specific hypothetical examples. Analysis of variance (ANOVA) and related methods remain popular, although other procedures sometimes have more statistical power against…

Identification of natural images and computer-generated graphics based on statistical and textural features.

PubMed

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Anthropometry of eyelid and orbit in four southern Thailand ethnic groups.

PubMed

Preechawai, Passorn

2011-02-01

To study the basic eyelid and orbital measurement in the four main ethnic groups of southern Thailand. The basic eyelid and orbital surface anatomy of 101 normal subjects aged 20-40 years old were measured in the four ethnic groups of which the majority of people in southern Thailand belong to: Thai, Chinese, Thai-Malay, and Thai-Chinese. Of the 101 subjects, 51 were male and 50 were female. Each ethnic group had at least 12 normal subjects. Male-female data were analyzed separately and compared between groups. The palpebral fissure heights in Thai, Chinese, Thai-Malay, and Thai-Chinese males were 9.5, 9.0, 10.2 and 9.6 mm respectively, which demonstrated statistically significant differences between Thai-Malay versus Thai, and Thai-Malay versus Chinese. The palpebral fissure lengths were 30.4, 29.8, 30.5 and 30.5 mm, but without statistically significant differences. The marginal reflex distances were 3.2, 2.8, 3.7 and 3.1 mm respectively with a statistically significant difference only between Thai-Malay versus Chinese. The levator functions were 15.2, 15.2, 15.3 and 15.2 mm. The upper lid creases were 7.1, 4.0, 6.6, and 4.4 mm, statistically significantly different in Thai versus Chinese, Thai versus Thai-Chinese and Chinese versus Thai-Malay. The Hertel exophthalmometer measurements were 15.4, 16.3, 16.6 and 15.9 mm without statistically significant differences. The female measurements were overall similar to the male measurements, with some parallel differences between the groups. The eyebrow position in this age group was mostly at and above the orbital rim in both genders and all ethnic groups. An absence of upper lid crease and an epicanthal fold were found in significantly greater numbers in the Chinese group compared to the others, while parallel lid crease was significantly found in greater numbers in the Thai-Malay group than in the others. Different eyelid characteristics in diferent ethnic groups are an important feature to note when planning for eyelid surgery. As there is a wide range of ethnic groups in Asia, with many differences in eyelid characteristics, it is important for the ophthalmologist to be aware of and understanding these anatomical variations in clinical assessment and treatment in Asians.

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

Berres, Anne Sabine

This slide presentation describes basic topological concepts, including topological spaces, homeomorphisms, homotopy, betti numbers. Scalar field topology explores finding topological features and scalar field visualization, and vector field topology explores finding topological features and vector field visualization.

Atlas of Radiographic Features of Osteoarthritis of the Ankle and Hindfoot

PubMed Central

Kraus, Virginia Byers; Kilfoil, Terrence M; Hash, Thomas W.; McDaniel, Gary; Renner, Jordan B; Carrino, John A.; Adams, Samuel

2015-01-01

Objective To develop a radiographic atlas of osteoarthritis (OA) for use as a template and guide for standardized scoring of radiographic features of OA of the ankle and hindfoot joints. Method Under Institutional Review Board approval, ankle and hindfoot images were selected from a cohort study and from among cases that underwent ankle radiography during a 6-month period at Duke University Medical Center. Missing OA pathology was obtained through supplementation of cases with the assistance of a foot and ankle specialist in Orthopaedic surgery and a musculoskeletal radiologist. Images were obtained and reviewed without patient identifying information. Images went through multiple rounds of review and final images were selected by consensus of the study team. For intra-rater and inter-rater reliability, the kappa statistic was calculated for two readings by 3 musculoskeletal radiologists, a minimum of two weeks apart, of ankle and hindfoot radiographs from 30 anonymized subjects. Results The atlas demonstrates individual radiographic features (osteophyte and joint space narrowing) and Kellgren Lawrence grade for all aspects of the talocrural (ankle joint proper) and talocalcaneal (subtalar) joints. Reliability of scoring based on the atlas was quite good to excellent for most features indicated. Additional examples of ankle joint findings are illustrated including sclerosis, os trigonum, subchondral cysts and talar tilt. Conclusions It is anticipated that this atlas will assist with standardization of scoring of ankle and hindfoot OA by basic and clinical OA researchers. PMID:26318654

Atlas of radiographic features of osteoarthritis of the ankle and hindfoot.

PubMed

Kraus, V B; Kilfoil, T M; Hash, T W; McDaniel, G; Renner, J B; Carrino, J A; Adams, S

2015-12-01

To develop a radiographic atlas of osteoarthritis (OA) for use as a template and guide for standardized scoring of radiographic features of OA of the ankle and hindfoot joints. Under Institutional Review Board approval, ankle and hindfoot images were selected from a cohort study and from among cases that underwent ankle radiography during a 6-month period at Duke University Medical Center. Missing OA pathology was obtained through supplementation of cases with the assistance of a foot and ankle specialist in Orthopaedic surgery and a musculoskeletal radiologist. Images were obtained and reviewed without patient identifying information. Images went through multiple rounds of review and final images were selected by consensus of the study team. For intra-rater and inter-rater reliability, the kappa statistic was calculated for two readings by three musculoskeletal radiologists, a minimum of two weeks apart, of ankle and hindfoot radiographs from 30 anonymized subjects. The atlas demonstrates individual radiographic features (osteophyte and joint space narrowing (JSN)) and Kellgren-Lawrence grade for all aspects of the talocrural (ankle joint proper) and talocalcaneal (subtalar) joints. Reliability of scoring based on the atlas was quite good to excellent for most features indicated. Additional examples of ankle joint findings are illustrated including sclerosis, os trigonum, subchondral cysts and talar tilt. It is anticipated that this atlas will assist with standardization of scoring of ankle and hindfoot OA by basic and clinical OA researchers. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Breast Cancer Basics and You

MedlinePlus

... page please turn JavaScript on. Feature: Screening For Breast Cancer Breast Cancer Basics and You Past Issues / Summer 2014 Table ... more than 232,670 new cases of female breast cancer in the United States in 2014. More than ...

The basic features of a closed fuel cycle without fast reactors

NASA Astrophysics Data System (ADS)

Bobrov, E. A.; Alekseev, P. N.; Teplov, P. S.

2017-01-01

In this paper the basic features of a closed fuel cycle with thermal reactors are considered. The three variants of multiple Pu and U recycling in VVER reactors was investigated. The comparison of MOX and REMIX fuel approaches for closed fuel cycle with thermal reactors is presented. All variants make possible to recycle several times the total amount of Pu and U obtained from spent fuel. The reported study was funded by RFBR according to the research project № 16-38-00021

Basic Radar Altimetry Toolbox: tools to teach altimetry for ocean

NASA Astrophysics Data System (ADS)

Rosmorduc, Vinca; Benveniste, Jerome; Bronner, Emilie; Niemeijer, Sander; Lucas, Bruno Manuel; Dinardo, Salvatore

2013-04-01

The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data, including the next mission to be launched, CryoSat. It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. More than 2000 people downloaded it (January 2013), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 and 3. Others are in discussion for the future, including addition of the future Sentinel-3. The Basic Radar Altimetry Toolbox is able: - to read most distributed radar altimetry data, including the one from future missions like Saral, - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways, including as an educational tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. Example from education uses will be presented, and feedback from those who used it as such will be most welcome. BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/

29 CFR 1904.42 - Requests from the Bureau of Labor Statistics for data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Requests from the Bureau of Labor Statistics for data. 1904... Statistics for data. (a) Basic requirement. If you receive a Survey of Occupational Injuries and Illnesses Form from the Bureau of Labor Statistics (BLS), or a BLS designee, you must promptly complete the form...

78 FR 34101 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... and basic descriptive statistics on the quantity and type of consumer-reported patient safety events... conduct correlations, cross tabulations of responses and other statistical analysis. Estimated Annual...

Hit rates and radiation doses to nuclei of bone lining cells from alpha-particle-emitting radionuclides

NASA Technical Reports Server (NTRS)

Polig, E.; Jee, W. S.; Kruglikov, I. L.

1992-01-01

Factors relating the local concentration of a bone-seeking alpha-particle emitter to the mean hit rate have been determined for nuclei of bone lining cells using a Monte Carlo procedure. Cell nuclei were approximated by oblate spheroids with dimensions and location taken from a previous histomorphometric study. The Monte Carlo simulation is applicable for planar and diffuse labels at plane or cylindrical bone surfaces. Additionally, the mean nuclear dose per hit, the dose mean per hit, the mean track segment length and its second moment, the percentage of stoppers, and the frequency distribution of the dose have been determined. Some basic features of the hit statistics for bone lining cells have been outlined, and the consequences of existing standards of radiation protection with regard to the hit frequency to cell nuclei are discussed.

Empirical analysis of individual popularity and activity on an online music service system

NASA Astrophysics Data System (ADS)

Hu, Hai-Bo; Han, Ding-Yi

2008-10-01

Quantitative understanding of human behaviors supplies basic comprehension of the dynamics of many socio-economic systems. Based on the log data of an online music service system, we investigate the statistical characteristics of individual activity and popularity, and find that the distributions of both of them follow a stretched exponential form which interpolates between exponential and power law distribution. We also study the human dynamics on the online system and find that the distribution of interevent time between two consecutive listenings of music shows the fat tail feature. Besides, with the reduction of user activity the fat tail becomes more and more irregular, indicating different behavior patterns for users with diverse activities. The research results may shed some light on the in-depth understanding of collective behaviors in socio-economic systems.

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.

Financial statistics for public health dispensary decisions in Nigeria: insights on standard presentation typologies.

PubMed

Agundu, Prince Umor C

2003-01-01

Public health dispensaries in Nigeria in recent times have demonstrated the poise to boost corporate productivity in the new millennium and to drive the nation closer to concretising the lofty goal of health-for-all. This is very pronounced considering the face-lift giving to the physical environment, increase in the recruitment and development of professionals, and upward review of financial subventions. However, there is little or no emphasis on basic statistical appreciation/application which enhances the decision making ability of corporate executives. This study used the responses from 120 senior public health officials in Nigeria and analyzed them with chi-square statistical technique. The results established low statistical aptitude, inadequate statistical training programmes, little/no emphasis on statistical literacy compared to computer literacy, amongst others. Consequently, it was recommended that these lapses be promptly addressed to enhance official executive performance in the establishments. Basic statistical data presentation typologies have been articulated in this study to serve as first-aid instructions to the target group, as they represent the contributions of eminent scholars in this area of intellectualism.

Strategy for Promoting the Equitable Development of Basic Education in Underdeveloped Counties as Seen from Cili County

ERIC Educational Resources Information Center

Shihua, Peng; Rihui, Tan

2009-01-01

Employing statistical analysis, this study has made a preliminary exploration of promoting the equitable development of basic education in underdeveloped counties through the case study of Cili county. The unequally developed basic education in the county has been made clear, the reasons for the inequitable education have been analyzed, and,…

Basic Investigations for Remote Sensing of Coastal Areas.

DTIC Science & Technology

for the delineation and analysis of bottom features in coastal areas. The focus is on the development of remote sensing techniques for delineating and classifying bottom features in the nearshore zone.

Feature maps driven no-reference image quality prediction of authentically distorted images

NASA Astrophysics Data System (ADS)

Ghadiyaram, Deepti; Bovik, Alan C.

2015-03-01

Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

Schizophrenia classification using functional network features

NASA Astrophysics Data System (ADS)

Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

2012-03-01

This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

Educating the Educator: U.S. Government Statistical Sources for Geographic Research and Teaching.

ERIC Educational Resources Information Center

Fryman, James F.; Wilkinson, Patrick J.

Appropriate for college geography students and researchers, this paper briefly introduces basic federal statistical publications and corresponding finding aids. General references include "Statistical Abstract of the United States," and three complementary publications: "County and City Data Book,""State and Metropolitan Area Data Book," and…

Statistical Cost Estimation in Higher Education: Some Alternatives.

ERIC Educational Resources Information Center

Brinkman, Paul T.; Niwa, Shelley

Recent developments in econometrics that are relevant to the task of estimating costs in higher education are reviewed. The relative effectiveness of alternative statistical procedures for estimating costs are also tested. Statistical cost estimation involves three basic parts: a model, a data set, and an estimation procedure. Actual data are used…

Statistical Significance Testing in Second Language Research: Basic Problems and Suggestions for Reform

ERIC Educational Resources Information Center

Norris, John M.

2015-01-01

Traditions of statistical significance testing in second language (L2) quantitative research are strongly entrenched in how researchers design studies, select analyses, and interpret results. However, statistical significance tests using "p" values are commonly misinterpreted by researchers, reviewers, readers, and others, leading to…

Ethical Statistics and Statistical Ethics: Making an Interdisciplinary Module

ERIC Educational Resources Information Center

Lesser, Lawrence M.; Nordenhaug, Erik

2004-01-01

This article describes an innovative curriculum module the first author created on the two-way exchange between statistics and applied ethics. The module, having no particular mathematical prerequisites beyond high school algebra, is part of an undergraduate interdisciplinary ethics course which begins with a 3-week introduction to basic applied…

Statistics Canada's Definition and Classification of Postsecondary and Adult Education Providers in Canada. Culture, Tourism and the Centre for Education Statistics. Research Paper. Catalogue no. 81-595-M No. 071

ERIC Educational Resources Information Center

Orton, Larry

2009-01-01

This document outlines the definitions and the typology now used by Statistics Canada's Centre for Education Statistics to identify, classify and delineate the universities, colleges and other providers of postsecondary and adult education in Canada for which basic enrollments, graduates, professors and finance statistics are produced. These new…

Building Capacity for Developing Statistical Literacy in a Developing Country: Lessons Learned from an Intervention

ERIC Educational Resources Information Center

North, Delia; Gal, Iddo; Zewotir, Temesgen

2014-01-01

This paper aims to contribute to the emerging literature on capacity-building in statistics education by examining issues pertaining to the readiness of teachers in a developing country to teach basic statistical topics. The paper reflects on challenges and barriers to building statistics capacity at grass-roots level in a developing country,…

No-reference image quality assessment based on natural scene statistics and gradient magnitude similarity

NASA Astrophysics Data System (ADS)

Jia, Huizhen; Sun, Quansen; Ji, Zexuan; Wang, Tonghan; Chen, Qiang

2014-11-01

The goal of no-reference/blind image quality assessment (NR-IQA) is to devise a perceptual model that can accurately predict the quality of a distorted image as human opinions, in which feature extraction is an important issue. However, the features used in the state-of-the-art "general purpose" NR-IQA algorithms are usually natural scene statistics (NSS) based or are perceptually relevant; therefore, the performance of these models is limited. To further improve the performance of NR-IQA, we propose a general purpose NR-IQA algorithm which combines NSS-based features with perceptually relevant features. The new method extracts features in both the spatial and gradient domains. In the spatial domain, we extract the point-wise statistics for single pixel values which are characterized by a generalized Gaussian distribution model to form the underlying features. In the gradient domain, statistical features based on neighboring gradient magnitude similarity are extracted. Then a mapping is learned to predict quality scores using a support vector regression. The experimental results on the benchmark image databases demonstrate that the proposed algorithm correlates highly with human judgments of quality and leads to significant performance improvements over state-of-the-art methods.

Development of a Rotary Wing Unmanned Aerial Vehicle (UAV) Simulation Model

DTIC Science & Technology

2014-03-01

Features Language URL Autopilot: DIY UAV - 2 DOF proportional controller - Kalman filtering C http://autopilot.sour ceforge.net Paperazzi - 3 DOF...proprtional controller - Basic navigation OCaml http://paparazzi.ena c.fr JSBSim - Basic control system blockset - Sample autopilot

Breast Cancer Basics and You: Introduction | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn Javascript on. Feature: Breast Cancer Breast Cancer Basics and You: Introduction Past Issues / Spring - Summer ... were more than 194,000 new cases of breast cancer in the United States in 2009. More than ...

The Basics of Probiotics | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn JavaScript on. Feature: Probiotics The Basics of Probiotics Past Issues / Winter 2016 Table of Contents Millions ... the facts? Photo courtest of Pixabay What Are Probiotics? Probiotics are live microorganisms (such as bacteria) that ...

Feature-Based Statistical Analysis of Combustion Simulation Data

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

Bennett, J; Krishnamoorthy, V; Liu, S

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing andmore » reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains.« less

County-by-County Financial and Staffing I-M-P-A-C-T. FY 1994-95 Basic Education Program.

ERIC Educational Resources Information Center

North Carolina State Dept. of Public Instruction, Raleigh.

This publication provides the basic statistics needed to illustrate the impact of North Carolina's Basic Education Program (BEP), an educational reform effort begun in 1985. Over 85% of the positions in the BEP are directly related to teaching and student-related activities. The new BEP programs result in smaller class sizes in kindergartens and…

Surface topography characterization of brass alloys: lead brass (CuZn39Pb3) and lead free brass (CuZn21Si3P)

NASA Astrophysics Data System (ADS)

Reddy, Vijeth V.; Vedantha Krishna, Amogh; Schultheiss, Fredrik; Rosén, B.-G.

2017-06-01

Manufactured surfaces usually consist of topographical features which include both those put forth by the manufacturing process, and micro-features caused by disturbances during this process. Surface characterization basically involves study of these features which influence the functionality of the surface. This article focuses on characterization of the surface topography of machined lead brass and lead free brass. The adverse effect of lead on human health and the environment has led the manufacturing sector to focus on sustainable manufacturing of lead free brass, as well as how to maintain control of the surface integrity when substituting the lead content in the brass with silicon. The investigation includes defined areal surface parameters measured on the turned samples of lead- and lead free brass using an optical coherence scanning interferometer, CSI. This paper deals with the study of surface topography of turned samples of lead- and lead free brass. It is important to study the topographical characteristics of the brass samples which are the intermediate link between the manufacturing process variables and the functional behaviour of the surface. To numerically evaluate the sample’s surface topography and to validate the measurements for a significant study, a general statistical methodology is implemented. The results indicate higher surface roughness in turned samples of lead brass compared to lead free brass.

Expression Quantitative Trait Locus Mapping across Water Availability Environments Reveals Contrasting Associations with Genomic Features in Arabidopsis[C][W][OPEN

PubMed Central

Lowry, David B.; Logan, Tierney L.; Santuari, Luca; Hardtke, Christian S.; Richards, James H.; DeRose-Wilson, Leah J.; McKay, John K.; Sen, Saunak; Juenger, Thomas E.

2013-01-01

The regulation of gene expression is crucial for an organism’s development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression. PMID:24045022

A nonstandard finite difference scheme for a basic model of cellular immune response to viral infection

NASA Astrophysics Data System (ADS)

Korpusik, Adam

2017-02-01

We present a nonstandard finite difference scheme for a basic model of cellular immune response to viral infection. The main advantage of this approach is that it preserves the essential qualitative features of the original continuous model (non-negativity and boundedness of the solution, equilibria and their stability conditions), while being easy to implement. All of the qualitative features are preserved independently of the chosen step-size. Numerical simulations of our approach and comparison with other conventional simulation methods are presented.

Breast Cancer Basics and You: Detection and Diagnosis | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn Javascript on. Feature: Breast Cancer Breast Cancer Basics and You: Detection and Diagnosis Past Issues / ... regular clinical breast exams and mammograms to find breast cancer early, when treatment is more likely to work ...

Breast Cancer Basics and You: Staging and Treatment | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn Javascript on. Feature: Breast Cancer Breast Cancer Basics and You: Staging and Treatment Past Issues / ... Table of Contents Staging The extent (stage) of breast cancer needs to be determined to help choose the ...

Universal Entropy of Word Ordering Across Linguistic Families

PubMed Central

Montemurro, Marcelo A.; Zanette, Damián H.

2011-01-01

Background The language faculty is probably the most distinctive feature of our species, and endows us with a unique ability to exchange highly structured information. In written language, information is encoded by the concatenation of basic symbols under grammatical and semantic constraints. As is also the case in other natural information carriers, the resulting symbolic sequences show a delicate balance between order and disorder. That balance is determined by the interplay between the diversity of symbols and by their specific ordering in the sequences. Here we used entropy to quantify the contribution of different organizational levels to the overall statistical structure of language. Methodology/Principal Findings We computed a relative entropy measure to quantify the degree of ordering in word sequences from languages belonging to several linguistic families. While a direct estimation of the overall entropy of language yielded values that varied for the different families considered, the relative entropy quantifying word ordering presented an almost constant value for all those families. Conclusions/Significance Our results indicate that despite the differences in the structure and vocabulary of the languages analyzed, the impact of word ordering in the structure of language is a statistical linguistic universal. PMID:21603637

Nonequilibrium statistical mechanics Brussels-Austin style

NASA Astrophysics Data System (ADS)

Bishop, Robert C.

The fundamental problem on which Ilya Prigogine and the Brussels-Austin Group have focused can be stated briefly as follows. Our observations indicate that there is an arrow of time in our experience of the world (e.g., decay of unstable radioactive atoms like uranium, or the mixing of cream in coffee). Most of the fundamental equations of physics are time reversible, however, presenting an apparent conflict between our theoretical descriptions and experimental observations. Many have thought that the observed arrow of time was either an artifact of our observations or due to very special initial conditions. An alternative approach, followed by the Brussels-Austin Group, is to consider the observed direction of time to be a basic physical phenomenon due to the dynamics of physical systems. This essay focuses mainly on recent developments in the Brussels-Austin Group after the mid-1980s. The fundamental concerns are the same as in their earlier approaches (subdynamics, similarity transformations), but the contemporary approach utilizes rigged Hilbert space (whereas the older approaches used Hilbert space). While the emphasis on nonequilibrium statistical mechanics remains the same, their more recent approach addresses the physical features of large Poincaré systems, nonlinear dynamics and the mathematical tools necessary to analyze them.

Internal representations reveal cultural diversity in expectations of facial expressions of emotion.

PubMed

Jack, Rachael E; Caldara, Roberto; Schyns, Philippe G

2012-02-01

Facial expressions have long been considered the "universal language of emotion." Yet consistent cultural differences in the recognition of facial expressions contradict such notions (e.g., R. E. Jack, C. Blais, C. Scheepers, P. G. Schyns, & R. Caldara, 2009). Rather, culture--as an intricate system of social concepts and beliefs--could generate different expectations (i.e., internal representations) of facial expression signals. To investigate, they used a powerful psychophysical technique (reverse correlation) to estimate the observer-specific internal representations of the 6 basic facial expressions of emotion (i.e., happy, surprise, fear, disgust, anger, and sad) in two culturally distinct groups (i.e., Western Caucasian [WC] and East Asian [EA]). Using complementary statistical image analyses, cultural specificity was directly revealed in these representations. Specifically, whereas WC internal representations predominantly featured the eyebrows and mouth, EA internal representations showed a preference for expressive information in the eye region. Closer inspection of the EA observer preference revealed a surprising feature: changes of gaze direction, shown primarily among the EA group. For the first time, it is revealed directly that culture can finely shape the internal representations of common facial expressions of emotion, challenging notions of a biologically hardwired "universal language of emotion."

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts

PubMed Central

Sugihara, George; Casdagli, Martin; Habjan, Edward; Hess, Dale; Dixon, Paul; Holland, Greg

1999-01-01

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems. PMID:10588685

g:Profiler-a web server for functional interpretation of gene lists (2016 update).

PubMed

Reimand, Jüri; Arak, Tambet; Adler, Priit; Kolberg, Liis; Reisberg, Sulev; Peterson, Hedi; Vilo, Jaak

2016-07-08

Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene function related terms. Translation of hundreds of gene identifiers is another core feature of g:Profiler. Since its first publication in 2007, our web server has become a popular tool of choice among basic and translational researchers. Timeliness is a major advantage of g:Profiler as genome and pathway information is synchronized with the Ensembl database in quarterly updates. g:Profiler supports 213 species including mammals and other vertebrates, plants, insects and fungi. The 2016 update of g:Profiler introduces several novel features. We have added further functional datasets to interpret gene lists, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms. Besides the interactive web interface, g:Profiler can be accessed in computational pipelines using our R package, Python interface and BioJS component. g:Profiler is freely available at http://biit.cs.ut.ee/gprofiler/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

3D Simulation Modeling of the Tooth Wear Process.

PubMed

Dai, Ning; Hu, Jian; Liu, Hao

2015-01-01

Severe tooth wear is the most common non-caries dental disease, and it can seriously affect oral health. Studying the tooth wear process is time-consuming and difficult, and technological tools are frequently lacking. This paper presents a novel method of digital simulation modeling that represents a new way to study tooth wear. First, a feature extraction algorithm is used to obtain anatomical feature points of the tooth without attrition. Second, after the alignment of non-attrition areas, the initial homogeneous surface is generated by means of the RBF (Radial Basic Function) implicit surface and then deformed to the final homogeneous by the contraction and bounding algorithm. Finally, the method of bilinear interpolation based on Laplacian coordinates between tooth with attrition and without attrition is used to inversely reconstruct the sequence of changes of the 3D tooth morphology during gradual tooth wear process. This method can also be used to generate a process simulation of nonlinear tooth wear by means of fitting an attrition curve to the statistical data of attrition index in a certain region. The effectiveness and efficiency of the attrition simulation algorithm are verified through experimental simulation.

3D Simulation Modeling of the Tooth Wear Process

PubMed Central

Dai, Ning; Hu, Jian; Liu, Hao

2015-01-01

Severe tooth wear is the most common non-caries dental disease, and it can seriously affect oral health. Studying the tooth wear process is time-consuming and difficult, and technological tools are frequently lacking. This paper presents a novel method of digital simulation modeling that represents a new way to study tooth wear. First, a feature extraction algorithm is used to obtain anatomical feature points of the tooth without attrition. Second, after the alignment of non-attrition areas, the initial homogeneous surface is generated by means of the RBF (Radial Basic Function) implicit surface and then deformed to the final homogeneous by the contraction and bounding algorithm. Finally, the method of bilinear interpolation based on Laplacian coordinates between tooth with attrition and without attrition is used to inversely reconstruct the sequence of changes of the 3D tooth morphology during gradual tooth wear process. This method can also be used to generate a process simulation of nonlinear tooth wear by means of fitting an attrition curve to the statistical data of attrition index in a certain region. The effectiveness and efficiency of the attrition simulation algorithm are verified through experimental simulation. PMID:26241942

Research of facial feature extraction based on MMC

NASA Astrophysics Data System (ADS)

Xue, Donglin; Zhao, Jiufen; Tang, Qinhong; Shi, Shaokun

2017-07-01

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics

NASA Astrophysics Data System (ADS)

Hartmann, Alexander K.; Weigt, Martin

2005-10-01

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

Financial Statistics. Higher Education General Information Survey (HEGIS) [machine-readable data file].

ERIC Educational Resources Information Center

Center for Education Statistics (ED/OERI), Washington, DC.

The Financial Statistics machine-readable data file (MRDF) is a subfile of the larger Higher Education General Information Survey (HEGIS). It contains basic financial statistics for over 3,000 institutions of higher education in the United States and its territories. The data are arranged sequentially by institution, with institutional…

The Greyhound Strike: Using a Labor Dispute to Teach Descriptive Statistics.

ERIC Educational Resources Information Center

Shatz, Mark A.

1985-01-01

A simulation exercise of a labor-management dispute is used to teach psychology students some of the basics of descriptive statistics. Using comparable data sets generated by the instructor, students work in small groups to develop a statistical presentation that supports their particular position in the dispute. (Author/RM)

Fundamentals of Counting Statistics in Digital PCR: I Just Measured Two Target Copies-What Does It Mean?

PubMed

Tzonev, Svilen

2018-01-01

Current commercially available digital PCR (dPCR) systems and assays are capable of detecting individual target molecules with considerable reliability. As tests are developed and validated for use on clinical samples, the need to understand and develop robust statistical analysis routines increases. This chapter covers the fundamental processes and limitations of detecting and reporting on single molecule detection. We cover the basics of quantification of targets and sources of imprecision. We describe the basic test concepts: sensitivity, specificity, limit of blank, limit of detection, and limit of quantification in the context of dPCR. We provide basic guidelines how to determine those, how to choose and interpret the operating point, and what factors may influence overall test performance in practice.

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

Predicting axillary lymph node metastasis from kinetic statistics of DCE-MRI breast images

NASA Astrophysics Data System (ADS)

Ashraf, Ahmed B.; Lin, Lilie; Gavenonis, Sara C.; Mies, Carolyn; Xanthopoulos, Eric; Kontos, Despina

2012-03-01

The presence of axillary lymph node metastases is the most important prognostic factor in breast cancer and can influence the selection of adjuvant therapy, both chemotherapy and radiotherapy. In this work we present a set of kinetic statistics derived from DCE-MRI for predicting axillary node status. Breast DCE-MRI images from 69 women with known nodal status were analyzed retrospectively under HIPAA and IRB approval. Axillary lymph nodes were positive in 12 patients while 57 patients had no axillary lymph node involvement. Kinetic curves for each pixel were computed and a pixel-wise map of time-to-peak (TTP) was obtained. Pixels were first partitioned according to the similarity of their kinetic behavior, based on TTP values. For every kinetic curve, the following pixel-wise features were computed: peak enhancement (PE), wash-in-slope (WIS), wash-out-slope (WOS). Partition-wise statistics for every feature map were calculated, resulting in a total of 21 kinetic statistic features. ANOVA analysis was done to select features that differ significantly between node positive and node negative women. Using the computed kinetic statistic features a leave-one-out SVM classifier was learned that performs with AUC=0.77 under the ROC curve, outperforming the conventional kinetic measures, including maximum peak enhancement (MPE) and signal enhancement ratio (SER), (AUCs of 0.61 and 0.57 respectively). These findings suggest that our DCE-MRI kinetic statistic features can be used to improve the prediction of axillary node status in breast cancer patients. Such features could ultimately be used as imaging biomarkers to guide personalized treatment choices for women diagnosed with breast cancer.

Random Forest Application for NEXRAD Radar Data Quality Control

NASA Astrophysics Data System (ADS)

Keem, M.; Seo, B. C.; Krajewski, W. F.

2017-12-01

Identification and elimination of non-meteorological radar echoes (e.g., returns from ground, wind turbines, and biological targets) are the basic data quality control steps before radar data use in quantitative applications (e.g., precipitation estimation). Although WSR-88Ds' recent upgrade to dual-polarization has enhanced this quality control and echo classification, there are still challenges to detect some non-meteorological echoes that show precipitation-like characteristics (e.g., wind turbine or anomalous propagation clutter embedded in rain). With this in mind, a new quality control method using Random Forest is proposed in this study. This classification algorithm is known to produce reliable results with less uncertainty. The method introduces randomness into sampling and feature selections and integrates consequent multiple decision trees. The multidimensional structure of the trees can characterize the statistical interactions of involved multiple features in complex situations. The authors explore the performance of Random Forest method for NEXRAD radar data quality control. Training datasets are selected using several clear cases of precipitation and non-precipitation (but with some non-meteorological echoes). The model is structured using available candidate features (from the NEXRAD data) such as horizontal reflectivity, differential reflectivity, differential phase shift, copolar correlation coefficient, and their horizontal textures (e.g., local standard deviation). The influence of each feature on classification results are quantified by variable importance measures that are automatically estimated by the Random Forest algorithm. Therefore, the number and types of features in the final forest can be examined based on the classification accuracy. The authors demonstrate the capability of the proposed approach using several cases ranging from distinct to complex rain/no-rain events and compare the performance with the existing algorithms (e.g., MRMS). They also discuss operational feasibility based on the observed strength and weakness of the method.

Effects of achievement contexts on the meaning structure of emotion words.

PubMed

Gentsch, Kornelia; Loderer, Kristina; Soriano, Cristina; Fontaine, Johnny R J; Eid, Michael; Pekrun, Reinhard; Scherer, Klaus R

2018-03-01

Little is known about the impact of context on the meaning of emotion words. In the present study, we used a semantic profiling instrument (GRID) to investigate features representing five emotion components (appraisal, bodily reaction, expression, action tendencies, and feeling) of 11 emotion words in situational contexts involving success or failure. We compared these to the data from an earlier study in which participants evaluated the typicality of features out of context. Profile analyses identified features for which typicality changed as a function of context for all emotion words, except contentment, with appraisal features being most frequently affected. Those context effects occurred for both hypothesised basic and non-basic emotion words. Moreover, both data sets revealed a four-dimensional structure. The four dimensions were largely similar (valence, power, arousal, and novelty). The results suggest that context may not change the underlying dimensionality but affects facets of the meaning of emotion words.

Nurses' foot care activities in home health care.

PubMed

Stolt, Minna; Suhonen, Riitta; Puukka, Pauli; Viitanen, Matti; Voutilainen, Päivi; Leino-Kilpi, Helena

2013-01-01

This study described the basic foot care activities performed by nurses and factors associated with these in the home care of older people. Data were collected from nurses (n=322) working in nine public home care agencies in Finland using the Nurses' Foot Care Activities Questionnaire (NFAQ). Data were analyzed statistically using descriptive statistics and multivariate liner models. Although some of the basic foot care activities of nurses reported using were outdated, the majority of foot care activities were consistent with recommendations in foot care literature. Longer working experience, referring patients with foot problems to a podiatrist and physiotherapist, and patient education in wart and nail care were associated with a high score for adequate foot care activities. Continuing education should focus on updating basic foot care activities and increasing the use of evidence-based foot care methods. Also, geriatric nursing research should focus in intervention research to improve the use of evidence-based basic foot care activities. Copyright © 2013 Mosby, Inc. All rights reserved.

Linear and Non-linear Information Flows In Rainfall Field

NASA Astrophysics Data System (ADS)

Molini, A.; La Barbera, P.; Lanza, L. G.

The rainfall process is the result of a complex framework of non-linear dynamical in- teractions between the different components of the atmosphere. It preserves the com- plexity and the intermittent features of the generating system in space and time as well as the strong dependence of these properties on the scale of observations. The understanding and quantification of how the non-linearity of the generating process comes to influence the single rain events constitute relevant research issues in the field of hydro-meteorology, especially in those applications where a timely and effective forecasting of heavy rain events is able to reduce the risk of failure. This work focuses on the characterization of the non-linear properties of the observed rain process and on the influence of these features on hydrological models. Among the goals of such a survey is the research of regular structures of the rainfall phenomenon and the study of the information flows within the rain field. The research focuses on three basic evo- lution directions for the system: in time, in space and between the different scales. In fact, the information flows that force the system to evolve represent in general a connection between the different locations in space, the different instants in time and, unless assuming the hypothesis of scale invariance is verified "a priori", the different characteristic scales. A first phase of the analysis is carried out by means of classic statistical methods, then a survey of the information flows within the field is devel- oped by means of techniques borrowed from the Information Theory, and finally an analysis of the rain signal in the time and frequency domains is performed, with par- ticular reference to its intermittent structure. The methods adopted in this last part of the work are both the classic techniques of statistical inference and a few procedures for the detection of non-linear and non-stationary features within the process starting from measured data.

Feature selection from a facial image for distinction of sasang constitution.

PubMed

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun; Kim, Keun Ho

2009-09-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

Feature Selection from a Facial Image for Distinction of Sasang Constitution

PubMed Central

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun

2009-01-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here. PMID:19745013

Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

USGS Publications Warehouse

Rand, R.S.; Clark, R.N.; Livo, K.E.

2011-01-01

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset.

PubMed

Schedl, Markus

2017-01-01

Recently, the LFM-1b dataset has been proposed to foster research and evaluation in music retrieval and music recommender systems, Schedl (Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR). New York, 2016). It contains more than one billion music listening events created by more than 120,000 users of Last.fm. Each listening event is characterized by artist, album, and track name, and further includes a timestamp. Basic demographic information and a selection of more elaborate listener-specific descriptors are included as well, for anonymized users. In this article, we reveal information about LFM-1b's acquisition and content and we compare it to existing datasets. We furthermore provide an extensive statistical analysis of the dataset, including basic properties of the item sets, demographic coverage, distribution of listening events (e.g., over artists and users), and aspects related to music preference and consumption behavior (e.g., temporal features and mainstreaminess of listeners). Exploiting country information of users and genre tags of artists, we also create taste profiles for populations and determine similar and dissimilar countries in terms of their populations' music preferences. Finally, we illustrate the dataset's usage in a simple artist recommendation task, whose results are intended to serve as baseline against which more elaborate techniques can be assessed.

Harmonic analysis of electric locomotive and traction power system based on wavelet singular entropy

NASA Astrophysics Data System (ADS)

Dun, Xiaohong

2018-05-01

With the rapid development of high-speed railway and heavy-haul transport, the locomotive and traction power system has become the main harmonic source of China's power grid. In response to this phenomenon, the system's power quality issues need timely monitoring, assessment and governance. Wavelet singular entropy is an organic combination of wavelet transform, singular value decomposition and information entropy theory, which combines the unique advantages of the three in signal processing: the time-frequency local characteristics of wavelet transform, singular value decomposition explores the basic modal characteristics of data, and information entropy quantifies the feature data. Based on the theory of singular value decomposition, the wavelet coefficient matrix after wavelet transform is decomposed into a series of singular values that can reflect the basic characteristics of the original coefficient matrix. Then the statistical properties of information entropy are used to analyze the uncertainty of the singular value set, so as to give a definite measurement of the complexity of the original signal. It can be said that wavelet entropy has a good application prospect in fault detection, classification and protection. The mat lab simulation shows that the use of wavelet singular entropy on the locomotive and traction power system harmonic analysis is effective.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

A method for automatic feature points extraction of human vertebrae three-dimensional model

NASA Astrophysics Data System (ADS)

Wu, Zhen; Wu, Junsheng

2017-05-01

A method for automatic extraction of the feature points of the human vertebrae three-dimensional model is presented. Firstly, the statistical model of vertebrae feature points is established based on the results of manual vertebrae feature points extraction. Then anatomical axial analysis of the vertebrae model is performed according to the physiological and morphological characteristics of the vertebrae. Using the axial information obtained from the analysis, a projection relationship between the statistical model and the vertebrae model to be extracted is established. According to the projection relationship, the statistical model is matched with the vertebrae model to get the estimated position of the feature point. Finally, by analyzing the curvature in the spherical neighborhood with the estimated position of feature points, the final position of the feature points is obtained. According to the benchmark result on multiple test models, the mean relative errors of feature point positions are less than 5.98%. At more than half of the positions, the error rate is less than 3% and the minimum mean relative error is 0.19%, which verifies the effectiveness of the method.

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

Feature extraction and classification algorithms for high dimensional data

NASA Technical Reports Server (NTRS)

Lee, Chulhee; Landgrebe, David

1993-01-01

Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized. By investigating the characteristics of high dimensional data, the reason why the second order statistics must be taken into account in high dimensional data is suggested. Recognizing the importance of the second order statistics, there is a need to represent the second order statistics. A method to visualize statistics using a color code is proposed. By representing statistics using color coding, one can easily extract and compare the first and the second statistics.

Developing Competency of Teachers in Basic Education Schools

ERIC Educational Resources Information Center

Yuayai, Rerngrit; Chansirisira, Pacharawit; Numnaphol, Kochaporn

2015-01-01

This study aims to develop competency of teachers in basic education schools. The research instruments included the semi-structured in-depth interview form, questionnaire, program developing competency, and evaluation competency form. The statistics used for data analysis were percentage, mean, and standard deviation. The research found that…

Characteristics of Knowledge Interconnectedness in Teaching

ERIC Educational Resources Information Center

Antonijevic, Radovan

2006-01-01

The subject of the paper presents establishing basic characteristics, forms and levels of knowledge interconnectedness in teaching, especially in mathematics and biology teaching. The analysis was realized by considering basic theoretical views in this field, as well as by establishing features and levels of knowledge interconnectedness in the…

Personal Docente del Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Cordoba (Teaching Personnel in Primary Schools. Basic Statistics Series , Level of Education: Cordoba).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working the elementary schools of Cordoba, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Personal Docente des Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Narino (Teaching Personnel in Primary Schools. Basic Statistics Series, Level of Education: Narino).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working in the elementary schools of Narino, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Personal Docente del Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Cauca (Teaching Personnel in Primary Schools. Basic Statistics Series, Level of Education: Cauca).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working in the elementary schools of Cauca, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Personal Docente del Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Caldas (Teaching Personnel in Primary Schools. Basic Statistics Series, Level of Education: Caldas).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working in the elementary schools of Caldas, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Personal Docente del Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Boyaca (Teaching Personnel in Primary Schools. Basic Statistics Series, Level of Education: Boyaca).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working in the elementary schools of Boyaca, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Personal Docente del Nivel Primario. Series Estadisticas Basicas, Nivel Educativo: Huila (Teaching Personnel in Primary Schools. Basic Statistics Series, Level of Education: Huila).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teaching personnel working in the elementary schools of Huila, Colombia, between 1958 and 1967. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of the teachers. For overall statistics in…

Health Resources Statistics; Health Manpower and Health Facilities, 1968. Public Health Service Publication No. 1509.

ERIC Educational Resources Information Center

National Center for Health Statistics (DHEW/PHS), Hyattsville, MD.

This report is a part of the program of the National Center for Health Statistics to provide current statistics as baseline data for the evaluation, planning, and administration of health programs. Part I presents data concerning the occupational fields: (1) administration, (2) anthropology and sociology, (3) data processing, (4) basic sciences,…

Personal Docente del Nivel Primario. Series Estadisticas Basicas: Colombia (Teaching Personnel in Primary Schools. Basic Statistics Series: Colombia).

ERIC Educational Resources Information Center

Ministerio de Educacion Nacional, Bogota (Colombia). Instituto Colombiano de Pedagogia.

This document provides statistical data on the distribution and education of teacher personnel working in Colombian elementary schools between 1940 and 1968. The statistics cover the number of men and women, public and private schools, urban and rural location, and the amount of education of teachers. (VM)

Explorations in Statistics: Standard Deviations and Standard Errors

ERIC Educational Resources Information Center

Curran-Everett, Douglas

2008-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This series in "Advances in Physiology Education" provides an opportunity to do just that: we will investigate basic concepts in statistics using the free software package R. Because this series uses R solely as a vehicle…

The Precision-Power-Gradient Theory for Teaching Basic Research Statistical Tools to Graduate Students.

ERIC Educational Resources Information Center

Cassel, Russell N.

This paper relates educational and psychological statistics to certain "Research Statistical Tools" (RSTs) necessary to accomplish and understand general research in the behavioral sciences. Emphasis is placed on acquiring an effective understanding of the RSTs and to this end they are are ordered to a continuum scale in terms of individual…

Estimates of School Statistics, 1971-72.

ERIC Educational Resources Information Center

Flanigan, Jean M.

This report presents public school statistics for the 50 States, the District of Columbia, and the regions and outlying areas of the United States. The text presents national data for each of the past 10 years and defines the basic series of statistics. Tables present the revised estimates by State and region for 1970-71 and the preliminary…

Combining statistical inference and decisions in ecology

USGS Publications Warehouse

Williams, Perry J.; Hooten, Mevin B.

2016-01-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Effects of atmospheric aerosols on scattering reflected visible light from earth resource features

NASA Technical Reports Server (NTRS)

Noll, K. E.; Tschantz, B. A.; Davis, W. T.

1972-01-01

The vertical variations in atmospheric light attenuation under ambient conditions were identified, and a method through which aerial photographs of earth features might be corrected to yield quantitative information about the actual features was provided. A theoretical equation was developed based on the Bouguer-Lambert extinction law and basic photographic theory.

Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis

PubMed Central

Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

2015-01-01

Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent. PMID:26053876

Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis.

PubMed

Wu, Yazhou; Zhou, Liang; Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

2015-01-01

Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent.

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab’s further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Senior Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section performing bio-statistical design, analysis and reporting of research projects conducted in the lab. This individual will be involved in the implementation of statistical models and data preparation. Successful candidate should have 5 or more years of competent, innovative biostatistics/bioinformatics research experience, beyond doctoral training Considerable experience with statistical software, such as SAS, R and S-Plus Sound knowledge, and demonstrated experience of theoretical and applied statistics Write program code to analyze data using statistical analysis software Contribute to the interpretation and publication of research results

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

Stata companion.

PubMed

Brennan, Jennifer Sousa

2010-01-01

This chapter is an introductory reference guide highlighting some of the most common statistical topics, broken down into both command-line syntax and graphical interface point-and-click commands. This chapter serves to supplement more formal statistics lessons and expedite using Stata to compute basic analyses.

System analysis for the Huntsville Operational Support Center distributed computer system

NASA Technical Reports Server (NTRS)

Ingels, E. M.

1983-01-01

A simulation model was developed and programmed in three languages BASIC, PASCAL, and SLAM. Two of the programs are included in this report, the BASIC and the PASCAL language programs. SLAM is not supported by NASA/MSFC facilities and hence was not included. The statistical comparison of simulations of the same HOSC system configurations are in good agreement and are in agreement with the operational statistics of HOSC that were obtained. Three variations of the most recent HOSC configuration was run and some conclusions drawn as to the system performance under these variations.

Quantum Social Science

NASA Astrophysics Data System (ADS)

Haven, Emmanuel; Khrennikov, Andrei

2013-01-01

Preface; Part I. Physics Concepts in Social Science? A Discussion: 1. Classical, statistical and quantum mechanics: all in one; 2. Econophysics: statistical physics and social science; 3. Quantum social science: a non-mathematical motivation; Part II. Mathematics and Physics Preliminaries: 4. Vector calculus and other mathematical preliminaries; 5. Basic elements of quantum mechanics; 6. Basic elements of Bohmian mechanics; Part III. Quantum Probabilistic Effects in Psychology: Basic Questions and Answers: 7. A brief overview; 8. Interference effects in psychology - an introduction; 9. A quantum-like model of decision making; Part IV. Other Quantum Probabilistic Effects in Economics, Finance and Brain Sciences: 10. Financial/economic theory in crisis; 11. Bohmian mechanics in finance and economics; 12. The Bohm-Vigier Model and path simulation; 13. Other applications to economic/financial theory; 14. The neurophysiological sources of quantum-like processing in the brain; Conclusion; Glossary; Index.

GENASIS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 2)

NASA Astrophysics Data System (ADS)

Cardall, Christian Y.; Budiardja, Reuben D.

2017-05-01

GenASiS Basics provides Fortran 2003 classes furnishing extensible object-oriented utilitarian functionality for large-scale physics simulations on distributed memory supercomputers. This functionality includes physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. This revision -Version 2 of Basics - makes mostly minor additions to functionality and includes some simplifying name changes.

Basic Facts and Figures about the Educational System in Japan.

ERIC Educational Resources Information Center

National Inst. for Educational Research, Tokyo (Japan).

Tables, charts, and graphs convey supporting data that accompany text on various aspects of the Japanese educational system presented in this booklet. There are seven chapters: (1) Fundamental principles of education; (2) Organization of the educational system; (3) Basic statistics of education; (4) Curricula, textbooks, and instructional aids;…

Application of the Recreation Opportunity Spectrum for Outdoor Recreation Planning on Army Installations.

DTIC Science & Technology

1982-03-01

to preference types, and uses capacity estimation; therefore, it is basically a good system for recreation and resource inventory and classification...quan- tity, and distribution of recreational resources. Its basic unit of inventory is landform, or the homogeneity of physical features used to...by Clark and Stankey, "the basic assumption underlying the ROS is that quality recreational experiences are best assured by providing a diverse set of

Cell biology: at the center of modern biomedicine.

PubMed

Budde, Priya Prakash; Williams, Elizabeth H; Misteli, Tom

2012-10-01

How does basic cell biology contribute to biomedicine? A new series of Features in JCB provides a cross section of compelling examples of how basic cell biology findings can lead to therapeutics. These articles highlight the fruitful, essential, and increasingly prominent bridge that exists between cell biology and the clinic.

DEMONSTRATION BULLETIN: THE BASIC EXTRACTIVE SLUDGE TREATMENT (B.E.S.T.) RESOURCES CONSERVATION COMPANY (RCC)

EPA Science Inventory

The Basic Extractive Sludge Treatment (B.E.S.T.®) process is a solvent extraction system that separates organic contaminants from sludges, soils, and sediments. The primary distinguishing feature of the process is the extraction agent, triethylamine. The key to the success of tri...

Annual statistical report 2008 : based on data from CARE/EC

DOT National Transportation Integrated Search

2008-10-31

This Annual Statistical Report provides the basic characteristics of road accidents in 19 member states of : the European Union for the period 1997-2006, on the basis of data collected and processed in the CARE : database, the Community Road Accident...

Country Education Profiles: Algeria.

ERIC Educational Resources Information Center

International Bureau of Education, Geneva (Switzerland).

One of a series of profiles prepared by the Cooperative Educational Abstracting Service, this brief outline provides basic background information on educational principles, system of administration, structure and organization, curricula, and teacher training in Algeria. Statistics provided by the Unesco Office of Statistics show enrollment at all…

78 FR 23158 - Organization and Delegation of Duties

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-18

... management actions of major significance, such as those relating to changes in basic organization pattern... regard to rulemaking, enforcement, vehicle safety research and statistics and data analysis, provides... Administrator for the National Center for Statistics and Analysis, and the Associate Administrator for Vehicle...

A topographic feature taxonomy for a U.S. national topographic mapping ontology

USGS Publications Warehouse

Varanka, Dalia E.

2013-01-01

Using legacy feature lists from the U.S. National Topographic Mapping Program of the twentieth century, a taxonomy of features is presented for purposes of developing a national topographic feature ontology for geographic mapping and analysis. After reviewing published taxonomic classifications, six basic classes are suggested; terrain, surface water, ecological regimes, built-up areas, divisions, and events. Aspects of ontology development are suggested as the taxonomy is described.

When Statistical Literacy Really Matters: Understanding Published Information about the HIV/AIDS Epidemic in South Africa

ERIC Educational Resources Information Center

Hobden, Sally

2014-01-01

Information on the HIV/AIDS epidemic in Southern Africa is often interpreted through a veil of secrecy and shame and, I argue, with flawed understanding of basic statistics. This research determined the levels of statistical literacy evident in 316 future Mathematical Literacy teachers' explanations of the median in the context of HIV/AIDS…

Introduction to Statistics. Learning Packages in the Policy Sciences Series, PS-26. Revised Edition.

ERIC Educational Resources Information Center

Policy Studies Associates, Croton-on-Hudson, NY.

The primary objective of this booklet is to introduce students to basic statistical skills that are useful in the analysis of public policy data. A few, selected statistical methods are presented, and theory is not emphasized. Chapter 1 provides instruction for using tables, bar graphs, bar graphs with grouped data, trend lines, pie diagrams,…

Building a Relationship between Elements of Product Form Features and Vocabulary Assessment Models

ERIC Educational Resources Information Center

Lo, Chi-Hung

2016-01-01

Based on the characteristic feature parameterization and the superiority evaluation method (SEM) in extension engineering, a product-shape design method was proposed in this study. The first step of this method is to decompose the basic feature components of a product. After that, the morphological chart method is used to segregate the ideas so as…

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods

PubMed Central

Hancock, Matthew C.; Magnan, Jerry F.

2016-01-01

Abstract. In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists’ annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (±1.14)%, which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (±0.012), which increases to 0.949 (±0.007) when diameter and volume features are included and has an accuracy of 88.08 (±1.11)%. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification. PMID:27990453

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods.

PubMed

Hancock, Matthew C; Magnan, Jerry F

2016-10-01

In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 [Formula: see text], which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 ([Formula: see text]), which increases to 0.949 ([Formula: see text]) when diameter and volume features are included and has an accuracy of 88.08 [Formula: see text]. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.

Mechanisms of flame stabilisation at low lifted height in a turbulent lifted slot-jet flame

DOE PAGES

Karami, Shahram; Hawkes, Evatt R.; Talei, Mohsen; ...

2015-07-23

A turbulent lifted slot-jet flame is studied using direct numerical simulation (DNS). A one-step chemistry model is employed with a mixture-fraction-dependent activation energy which can reproduce qualitatively the dependence of the laminar burning rate on the equivalence ratio that is typical of hydrocarbon fuels. The basic structure of the flame base is first examined and discussed in the context of earlier experimental studies of lifted flames. Several features previously observed in experiments are noted and clarified. Some other unobserved features are also noted. Comparison with previous DNS modelling of hydrogen flames reveals significant structural differences. The statistics of flow andmore » relative edge-flame propagation velocity components conditioned on the leading edge locations are then examined. The results show that, on average, the streamwise flame propagation and streamwise flow balance, thus demonstrating that edge-flame propagation is the basic stabilisation mechanism. Fluctuations of the edge locations and net edge velocities are, however, significant. It is demonstrated that the edges tend to move in an essentially two-dimensional (2D) elliptical pattern (laterally outwards towards the oxidiser, then upstream, then inwards towards the fuel, then downstream again). It is proposed that this is due to the passage of large eddies, as outlined in Suet al.(Combust. Flame, vol. 144 (3), 2006, pp. 494–512). However, the mechanism is not entirely 2D, and out-of-plane motion is needed to explain how flames escape the high-velocity inner region of the jet. Finally, the time-averaged structure is examined. A budget of terms in the transport equation for the product mass fraction is used to understand the stabilisation from a time-averaged perspective. The result of this analysis is found to be consistent with the instantaneous perspective. The budget reveals a fundamentally 2D structure, involving transport in both the streamwise and transverse directions, as opposed to possible mechanisms involving a dominance of either one direction of transport. Furthermore, it features upstream transport balanced by entrainment into richer conditions, while on the rich side, upstream turbulent transport and entrainment from leaner conditions balance the streamwise convection.« less

75 FR 33203 - Funding Formula for Grants to States

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-11

... as Social Security numbers, birth dates, and medical data. Docket: To read or download submissions or... Local Area Unemployment Statistics (LAUS), both of which are compiled by DOL's Bureau of Labor Statistics. Specifies how each State's basic JVSG allocation is calculated. Identifies the procedures...

Statistical Considerations for Establishing CBTE Cut-Off Scores.

ERIC Educational Resources Information Center

Trzasko, Joseph A.

This report gives the basic definition and purpose of competency-based teacher education (CBTE) cut-off scores. It describes the basic characteristics of CBTE as a yes-no dichotomous decision regarding the presence of a specific ability or knowledge, which necesitates the establishment of a cut-off point to designate competency vs. incompetency on…

ADULT BASIC EDUCATION. PROGRAM SUMMARY.

ERIC Educational Resources Information Center

Office of Education (DHEW), Washington, DC.

A BRIEF DESCRIPTION IS GIVEN OF THE FEDERAL ADULT BASIC EDUCATION PROGRAM, UNDER THE ADULT EDUCATION ACT OF 1966, AT THE NATIONAL AND STATE LEVELS (INCLUDING PUERTO RICO, GUAM, AMERICAN SAMOA, AND THE VIRGIN ISLANDS) AS PROVIDED BY STATE EDUCATION AGENCIES. STATISTICS FOR FISCAL YEARS 1965 AND 1966, AND ESTIMATES FOR FISCAL YEAR 1967, INDICATE…

Action Research of Computer-Assisted-Remediation of Basic Research Concepts.

ERIC Educational Resources Information Center

Packard, Abbot L.; And Others

This study investigated the possibility of creating a computer-assisted remediation program to assist students having difficulties in basic college research and statistics courses. A team approach involving instructors and students drove the research into and creation of the computer program. The effect of student use was reviewed by looking at…

Introduction to Probability, Part 1 - Basic Concepts. Student Text. Revised Edition.

ERIC Educational Resources Information Center

Blakeslee, David W.; And Others

This book is designed to introduce the reader to some fundamental ideas about probability. The mathematical theory of probability plays an increasingly important role in science, government, industry, business, and economics. An understanding of the basic concepts of probability is essential for the study of statistical methods that are widely…

77 FR 37059 - Draft Guidance for Industry on Active Controls in Studies To Demonstrate Effectiveness of a New...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-20

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2012-D-0419... who conduct studies using active controls and have a basic understanding of statistical principles... clinical investigators who conduct studies using active controls and have a basic understanding of...

The influence of somatotype components and personality traits on the playing position and the quality of top Croatian female cadet handball players.

PubMed

Cavala, Marijana; Trninić, Viktorija; Jasić, Dajana; Tomljanović, Mario

2013-05-01

The research was conducted with the aim to establish the structure and the differences of morphological features and personality traits between different age groups of female cadet handball players grouped by their playing quality and playing positions. Further on, the research was done on 70 handball players aged 15, 31 on average, who were grouped according to their positions on goalkeepers, outside players, wings and pivots. Furthermore, according to the quality of playing, they were divided in two quality groups of players, those from the wider cadet national team, thus characterised as top female players in Croatia, and those who had never been invited into the cadet national team and thus can be referred to as low-quality, i.e. average female handball players. The structure of predictor variables has indicated the existence of general morphological factor assessing the players' constitution and two personality features factors - neuroticism and extraversion. The variance analysis showed no statistically significant differences of somatotype variables with relation to quality and playing position. By observing basic personality traits, a statistically significant difference was confirmed only in introversion-extraversion with a lower score in goalkeepers than in other positions, which indicates a higher level of introversion in this playing position. Such result was expected since this particular position abounds in specific tasks and demands in the game in relation to all other playing positions. Further on, it has been concluded that the selection of players must not be based only on the stated physical and psychological characteristics, but on relevant anthropological complexes determining performance and sport achievement.

Multi-view 3D echocardiography compounding based on feature consistency

NASA Astrophysics Data System (ADS)

Yao, Cheng; Simpson, John M.; Schaeffter, Tobias; Penney, Graeme P.

2011-09-01

Echocardiography (echo) is a widely available method to obtain images of the heart; however, echo can suffer due to the presence of artefacts, high noise and a restricted field of view. One method to overcome these limitations is to use multiple images, using the 'best' parts from each image to produce a higher quality 'compounded' image. This paper describes our compounding algorithm which specifically aims to reduce the effect of echo artefacts as well as improving the signal-to-noise ratio, contrast and extending the field of view. Our method weights image information based on a local feature coherence/consistency between all the overlapping images. Validation has been carried out using phantom, volunteer and patient datasets consisting of up to ten multi-view 3D images. Multiple sets of phantom images were acquired, some directly from the phantom surface, and others by imaging through hard and soft tissue mimicking material to degrade the image quality. Our compounding method is compared to the original, uncompounded echocardiography images, and to two basic statistical compounding methods (mean and maximum). Results show that our method is able to take a set of ten images, degraded by soft and hard tissue artefacts, and produce a compounded image of equivalent quality to images acquired directly from the phantom. Our method on phantom, volunteer and patient data achieves almost the same signal-to-noise improvement as the mean method, while simultaneously almost achieving the same contrast improvement as the maximum method. We show a statistically significant improvement in image quality by using an increased number of images (ten compared to five), and visual inspection studies by three clinicians showed very strong preference for our compounded volumes in terms of overall high image quality, large field of view, high endocardial border definition and low cavity noise.

24 CFR 570.201 - Basic eligible activities.

Code of Federal Regulations, 2014 CFR

2014-04-01

... provided for in § 570.207(a)(1).) In undertaking such activities, design features and improvements which... design features, and similar treatments intended to enhance the aesthetic quality of facilities and improvements receiving CDBG assistance, such as decorative pavements, railings, sculptures, pools of water and...

24 CFR 570.201 - Basic eligible activities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... provided for in § 570.207(a)(1).) In undertaking such activities, design features and improvements which... design features, and similar treatments intended to enhance the aesthetic quality of facilities and improvements receiving CDBG assistance, such as decorative pavements, railings, sculptures, pools of water and...

24 CFR 570.201 - Basic eligible activities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... provided for in § 570.207(a)(1).) In undertaking such activities, design features and improvements which... design features, and similar treatments intended to enhance the aesthetic quality of facilities and improvements receiving CDBG assistance, such as decorative pavements, railings, sculptures, pools of water and...

24 CFR 570.201 - Basic eligible activities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... provided for in § 570.207(a)(1).) In undertaking such activities, design features and improvements which... design features, and similar treatments intended to enhance the aesthetic quality of facilities and improvements receiving CDBG assistance, such as decorative pavements, railings, sculptures, pools of water and...

24 CFR 570.201 - Basic eligible activities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... provided for in § 570.207(a)(1).) In undertaking such activities, design features and improvements which... design features, and similar treatments intended to enhance the aesthetic quality of facilities and improvements receiving CDBG assistance, such as decorative pavements, railings, sculptures, pools of water and...

Program Management Collection. "LINCS" Resource Collection News

ERIC Educational Resources Information Center

Literacy Information and Communication System, 2011

2011-01-01

This edition of "'LINCS' Resource Collection News" features the Program Management Collection, which covers the topics of Assessment, Learning Disabilities, and Program Improvement. Each month Collections News features one of the three "LINCS" (Literacy Information and Communication System) Resource Collections--Basic Skills, Program Management,…

Taking the School to the Child: An Experiment by Ruchika School Service Wing.

ERIC Educational Resources Information Center

Khurana, Inderjit

1992-01-01

Describes a basic literacy project targeting deprived children in Bhubaneswar, Orissa, India. Considers such program features as the use of 35 slum and public utility centers as sites for teaching basic skills, nutrition, and hygiene; flexible schedules including morning classes for slum children and afternoon and evening classes for working…

A Comparison of the Language Features of Basic and HyperCard.

ERIC Educational Resources Information Center

Henry, M. J.; Southerly, T. W.

This paper examines the structure of the Applesoft BASIC programming language and the Macintosh authoring language, HyperCard, and scrutinizes the language structures as the building blocks for moving along a chain of cognitive outcomes that culminates in the acquisition of problem solving skills which allow the programmer to learn new formal…

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY.

PubMed

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2009-08-07

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY

PubMed Central

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2010-01-01

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application. PMID:21197416

Effects of preprocessing Landsat MSS data on derived features

NASA Technical Reports Server (NTRS)

Parris, T. M.; Cicone, R. C.

1983-01-01

Important to the use of multitemporal Landsat MSS data for earth resources monitoring, such as agricultural inventories, is the ability to minimize the effects of varying atmospheric and satellite viewing conditions, while extracting physically meaningful features from the data. In general, the approaches to the preprocessing problem have been derived from either physical or statistical models. This paper compares three proposed algorithms; XSTAR haze correction, Color Normalization, and Multiple Acquisition Mean Level Adjustment. These techniques represent physical, statistical, and hybrid physical-statistical models, respectively. The comparisons are made in the context of three feature extraction techniques; the Tasseled Cap, the Cate Color Cube. and Normalized Difference.

Geospatial tools for the identification of a malaria corridor in Estado Sucre, a Venezuelan north-eastern state.

PubMed

Delgado-Petrocelli, Laura; Camardiel, Alberto; Aguilar, Víctor Hugo; Martinez, Néstor; Córdova, Karenia; Ramos, Santiago

2011-05-01

Landscape ecology research relies on frameworks based on geographical information systems (GIS), geostatistics and spatial-feature relationships. With regard to health, the approach consists of systems analysis using a set of powerful tools aimed at the reduction of community vulnerability through improved public policies. The north-oriental malaria focus, one of five such foci in Venezuela, situated in the north-eastern part of the Estado Sucre state, unites several social and environmental features and functions as an epidemiological corridor, i.e. an endemic zone characterised by permanent interaction between the mosquito vector and the human host allowing a continuous persistence of the malaria lifecycle. A GIS was developed based on official cartography with thematic overlays depicting malaria distribution, socio-economic conditions, basic environmental information and specific features associated with the natural wetlands present in the area. Generally, malaria foci are continuously active but when the malaria situation was modelled in the north-oriental focus, a differential, spatio-temporal distribution pattern situation was found, i.e. a situation oscillating between very active and dormant transmission. This pattern was displayed by spatial and statistical analysis based on the model generated in this study and the results were confirmed by municipal and county malaria records. Control of malaria, keeping the incidence at a permanently low level within the regional population, should be possible if these results are taken into account when designing and implementing epidemiological surveillance policies.

Machine learning approach for automated screening of malaria parasite using light microscopic images.

PubMed

Das, Dev Kumar; Ghosh, Madhumala; Pal, Mallika; Maiti, Asok K; Chakraborty, Chandan

2013-02-01

The aim of this paper is to address the development of computer assisted malaria parasite characterization and classification using machine learning approach based on light microscopic images of peripheral blood smears. In doing this, microscopic image acquisition from stained slides, illumination correction and noise reduction, erythrocyte segmentation, feature extraction, feature selection and finally classification of different stages of malaria (Plasmodium vivax and Plasmodium falciparum) have been investigated. The erythrocytes are segmented using marker controlled watershed transformation and subsequently total ninety six features describing shape-size and texture of erythrocytes are extracted in respect to the parasitemia infected versus non-infected cells. Ninety four features are found to be statistically significant in discriminating six classes. Here a feature selection-cum-classification scheme has been devised by combining F-statistic, statistical learning techniques i.e., Bayesian learning and support vector machine (SVM) in order to provide the higher classification accuracy using best set of discriminating features. Results show that Bayesian approach provides the highest accuracy i.e., 84% for malaria classification by selecting 19 most significant features while SVM provides highest accuracy i.e., 83.5% with 9 most significant features. Finally, the performance of these two classifiers under feature selection framework has been compared toward malaria parasite classification. Copyright © 2012 Elsevier Ltd. All rights reserved.

Laban Movement Analysis towards Behavior Patterns

NASA Astrophysics Data System (ADS)

Santos, Luís; Dias, Jorge

This work presents a study about the use of Laban Movement Analysis (LMA) as a robust tool to describe human basic behavior patterns, to be applied in human-machine interaction. LMA is a language used to describe and annotate dancing movements and is divided in components [1]: Body, Space, Shape and Effort. Despite its general framework is widely used in physical and mental therapy [2], it has found little application in the engineering domain. Rett J. [3] proposed to implement LMA using Bayesian Networks. However LMA component models have not yet been fully implemented. A study on how to approach behavior using LMA is presented. Behavior is a complex feature and movement chain, but we believe that most basic behavior primitives can be discretized in simple features. Correctly identifying Laban parameters and the movements the authors feel that good patterns can be found within a specific set of basic behavior semantics.

Combining statistical inference and decisions in ecology.

PubMed

Williams, Perry J; Hooten, Mevin B

2016-09-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods, including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem. © 2016 by the Ecological Society of America.

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

PubMed Central

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J.; Yanes, Oscar

2012-01-01

Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples. PMID:24957762

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data.

PubMed

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J; Yanes, Oscar

2012-10-18

Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.

a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

NASA Astrophysics Data System (ADS)

Li, L.; Yang, H.; Chen, Q.; Liu, X.

2018-04-01

Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

Guided Search for Triple Conjunctions

PubMed Central

Nordfang, Maria; Wolfe, Jeremy M

2017-01-01

A key tenet of Feature Integration Theory and related theories such as Guided Search (GS) is that the binding of basic features requires attention. This would seem to predict that conjunctions of features of objects that have not been attended should not influence search. However, Found (1998) reported that an irrelevant feature (size) improved the efficiency of search for a color × orientation conjunction if it was correlated with the other two features across the display compared to the case where size was not correlated with color and orientation features. We examine this issue with somewhat different stimuli. We use triple conjunctions of color, orientation and shape (e.g. search for a red, vertical, oval-shaped item). This allows us to manipulate the number of features that each distractor shares with the target (Sharing) and it allows us to vary the total number of distractor types (and, thus, the number of groups of identical items; Grouping). We find these triple conjunction searches are generally very efficient – producing very shallow reaction time (RT) × set size slopes, consistent with strong guidance by basic features. Nevertheless, both of these variables, Sharing and Grouping modulate performance. These influences are not predicted by previous accounts of GS. However, both can be accommodated in a GS framework. Alternatively, it is possible, if not necessary, to see these effects as evidence for “preattentive binding” of conjunctions. PMID:25005070

Guided search for triple conjunctions.

PubMed

Nordfang, Maria; Wolfe, Jeremy M

2014-08-01

A key tenet of feature integration theory and of related theories such as guided search (GS) is that the binding of basic features requires attention. This would seem to predict that conjunctions of features of objects that have not been attended should not influence search. However, Found (1998) reported that an irrelevant feature (size) improved the efficiency of search for a Color × Orientation conjunction if it was correlated with the other two features across the display, as compared to the case in which size was not correlated with color and orientation features. We examined this issue with somewhat different stimuli. We used triple conjunctions of color, orientation, and shape (e.g., search for a red, vertical, oval-shaped item). This allowed us to manipulate the number of features that each distractor shared with the target (sharing) and it allowed us to vary the total number of distractor types (and, thus, the number of groups of identical items: grouping). We found that these triple conjunction searches were generally very efficient--producing very shallow Reaction Time × Set Size slopes, consistent with strong guidance by basic features. Nevertheless, both of the variables, sharing and grouping, modulated performance. These influences were not predicted by previous accounts of GS; however, both can be accommodated in a GS framework. Alternatively, it is possible, though not necessary, to see these effects as evidence for "preattentive binding" of conjunctions.

Peers versus professional training of basic life support in Syria: a randomized controlled trial.

PubMed

Abbas, Fatima; Sawaf, Bisher; Hanafi, Ibrahem; Hajeer, Mohammad Younis; Zakaria, Mhd Ismael; Abbas, Wafaa; Alabdeh, Fadi; Ibrahim, Nazir

2018-06-18

Peer training has been identified as a useful tool for delivering undergraduate training in basic life support (BLS) which is fundamental as an initial response in cases of emergency. This study aimed to (1) Evaluate the efficacy of peer-led model in basic life support training among medical students in their first three years of study, compared to professional-led training and (2) To assess the efficacy of the course program and students' satisfaction of peer-led training. A randomized controlled trial with blinded assessors was conducted on 72 medical students from the pre-clinical years (1st to 3rd years in Syria) at Syrian Private University. Students were randomly assigned to peer-led or to professional-led training group for one-day-course of basic life support skills. Sixty-four students who underwent checklist based assessment using objective structured clinical examination design (OSCE) (practical assessment of BLS skills) and answered BLS knowledge checkpoint-questionnaire were included in the analysis. There was no statistically significant difference between the two groups in delivering BLS skills to medical students in practical (P = 0.850) and BLS knowledge questionnaire outcomes (P = 0.900). Both groups showed statistically significant improvement from pre- to post-course assessment with significant statistical difference in both practical skills and theoretical knowledge (P-Value < 0.001). Students were satisfied with the peer model of training. Peer-led training of basic life support for medical students was beneficial and it provided a quality of education which was as effective as training conducted by professionals. This method is applicable and desirable especially in poor-resource countries and in crisis situation.

An adaptive approach to the dynamic allocation of buffer storage. M.S. Thesis

NASA Technical Reports Server (NTRS)

Crooke, S. C.

1970-01-01

Several strategies for the dynamic allocation of buffer storage are simulated and compared. The basic algorithms investigated, using actual statistics observed in the Univac 1108 EXEC 8 System, include the buddy method and the first-fit method. Modifications are made to the basic methods in an effort to improve and to measure allocation performance. A simulation model of an adaptive strategy is developed which permits interchanging the two different methods, the buddy and the first-fit methods with some modifications. Using an adaptive strategy, each method may be employed in the statistical environment in which its performance is superior to the other method.

Ultrasound Dopplerography of abdomen pathology using statistical computer programs

NASA Astrophysics Data System (ADS)

Dmitrieva, Irina V.; Arakelian, Sergei M.; Wapota, Alberto R. W.

1998-04-01

The modern ultrasound dopplerography give us the big possibilities in investigation of gemodynamical changes in all stages of abdomen pathology. Many of researches devoted to using of noninvasive methods in practical medicine. Now ultrasound Dopplerography is one of the basic one. We investigated 250 patients from 30 to 77 ages, including 149 men and 101 women. The basic diagnosis of all patients was the Ischaemic Pancreatitis. The Second diagnoses of pathology were the Ischaemic Disease of Heart, Gypertension, Atherosclerosis, Diabet, Vascular Disease of Extremities. We researched the abdominal aorta and her branches: Arteria Mesenterica Superior (AMS), truncus coeliacus (TC), arteria hepatica communis (AHC), arteria lienalis (AL). For investigation we use the following equipment: ACUSON 128 XP/10c, BIOMEDIC, GENERAL ELECTRIC (USA, Japan). We analyzed the following componetns of gemodynamical changes of abdominal vessels: index of pulsation, index of resistance, ratio of systol-dystol, speed of blood circulation. Statistical program included the following one: 'basic statistic's,' 'analytic program.' In conclusion we determined that the all gemodynamical components of abdominal vessels had considerable changes in abdominal ischaemia than in normal situation. Using the computer's program for definition degree of gemodynamical changes, we can recommend the individual plan of diagnostical and treatment program.

The facial levels of the melting of the Permian - Triassic trap basalts of West Siberian plate and Siberian platform.

NASA Astrophysics Data System (ADS)

Sharapov, Victor; Vasiliev, Yury

2014-05-01

Statistical processing of numerical information allow to indicate the following regional petro- geochemical characteristics of Permo-Triassic trap magmatism in West Siberian plate WSP: 1) Examined regional petrochemical trend of major element chemistry variation of trap magmatism from north to the south is appeared in increase of the acidity, a decrease of Mg and alumina and potassium of the igneous rocks, for other components existing data do not allow to determine regularities; 2) According to (La/Yb)n, (Gd/Yb)n and(Tb/Yb)n ratios all basic melts belong to the spinel facie. In general the trap basalts of Siberian Platform reveal the following structural facial features are characteristic: 1) From west and east the region of the basalt effusions practically coincides with the area of Devonian sea depressions, 2) from the west to east lava shields are framed by the zones of the variously differentiated intrusive basic bodies grouped within the zones of arched and linear faults; 3) the region of effusive volcanics appearance has the zone - distributed structural - material areas, the tholeitic "super-shield" (plateau Putorana) occupyingthe center part of the Tunguska syneclise), framed from the West, and NW by the local lava shields located in rounded depressions( mulda) in which the lavas are more magnesian, titaniferrous and alkaline. 4) examined overall petrochemical zonation of basic rocks in Siberian platform reveal general decrease from the Norilsk mulda to Angara- Ilim iron-ore deposit region, with the growth of Ti02 and alkalinity of the basic rocks. The statistical wavelet analysis of the cyclic recurrence of the effusive rock sections along the eastern board of Khatanga rift show substantially different characteristics of the spectra of time series, in Norilsk -Kharaelakh depression the low-frequency modules predominate, whereas for The Meimecha-Kotuy effusion section the high frequency values are characteristic. The comparison of the possible facial levels of the melting of the initial magmas of trap basalts in WSP and Siberian platform showed that the magnesian melts were generated in garnet mantle facie, and major part of the basalt melts, forming volcanic plateaus in Siberian Platform and traps of WSP were apparently generated in the spinel facie of lithospheric mantle. The most obvious evidence of two - level magmatic sources is found on the border with the eastern margin of Khatanga depression and in the region of junction of volcanic plateau and Anabar craton. RFBR grant 12-05-00625

Resilience Among Students at the Basic Enlisted Submarine School

DTIC Science & Technology

2016-12-01

reported resilience. The Hayes’ Macro in the Statistical Package for the Social Sciences (SSPS) was used to uncover factors relevant to mediation analysis... Statistical Package for the Social Sciences (SPSS) was used to uncover factors relevant to mediation analysis. Findings suggest that the encouragement of...to Stressful Experiences Scale RTC Recruit Training Command SPSS Statistical Package for the Social Sciences SS Social Support SWB Subjective Well

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

A Simple Statistical Thermodynamics Experiment

ERIC Educational Resources Information Center

LoPresto, Michael C.

2010-01-01

Comparing the predicted and actual rolls of combinations of both two and three dice can help to introduce many of the basic concepts of statistical thermodynamics, including multiplicity, probability, microstates, and macrostates, and demonstrate that entropy is indeed a measure of randomness, that disordered states (those of higher entropy) are…

76 FR 41756 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-15

... materials and supplies used in production. The economic census will produce basic statistics by kind of business on number of establishments, sales, payroll, employment, inventories, and operating expenses. It also will yield a variety of subject statistics, including sales by product line; sales by class of...

Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who, What, Why, When, Where, and a Sixth, So What?

PubMed

Vetter, Thomas R

2017-11-01

Descriptive statistics are specific methods basically used to calculate, describe, and summarize collected research data in a logical, meaningful, and efficient way. Descriptive statistics are reported numerically in the manuscript text and/or in its tables, or graphically in its figures. This basic statistical tutorial discusses a series of fundamental concepts about descriptive statistics and their reporting. The mean, median, and mode are 3 measures of the center or central tendency of a set of data. In addition to a measure of its central tendency (mean, median, or mode), another important characteristic of a research data set is its variability or dispersion (ie, spread). In simplest terms, variability is how much the individual recorded scores or observed values differ from one another. The range, standard deviation, and interquartile range are 3 measures of variability or dispersion. The standard deviation is typically reported for a mean, and the interquartile range for a median. Testing for statistical significance, along with calculating the observed treatment effect (or the strength of the association between an exposure and an outcome), and generating a corresponding confidence interval are 3 tools commonly used by researchers (and their collaborating biostatistician or epidemiologist) to validly make inferences and more generalized conclusions from their collected data and descriptive statistics. A number of journals, including Anesthesia & Analgesia, strongly encourage or require the reporting of pertinent confidence intervals. A confidence interval can be calculated for virtually any variable or outcome measure in an experimental, quasi-experimental, or observational research study design. Generally speaking, in a clinical trial, the confidence interval is the range of values within which the true treatment effect in the population likely resides. In an observational study, the confidence interval is the range of values within which the true strength of the association between the exposure and the outcome (eg, the risk ratio or odds ratio) in the population likely resides. There are many possible ways to graphically display or illustrate different types of data. While there is often latitude as to the choice of format, ultimately, the simplest and most comprehensible format is preferred. Common examples include a histogram, bar chart, line chart or line graph, pie chart, scatterplot, and box-and-whisker plot. Valid and reliable descriptive statistics can answer basic yet important questions about a research data set, namely: "Who, What, Why, When, Where, How, How Much?"

Semantic Feature Distinctiveness and Frequency

ERIC Educational Resources Information Center

Lamb, Katherine M.

2012-01-01

Lexical access is the process in which basic components of meaning in language, the lexical entries (words) are activated. This activation is based on the organization and representational structure of the lexical entries. Semantic features of words, which are the prominent semantic characteristics of a word concept, provide important information…

Integrated System Test of the Advanced Instructional System (AIS). Final Report.

ERIC Educational Resources Information Center

Lintz, Larry M.; And Others

The integrated system test for the Advanced Instructional System (AIS) was designed to provide quantitative information regarding training time reductions resulting from certain computer managed instruction features. The reliabilities of these features and of support systems were also investigated. Basic computer managed instruction reduced…

ON THE DYNAMICAL DERIVATION OF EQUILIBRIUM STATISTICAL MECHANICS

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

Prigogine, I.; Balescu, R.; Henin, F.

1960-12-01

Work on nonequilibrium statistical mechanics, which allows an extension of the kinetic proof to all results of equilibrium statistical mechanics involving a finite number of degrees of freedom, is summarized. As an introduction to the general N-body problem, the scattering theory in classical mechanics is considered. The general N-body problem is considered for the case of classical mechanics, quantum mechanics with Boltzmann statistics, and quantum mechanics including quantum statistics. Six basic diagrams, which describe the elementary processes of the dynamics of correlations, were obtained. (M.C.G.)

`New insight into statistical hydrology' preface to the special issue

NASA Astrophysics Data System (ADS)

Kochanek, Krzysztof

2018-04-01

Statistical methods are still the basic tool for investigating random, extreme events occurring in hydrosphere. On 21-22 September 2017, in Warsaw (Poland) the international workshop of the Statistical Hydrology (StaHy) 2017 took place under the auspices of the International Association of Hydrological Sciences. The authors of the presentations proposed to publish their research results in the Special Issue of the Acta Geophysica-`New Insight into Statistical Hydrology'. Five papers were selected for publication, touching on the most crucial issues of statistical methodology in hydrology.

Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?

NASA Astrophysics Data System (ADS)

Shi, Bibo; Grimm, Lars J.; Mazurowski, Maciej A.; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2017-03-01

Reducing the overdiagnosis and overtreatment associated with ductal carcinoma in situ (DCIS) requires accurate prediction of the invasive potential at cancer screening. In this work, we investigated the utility of pre-operative histologic and mammographic features to predict upstaging of DCIS. The goal was to provide intentionally conservative baseline performance using readily available data from radiologists and pathologists and only linear models. We conducted a retrospective analysis on 99 patients with DCIS. Of those 25 were upstaged to invasive cancer at the time of definitive surgery. Pre-operative factors including both the histologic features extracted from stereotactic core needle biopsy (SCNB) reports and the mammographic features annotated by an expert breast radiologist were investigated with statistical analysis. Furthermore, we built classification models based on those features in an attempt to predict the presence of an occult invasive component in DCIS, with generalization performance assessed by receiver operating characteristic (ROC) curve analysis. Histologic features including nuclear grade and DCIS subtype did not show statistically significant differences between cases with pure DCIS and with DCIS plus invasive disease. However, three mammographic features, i.e., the major axis length of DCIS lesion, the BI-RADS level of suspicion, and radiologist's assessment did achieve the statistical significance. Using those three statistically significant features as input, a linear discriminant model was able to distinguish patients with DCIS plus invasive disease from those with pure DCIS, with AUC-ROC equal to 0.62. Overall, mammograms used for breast screening contain useful information that can be perceived by radiologists and help predict occult invasive components in DCIS.

Capability of geometric features to classify ships in SAR imagery

NASA Astrophysics Data System (ADS)

Lang, Haitao; Wu, Siwen; Lai, Quan; Ma, Li

2016-10-01

Ship classification in synthetic aperture radar (SAR) imagery has become a new hotspot in remote sensing community for its valuable potential in many maritime applications. Several kinds of ship features, such as geometric features, polarimetric features, and scattering features have been widely applied on ship classification tasks. Compared with polarimetric features and scattering features, which are subject to SAR parameters (e.g., sensor type, incidence angle, polarization, etc.) and environment factors (e.g., sea state, wind, wave, current, etc.), geometric features are relatively independent of SAR and environment factors, and easy to be extracted stably from SAR imagery. In this paper, the capability of geometric features to classify ships in SAR imagery with various resolution has been investigated. Firstly, the relationship between the geometric feature extraction accuracy and the SAR imagery resolution is analyzed. It shows that the minimum bounding rectangle (MBR) of ship can be extracted exactly in terms of absolute precision by the proposed automatic ship-sea segmentation method. Next, six simple but effective geometric features are extracted to build a ship representation for the subsequent classification task. These six geometric features are composed of length (f1), width (f2), area (f3), perimeter (f4), elongatedness (f5) and compactness (f6). Among them, two basic features, length (f1) and width (f2), are directly extracted based on the MBR of ship, the other four are derived from those two basic features. The capability of the utilized geometric features to classify ships are validated on two data set with different image resolutions. The results show that the performance of ship classification solely by geometric features is close to that obtained by the state-of-the-art methods, which obtained by a combination of multiple kinds of features, including scattering features and geometric features after a complex feature selection process.

Acoustic Emission Analysis Applet (AEAA) Software

NASA Technical Reports Server (NTRS)

Nichols, Charles T.; Roth, Don J.

2013-01-01

NASA Glenn Research and NASA White Sands Test Facility have developed software supporting an automated pressure vessel structural health monitoring (SHM) system based on acoustic emissions (AE). The software, referred to as the Acoustic Emission Analysis Applet (AEAA), provides analysts with a tool that can interrogate data collected on Digital Wave Corp. and Physical Acoustics Corp. software using a wide spectrum of powerful filters and charts. This software can be made to work with any data once the data format is known. The applet will compute basic AE statistics, and statistics as a function of time and pressure (see figure). AEAA provides value added beyond the analysis provided by the respective vendors' analysis software. The software can handle data sets of unlimited size. A wide variety of government and commercial applications could benefit from this technology, notably requalification and usage tests for compressed gas and hydrogen-fueled vehicles. Future enhancements will add features similar to a "check engine" light on a vehicle. Once installed, the system will ultimately be used to alert International Space Station crewmembers to critical structural instabilities, but will have little impact to missions otherwise. Diagnostic information could then be transmitted to experienced technicians on the ground in a timely manner to determine whether pressure vessels have been impacted, are structurally unsound, or can be safely used to complete the mission.

Universal biology and the statistical mechanics of early life.

PubMed

Goldenfeld, Nigel; Biancalani, Tommaso; Jafarpour, Farshid

2017-12-28

All known life on the Earth exhibits at least two non-trivial common features: the canonical genetic code and biological homochirality, both of which emerged prior to the Last Universal Common Ancestor state. This article describes recent efforts to provide a narrative of this epoch using tools from statistical mechanics. During the emergence of self-replicating life far from equilibrium in a period of chemical evolution, minimal models of autocatalysis show that homochirality would have necessarily co-evolved along with the efficiency of early-life self-replicators. Dynamical system models of the evolution of the genetic code must explain its universality and its highly refined error-minimization properties. These have both been accounted for in a scenario where life arose from a collective, networked phase where there was no notion of species and perhaps even individuality itself. We show how this phase ultimately terminated during an event sometimes known as the Darwinian transition, leading to the present epoch of tree-like vertical descent of organismal lineages. These examples illustrate concrete examples of universal biology: the quest for a fundamental understanding of the basic properties of living systems, independent of precise instantiation in chemistry or other media.This article is part of the themed issue 'Reconceptualizing the origins of life'. © 2017 The Author(s).

Data visualization, bar naked: A free tool for creating interactive graphics.

PubMed

Weissgerber, Tracey L; Savic, Marko; Winham, Stacey J; Stanisavljevic, Dejana; Garovic, Vesna D; Milic, Natasa M

2017-12-15

Although bar graphs are designed for categorical data, they are routinely used to present continuous data in studies that have small sample sizes. This presentation is problematic, as many data distributions can lead to the same bar graph, and the actual data may suggest different conclusions from the summary statistics. To address this problem, many journals have implemented new policies that require authors to show the data distribution. This paper introduces a free, web-based tool for creating an interactive alternative to the bar graph (http://statistika.mfub.bg.ac.rs/interactive-dotplot/). This tool allows authors with no programming expertise to create customized interactive graphics, including univariate scatterplots, box plots, and violin plots, for comparing values of a continuous variable across different study groups. Individual data points may be overlaid on the graphs. Additional features facilitate visualization of subgroups or clusters of non-independent data. A second tool enables authors to create interactive graphics from data obtained with repeated independent experiments (http://statistika.mfub.bg.ac.rs/interactive-repeated-experiments-dotplot/). These tools are designed to encourage exploration and critical evaluation of the data behind the summary statistics and may be valuable for promoting transparency, reproducibility, and open science in basic biomedical research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Universal biology and the statistical mechanics of early life

NASA Astrophysics Data System (ADS)

Goldenfeld, Nigel; Biancalani, Tommaso; Jafarpour, Farshid

2017-11-01

All known life on the Earth exhibits at least two non-trivial common features: the canonical genetic code and biological homochirality, both of which emerged prior to the Last Universal Common Ancestor state. This article describes recent efforts to provide a narrative of this epoch using tools from statistical mechanics. During the emergence of self-replicating life far from equilibrium in a period of chemical evolution, minimal models of autocatalysis show that homochirality would have necessarily co-evolved along with the efficiency of early-life self-replicators. Dynamical system models of the evolution of the genetic code must explain its universality and its highly refined error-minimization properties. These have both been accounted for in a scenario where life arose from a collective, networked phase where there was no notion of species and perhaps even individuality itself. We show how this phase ultimately terminated during an event sometimes known as the Darwinian transition, leading to the present epoch of tree-like vertical descent of organismal lineages. These examples illustrate concrete examples of universal biology: the quest for a fundamental understanding of the basic properties of living systems, independent of precise instantiation in chemistry or other media. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Automated thematic mapping and change detection of ERTS-A images. [digital interpretation of Arizona imagery

NASA Technical Reports Server (NTRS)

Gramenopoulos, N. (Principal Investigator)

1973-01-01

The author has identified the following significant results. For the recognition of terrain types, spatial signatures are developed from the diffraction patterns of small areas of ERTS-1 images. This knowledge is exploited for the measurements of a small number of meaningful spatial features from the digital Fourier transforms of ERTS-1 image cells containing 32 x 32 picture elements. Using these spatial features and a heuristic algorithm, the terrain types in the vicinity of Phoenix, Arizona were recognized by the computer with a high accuracy. Then, the spatial features were combined with spectral features and using the maximum likelihood criterion the recognition accuracy of terrain types increased substantially. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. Nonlinear transformations of the feature vectors are required so that the terrain class statistics become approximately Gaussian. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month but vary substantially between seasons.

Separating morphologically similar pollen types using basic shape features from digital images: A preliminary study1

PubMed Central

Holt, Katherine A.; Bebbington, Mark S.

2014-01-01

• Premise of the study: One of the many advantages offered by automated palynology systems is the ability to vastly increase the number of observations made on a particular sample or samples. This is of particular benefit when attempting to fully quantify the degree of variation within or between closely related pollen types. • Methods: An automated palynology system (Classifynder) has been used to further investigate the variation in pollen morphology between two New Zealand species of Myrtaceae (Leptospermum scoparium and Kunzea ericoides) that are of significance in the New Zealand honey industry. Seven geometric features extracted from automatically gathered digital images were used to characterize the range of shape and size of the two taxa, and to examine the extent of previously reported overlap in these variables. • Results: Our results indicate a degree of overlap in all cases. The narrowest overlap was in measurements of maximum Feret diameter (MFD) in grains oriented in polar view. Multivariate statistical analysis using all seven factors provided the most robust discrimination between the two types. • Discussion: Further work is required before this approach could be routinely applied to separating the two pollen types used in this study, most notably the development of comprehensive reference distributions for the types in question. PMID:25202650

Prediction of paroxysmal atrial fibrillation using recurrence plot-based features of the RR-interval signal.

PubMed

Mohebbi, Maryam; Ghassemian, Hassan

2011-08-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia and increases the risk of stroke. Predicting the onset of paroxysmal AF (PAF), based on noninvasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize risks for the patients. In this paper, we propose an effective PAF predictor which is based on the analysis of the RR-interval signal. This method consists of three steps: preprocessing, feature extraction and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the RR-interval signal is extracted. In the next step, the recurrence plot (RP) of the RR-interval signal is obtained and five statistically significant features are extracted to characterize the basic patterns of the RP. These features consist of the recurrence rate, length of longest diagonal segments (L(max )), average length of the diagonal lines (L(mean)), entropy, and trapping time. Recurrence quantification analysis can reveal subtle aspects of dynamics not easily appreciated by other methods and exhibits characteristic patterns which are caused by the typical dynamical behavior. In the final step, a support vector machine (SVM)-based classifier is used for PAF prediction. The performance of the proposed method in prediction of PAF episodes was evaluated using the Atrial Fibrillation Prediction Database (AFPDB) which consists of both 30 min ECG recordings that end just prior to the onset of PAF and segments at least 45 min distant from any PAF events. The obtained sensitivity, specificity, positive predictivity and negative predictivity were 97%, 100%, 100%, and 96%, respectively. The proposed methodology presents better results than other existing approaches.

Digitise This! A Quick and Easy Remote Sensing Method to Monitor the Daily Extent of Dredge Plumes

PubMed Central

Evans, Richard D.; Murray, Kathy L.; Field, Stuart N.; Moore, James A. Y.; Shedrawi, George; Huntley, Barton G.; Fearns, Peter; Broomhall, Mark; McKinna, Lachlan I. W.; Marrable, Daniel

2012-01-01

Technological advancements in remote sensing and GIS have improved natural resource managers’ abilities to monitor large-scale disturbances. In a time where many processes are heading towards automation, this study has regressed to simple techniques to bridge a gap found in the advancement of technology. The near-daily monitoring of dredge plume extent is common practice using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and associated algorithms to predict the total suspended solids (TSS) concentration in the surface waters originating from floods and dredge plumes. Unfortunately, these methods cannot determine the difference between dredge plume and benthic features in shallow, clear water. This case study at Barrow Island, Western Australia, uses hand digitising to demonstrate the ability of human interpretation to determine this difference with a level of confidence and compares the method to contemporary TSS methods. Hand digitising was quick, cheap and required very little training of staff to complete. Results of ANOSIM R statistics show remote sensing derived TSS provided similar spatial results if they were thresholded to at least 3 mg L−1. However, remote sensing derived TSS consistently provided false-positive readings of shallow benthic features as Plume with a threshold up to TSS of 6 mg L−1, and began providing false-negatives (excluding actual plume) at a threshold as low as 4 mg L−1. Semi-automated processes that estimate plume concentration and distinguish between plumes and shallow benthic features without the arbitrary nature of human interpretation would be preferred as a plume monitoring method. However, at this stage, the hand digitising method is very useful and is more accurate at determining plume boundaries over shallow benthic features and is accessible to all levels of management with basic training. PMID:23240055

The Social Profile of Students in Basic General Education in Ecuador: A Data Analysis

ERIC Educational Resources Information Center

Buri, Olga Elizabeth Minchala; Stefos, Efstathios

2017-01-01

The objective of this study is to examine the social profile of students who are enrolled in Basic General Education in Ecuador. Both a descriptive and multidimensional statistical analysis was carried out based on the data provided by the National Survey of Employment, Unemployment and Underemployment in 2015. The descriptive analysis shows the…

Improving Attendance and Punctuality of FE Basic Skill Students through an Innovative Scheme

ERIC Educational Resources Information Center

Ade-Ojo, Gordon O.

2005-01-01

This paper reports the findings of a study set up to establish the impact of a particular scheme on the attendance and punctuality performance of a group of Basic Skills learners against the backdrop of various theoretical postulations on managing undesirable behavior. Data collected on learners' performance was subjected to statistical analysis…

Statistical Match of the VA 1979-1980 Recipient File against the 1979-1980 Basic Grant Recipient File. Revised.

ERIC Educational Resources Information Center

Applied Management Sciences, Inc., Silver Spring, MD.

The amount of misreporting of Veterans Administration (VA) benefits was assessed, along with the impact of misreporting on the Basic Educational Opportunity Grant (BEOG) program. Accurate financial information is need to determine appropriate awards. The analysis revealed: over 97% of VA beneficiaries misreported benefits; the total net loss to…

An Inspection on the Gini Coefficient of the Budget Educational Public Expenditure per Student for China's Basic Education

ERIC Educational Resources Information Center

Yingxiu, Yang

2006-01-01

Using statistical data on the implementing conditions of China's educational expenditure published by the state, this paper studies the Gini coefficient of the budget educational public expenditure per student in order to examine the concentration degree of the educational expenditure for China's basic education and analyze its balanced…

Trees for Ohio

Treesearch

Ernest J. Gebhart

1980-01-01

Other members of this panel are going to reveal the basic statistics about the coal strip mining industry in Ohio so I will confine my remarks to the revegetation of the spoil banks. So it doesn't appear that Ohio confined its tree planting efforts to spoil banks alone, I will rely on a few statistics.

Idaho State University Statistical Portrait, Academic Year 1998-1999.

ERIC Educational Resources Information Center

Idaho State Univ., Pocatello. Office of Institutional Research.

This report provides basic statistical data for Idaho State University, and includes both point-of-time data as well as trend data. The information is divided into sections emphasizing students, programs, faculty and staff, finances, and physical facilities. Student data includes enrollment, geographical distribution, student/faculty ratios,…

Statistical Report. Fiscal Year 1995: September 1, 1994 - August 31, 1995.

ERIC Educational Resources Information Center

Texas Higher Education Coordinating Board, Austin.

This report provides statistical data on Texas public and independent higher education institutions for fiscal year 1995. An introductory section provides basic information on Texas higher education institutions, while nine major sections cover: (1) student enrollment, including 1990-94 headcount data; headcount by classification, ethnic origin,…

Statistical Report. Fiscal Year 1994: September 1, 1993 - August 31, 1994.

ERIC Educational Resources Information Center

Texas Higher Education Coordinating Board, Austin.

This report provides statistical data on Texas public and independent higher education institutions for fiscal year 1994. An introductory section provides basic information on Texas higher education institutions, while nine major sections cover: (1) student enrollment, including 1989-93 headcount data; headcount by classification, ethnic origin,…

29 CFR 1904.42 - Requests from the Bureau of Labor Statistics for data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... ADMINISTRATION, DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Reporting Fatality, Injury and Illness Information to the Government § 1904.42 Requests from the Bureau of Labor Statistics for data. (a) Basic requirement. If you receive a Survey of Occupational Injuries and Illnesses...

29 CFR 1904.42 - Requests from the Bureau of Labor Statistics for data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... ADMINISTRATION, DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Reporting Fatality, Injury and Illness Information to the Government § 1904.42 Requests from the Bureau of Labor Statistics for data. (a) Basic requirement. If you receive a Survey of Occupational Injuries and Illnesses...

29 CFR 1904.42 - Requests from the Bureau of Labor Statistics for data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... ADMINISTRATION, DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Reporting Fatality, Injury and Illness Information to the Government § 1904.42 Requests from the Bureau of Labor Statistics for data. (a) Basic requirement. If you receive a Survey of Occupational Injuries and Illnesses...

29 CFR 1904.42 - Requests from the Bureau of Labor Statistics for data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... ADMINISTRATION, DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Reporting Fatality, Injury and Illness Information to the Government § 1904.42 Requests from the Bureau of Labor Statistics for data. (a) Basic requirement. If you receive a Survey of Occupational Injuries and Illnesses...

Theoretical Frameworks for Math Fact Fluency

ERIC Educational Resources Information Center

Arnold, Katherine

2012-01-01

Recent education statistics indicate persistent low math scores for our nation's students. This drop in math proficiency includes deficits in basic number sense and automaticity of math facts. The decrease has been recorded across all grade levels with the elementary levels showing the greatest loss (National Center for Education Statistics,…

Basic Statistical Concepts and Methods for Earth Scientists

USGS Publications Warehouse

Olea, Ricardo A.

2008-01-01

INTRODUCTION Statistics is the science of collecting, analyzing, interpreting, modeling, and displaying masses of numerical data primarily for the characterization and understanding of incompletely known systems. Over the years, these objectives have lead to a fair amount of analytical work to achieve, substantiate, and guide descriptions and inferences.

A Simple Radio Receiver Aids Understanding of Wireless Communication

ERIC Educational Resources Information Center

Straulino, S.; Orlando, A.

2012-01-01

The basic theory of radio broadcasting is discussed from an experimental point of view. First, concepts like wave modulation and tuning are explained with the use of instruments in the physics laboratory. Then, a very basic radio receiver is described and assembled, whose most important feature, like in the old "crystal radios", is the absence of…

High Dimensional Classification Using Features Annealed Independence Rules.

PubMed

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

Assessment of statistical education in Indonesia: Preliminary results and initiation to simulation-based inference

NASA Astrophysics Data System (ADS)

Saputra, K. V. I.; Cahyadi, L.; Sembiring, U. A.

2018-01-01

Start in this paper, we assess our traditional elementary statistics education and also we introduce elementary statistics with simulation-based inference. To assess our statistical class, we adapt the well-known CAOS (Comprehensive Assessment of Outcomes in Statistics) test that serves as an external measure to assess the student’s basic statistical literacy. This test generally represents as an accepted measure of statistical literacy. We also introduce a new teaching method on elementary statistics class. Different from the traditional elementary statistics course, we will introduce a simulation-based inference method to conduct hypothesis testing. From the literature, it has shown that this new teaching method works very well in increasing student’s understanding of statistics.

The Use of Molecular Modeling Programs in Medicinal Chemistry Instruction.

ERIC Educational Resources Information Center

Harrold, Marc W.

1992-01-01

This paper describes and evaluates the use of a molecular modeling computer program (Alchemy II) in a pharmaceutical education program. Provided are the hardware requirements and basic program features as well as several examples of how this program and its features have been applied in the classroom. (GLR)

Rebuilding Government Legitimacy in Post-conflict Societies: Case Studies of Nepal and Afghanistan

DTIC Science & Technology

2015-09-09

administered via the verbal scales due to reduced time spent explaining the visual show cards. Statistical results corresponded with observations from...a three-step strategy for dealing with item non-response. First, basic descriptive statistics are calculated to determine the extent of item...descriptive statistics for all items in the survey), however this section of the report highlights just some of the findings. Thus, the results

Biostatistical and medical statistics graduate education

PubMed Central

2014-01-01

The development of graduate education in biostatistics and medical statistics is discussed in the context of training within a medical center setting. The need for medical researchers to employ a wide variety of statistical designs in clinical, genetic, basic science and translational settings justifies the ongoing integration of biostatistical training into medical center educational settings and informs its content. The integration of large data issues are a challenge. PMID:24472088

A Thermodynamically General Theory for Convective Circulations and Vortices

NASA Astrophysics Data System (ADS)

Renno, N. O.

2007-12-01

Convective circulations and vortices are common features of atmospheres that absorb low-entropy-energy at higher temperatures than they reject high-entropy-energy to space. These circulations range from small to planetary-scale and play an important role in the vertical transport of heat, momentum, and tracer species. Thus, the development of theoretical models for convective phenomena is important to our understanding of many basic features of planetary atmospheres. A thermodynamically general theory for convective circulations and vortices is proposed. The theory includes irreversible processes and quantifies the pressure drop between the environment and any point in a convective updraft. The article's main result is that the proposed theory provides an expression for the pressure drop along streamlines or streamtubes that is a generalization of Bernoulli's equation to convective circulations. We speculate that the proposed theory not only explains the intensity, but also shed light on other basic features of convective circulations and vortices.

An algorithm for analytical solution of basic problems featuring elastostatic bodies with cavities and surface flaws

NASA Astrophysics Data System (ADS)

Penkov, V. B.; Levina, L. V.; Novikova, O. S.; Shulmin, A. S.

2018-03-01

Herein we propose a methodology for structuring a full parametric analytical solution to problems featuring elastostatic media based on state-of-the-art computing facilities that support computerized algebra. The methodology includes: direct and reverse application of P-Theorem; methods of accounting for physical properties of media; accounting for variable geometrical parameters of bodies, parameters of boundary states, independent parameters of volume forces, and remote stress factors. An efficient tool to address the task is the sustainable method of boundary states originally designed for the purposes of computerized algebra and based on the isomorphism of Hilbertian spaces of internal states and boundary states of bodies. We performed full parametric solutions of basic problems featuring a ball with a nonconcentric spherical cavity, a ball with a near-surface flaw, and an unlimited medium with two spherical cavities.

Electrophysiological correlates of the retention of tones differing in timbre in auditory short-term memory.

PubMed

Nolden, Sophie; Bermudez, Patrick; Alunni-Menichini, Kristelle; Lefebvre, Christine; Grimault, Stephan; Jolicoeur, Pierre

2013-11-01

We examined the electrophysiological correlates of retention in auditory short-term memory (ASTM) for sequences of one, two, or three tones differing in timbre but having the same pitch. We focused on event-related potentials (ERPs) during the retention interval and revealed a sustained fronto-central ERP component (most likely a sustained anterior negativity; SAN) that became more negative as memory load increased. Our results are consistent with recent ERP studies on the retention of pitch and suggest that the SAN reflects brain activity mediating the low-level retention of basic acoustic features in ASTM. The present work shows that the retention of timbre shares common features with the retention of pitch, hence supporting the notion that the retention of basic sensory features is an active process that recruits modality-specific brain areas. © 2013 Elsevier Ltd. All rights reserved.

PopSc: Computing Toolkit for Basic Statistics of Molecular Population Genetics Simultaneously Implemented in Web-Based Calculator, Python and R

PubMed Central

Huang, Ying; Li, Cao; Liu, Linhai; Jia, Xianbo; Lai, Song-Jia

2016-01-01

Although various computer tools have been elaborately developed to calculate a series of statistics in molecular population genetics for both small- and large-scale DNA data, there is no efficient and easy-to-use toolkit available yet for exclusively focusing on the steps of mathematical calculation. Here, we present PopSc, a bioinformatic toolkit for calculating 45 basic statistics in molecular population genetics, which could be categorized into three classes, including (i) genetic diversity of DNA sequences, (ii) statistical tests for neutral evolution, and (iii) measures of genetic differentiation among populations. In contrast to the existing computer tools, PopSc was designed to directly accept the intermediate metadata, such as allele frequencies, rather than the raw DNA sequences or genotyping results. PopSc is first implemented as the web-based calculator with user-friendly interface, which greatly facilitates the teaching of population genetics in class and also promotes the convenient and straightforward calculation of statistics in research. Additionally, we also provide the Python library and R package of PopSc, which can be flexibly integrated into other advanced bioinformatic packages of population genetics analysis. PMID:27792763

PopSc: Computing Toolkit for Basic Statistics of Molecular Population Genetics Simultaneously Implemented in Web-Based Calculator, Python and R.

PubMed

Chen, Shi-Yi; Deng, Feilong; Huang, Ying; Li, Cao; Liu, Linhai; Jia, Xianbo; Lai, Song-Jia

2016-01-01

Although various computer tools have been elaborately developed to calculate a series of statistics in molecular population genetics for both small- and large-scale DNA data, there is no efficient and easy-to-use toolkit available yet for exclusively focusing on the steps of mathematical calculation. Here, we present PopSc, a bioinformatic toolkit for calculating 45 basic statistics in molecular population genetics, which could be categorized into three classes, including (i) genetic diversity of DNA sequences, (ii) statistical tests for neutral evolution, and (iii) measures of genetic differentiation among populations. In contrast to the existing computer tools, PopSc was designed to directly accept the intermediate metadata, such as allele frequencies, rather than the raw DNA sequences or genotyping results. PopSc is first implemented as the web-based calculator with user-friendly interface, which greatly facilitates the teaching of population genetics in class and also promotes the convenient and straightforward calculation of statistics in research. Additionally, we also provide the Python library and R package of PopSc, which can be flexibly integrated into other advanced bioinformatic packages of population genetics analysis.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Paroxysmal atrial fibrillation prediction method with shorter HRV sequences.

PubMed

Boon, K H; Khalil-Hani, M; Malarvili, M B; Sia, C W

2016-10-01

This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF), using heart rate variability (HRV) segments that are shorter than those applied in existing methods, while maintaining good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to stabilize (electrically) and prevent the onset of atrial arrhythmias with different pacing techniques. We investigate the effect of HRV features extracted from different lengths of HRV segments prior to PAF onset with the proposed PAF prediction method. The pre-processing stage of the predictor includes QRS detection, HRV quantification and ectopic beat correction. Time-domain, frequency-domain, non-linear and bispectrum features are then extracted from the quantified HRV. In the feature selection, the HRV feature set and classifier parameters are optimized simultaneously using an optimization procedure based on genetic algorithm (GA). Both full feature set and statistically significant feature subset are optimized by GA respectively. For the statistically significant feature subset, Mann-Whitney U test is used to filter non-statistical significance features that cannot pass the statistical test at 20% significant level. The final stage of our predictor is the classifier that is based on support vector machine (SVM). A 10-fold cross-validation is applied in performance evaluation, and the proposed method achieves 79.3% prediction accuracy using 15-minutes HRV segment. This accuracy is comparable to that achieved by existing methods that use 30-minutes HRV segments, most of which achieves accuracy of around 80%. More importantly, our method significantly outperforms those that applied segments shorter than 30 minutes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Control chart pattern recognition using RBF neural network with new training algorithm and practical features.

PubMed

Addeh, Abdoljalil; Khormali, Aminollah; Golilarz, Noorbakhsh Amiri

2018-05-04

The control chart patterns are the most commonly used statistical process control (SPC) tools to monitor process changes. When a control chart produces an out-of-control signal, this means that the process has been changed. In this study, a new method based on optimized radial basis function neural network (RBFNN) is proposed for control chart patterns (CCPs) recognition. The proposed method consists of four main modules: feature extraction, feature selection, classification and learning algorithm. In the feature extraction module, shape and statistical features are used. Recently, various shape and statistical features have been presented for the CCPs recognition. In the feature selection module, the association rules (AR) method has been employed to select the best set of the shape and statistical features. In the classifier section, RBFNN is used and finally, in RBFNN, learning algorithm has a high impact on the network performance. Therefore, a new learning algorithm based on the bees algorithm has been used in the learning module. Most studies have considered only six patterns: Normal, Cyclic, Increasing Trend, Decreasing Trend, Upward Shift and Downward Shift. Since three patterns namely Normal, Stratification, and Systematic are very similar to each other and distinguishing them is very difficult, in most studies Stratification and Systematic have not been considered. Regarding to the continuous monitoring and control over the production process and the exact type detection of the problem encountered during the production process, eight patterns have been investigated in this study. The proposed method is tested on a dataset containing 1600 samples (200 samples from each pattern) and the results showed that the proposed method has a very good performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Predictive capabilities of statistical learning methods for lung nodule malignancy classification using diagnostic image features: an investigation using the Lung Image Database Consortium dataset

NASA Astrophysics Data System (ADS)

Hancock, Matthew C.; Magnan, Jerry F.

2017-03-01

To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capabilities of statistical learning methods for classifying nodule malignancy, utilizing the Lung Image Database Consortium (LIDC) dataset, and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that is achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (+/-1.14)% which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (+/-0.012), which increases to 0.949 (+/-0.007) when diameter and volume features are included, along with the accuracy to 88.08 (+/-1.11)%. Our results are comparable to those in the literature that use algorithmically-derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features, and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.

Views of medical students: what, when and how do they want statistics taught?

PubMed

Fielding, S; Poobalan, A; Prescott, G J; Marais, D; Aucott, L

2015-11-01

A key skill for a practising clinician is being able to do research, understand the statistical analyses and interpret results in the medical literature. Basic statistics has become essential within medical education, but when, what and in which format is uncertain. To inform curriculum design/development we undertook a quantitative survey of fifth year medical students and followed them up with a series of focus groups to obtain their opinions as to what statistics teaching they want, when and how. A total of 145 students undertook the survey and five focus groups were held with between 3 and 9 participants each. Previous statistical training varied and students recognised their knowledge was inadequate and keen to see additional training implemented. Students were aware of the importance of statistics to their future careers, but apprehensive about learning. Face-to-face teaching supported by online resources was popular. Focus groups indicated the need for statistical training early in their degree and highlighted their lack of confidence and inconsistencies in support. The study found that the students see the importance of statistics training in the medical curriculum but that timing and mode of delivery are key. The findings have informed the design of a new course to be implemented in the third undergraduate year. Teaching will be based around published studies aiming to equip students with the basics required with additional resources available through a virtual learning environment. © The Author(s) 2015.

A generalized concept for cost-effective structural design. [Statistical Decision Theory applied to aerospace systems

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Hawk, J. D.

1975-01-01

A generalized concept for cost-effective structural design is introduced. It is assumed that decisions affecting the cost effectiveness of aerospace structures fall into three basic categories: design, verification, and operation. Within these basic categories, certain decisions concerning items such as design configuration, safety factors, testing methods, and operational constraints are to be made. All or some of the variables affecting these decisions may be treated probabilistically. Bayesian statistical decision theory is used as the tool for determining the cost optimum decisions. A special case of the general problem is derived herein, and some very useful parametric curves are developed and applied to several sample structures.

On a Quantum Model of Brain Activities

NASA Astrophysics Data System (ADS)

Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

2010-01-01

One of the main activities of the brain is the recognition of signals. A first attempt to explain the process of recognition in terms of quantum statistics was given in [6]. Subsequently, details of the mathematical model were presented in a (still incomplete) series of papers (cf. [7, 2, 5, 10]). In the present note we want to give a general view of the principal ideas of this approach. We will introduce the basic spaces and justify the choice of spaces and operations. Further, we bring the model face to face with basic postulates any statistical model of the recognition process should fulfill. These postulates are in accordance with the opinion widely accepted in psychology and neurology.

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics

PubMed Central

Allen, Peter J.; Dorozenko, Kate P.; Roberts, Lynne D.

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these “experts” were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an “answer.” Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities. PMID:26909064

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics.

PubMed

Allen, Peter J; Dorozenko, Kate P; Roberts, Lynne D

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these "experts" were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an "answer." Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities.

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

NASA Astrophysics Data System (ADS)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)

Learning representations for the early detection of sepsis with deep neural networks.

PubMed

Kam, Hye Jin; Kim, Ha Young

2017-10-01

Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens. This study aimed to develop detection models for the early stage of sepsis using deep learning methodologies, and to compare the feasibility and performance of the new deep learning methodology with those of the regression method with conventional temporal feature extraction. Study group selection adhered to the InSight model. The results of the deep learning-based models and the InSight model were compared. With deep feedforward networks, the area under the ROC curve (AUC) of the models were 0.887 and 0.915 for the InSight and the new feature sets, respectively. For the model with the combined feature set, the AUC was the same as that of the basic feature set (0.915). For the long short-term memory model, only the basic feature set was applied and the AUC improved to 0.929 compared with the existing 0.887 of the InSight model. The contributions of this paper can be summarized in three ways: (i) improved performance without feature extraction using domain knowledge, (ii) verification of feature extraction capability of deep neural networks through comparison with reference features, and (iii) improved performance with feedforward neural networks using long short-term memory, a neural network architecture that can learn sequential patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design and grayscale fabrication of beamfanners in a silicon substrate

NASA Astrophysics Data System (ADS)

Ellis, Arthur Cecil

2001-11-01

This dissertation addresses important first steps in the development of a grayscale fabrication process for multiple phase diffractive optical elements (DOS's) in silicon. Specifically, this process was developed through the design, fabrication, and testing of 1-2 and 1-4 beamfanner arrays for 5-micron illumination. The 1-2 beamfanner arrays serve as a test-of- concept and basic developmental step toward the construction of the 1-4 beamfanners. The beamfanners are 50 microns wide, and have features with dimensions of between 2 and 10 microns. The Iterative Annular Spectrum Approach (IASA) method, developed by Steve Mellin of UAH, and the Boundary Element Method (BEM) are the design and testing tools used to create the beamfanner profiles and predict their performance. Fabrication of the beamfanners required the techniques of grayscale photolithography and reactive ion etching (RIE). A 2-3micron feature size 1-4 silicon beamfanner array was fabricated, but the small features and contact photolithographic techniques available prevented its construction to specifications. A second and more successful attempt was made in which both 1-4 and 1-2 beamfanner arrays were fabricated with a 5-micron minimum feature size. Photolithography for the UAH array was contracted to MEMS-Optical of Huntsville, Alabama. A repeatability study was performed, using statistical techniques, of 14 photoresist arrays and the subsequent RIE process used to etch the arrays in silicon. The variance in selectivity between the 14 processes was far greater than the variance between the individual etched features within each process. Specifically, the ratio of the variance of the selectivities averaged over each of the 14 etch processes to the variance of individual feature selectivities within the processes yielded a significance level below 0.1% by F-test, indicating that good etch-to-etch process repeatability was not attained. One of the 14 arrays had feature etch-depths close enough to design specifications for optical testing, but 5- micron IR illumination of the 1-4 and 1-2 beamfanners yielded no convincing results of beam splitting in the detector plane 340 microns from the surface of the beamfanner array.

Expanding the Library of Uranyl Amide Derivatives: New Complexes Featuring the tert-Butyldimethylsilylamide Ligand.

PubMed

Pattenaude, Scott A; Coughlin, Ezra J; Collins, Tyler S; Zeller, Matthias; Bart, Suzanne C

2018-04-16

New uranyl derivatives featuring the amide ligand, -N(SiHMe 2 ) t Bu, were synthesized and characterized by X-ray crystallography, multinuclear NMR spectroscopy, and absorption spectroscopies. Steric properties of these complexes were also quantified using the computational program Solid-G. The increased basicity of the free ligand -N(SiHMe 2 ) t Bu was demonstrated by direct comparison to -N(SiMe 3 ) 2 , a popular supporting ligand for uranyl. Substitutional lability on a uranyl center was also demonstrated by exchange with the -N(SiMe 3 ) 2 ligand. The increased basicity of this ligand and diverse characterization handles discussed here will make these compounds useful synthons for future reactivity.

Conventional Radiology in Crystal Arthritis: Gout, Calcium Pyrophosphate Deposition, and Basic Calcium Phosphate Crystals.

PubMed

Jacques, Thibaut; Michelin, Paul; Badr, Sammy; Nasuto, Michelangelo; Lefebvre, Guillaume; Larkman, Neal; Cotten, Anne

2017-09-01

This article reviews the main radiographic features of crystal deposition diseases. Gout is linked to monosodium urate crystals. Classic radiographic features include subcutaneous tophi, large and well-circumscribed paraarticular bone erosions, and exuberant bone hyperostosis. Calcium pyrophosphate deposition (CPPD) can involve numerous structures, such as hyaline cartilages, fibrocartilages, or tendons. CPPD arthropathy involves joints usually spared by osteoarthritis. Basic calcium phosphate deposits are periarticular or intraarticular. Periarticular calcifications are amorphous, dense, and round or oval with well-limited borders, and most are asymptomatic. When resorbing, they become cloudy and less dense with an ill-defined shape and can migrate into adjacent structures. Copyright © 2017 Elsevier Inc. All rights reserved.

Usage Statistics

MedlinePlus

... this page: https://medlineplus.gov/usestatistics.html MedlinePlus Statistics To use the sharing features on this page, ... By Quarter View image full size Quarterly User Statistics Quarter Page Views Unique Visitors Oct-Dec-98 ...

Innovations in curriculum design: A multi-disciplinary approach to teaching statistics to undergraduate medical students

PubMed Central

Freeman, Jenny V; Collier, Steve; Staniforth, David; Smith, Kevin J

2008-01-01

Background Statistics is relevant to students and practitioners in medicine and health sciences and is increasingly taught as part of the medical curriculum. However, it is common for students to dislike and under-perform in statistics. We sought to address these issues by redesigning the way that statistics is taught. Methods The project brought together a statistician, clinician and educational experts to re-conceptualize the syllabus, and focused on developing different methods of delivery. New teaching materials, including videos, animations and contextualized workbooks were designed and produced, placing greater emphasis on applying statistics and interpreting data. Results Two cohorts of students were evaluated, one with old style and one with new style teaching. Both were similar with respect to age, gender and previous level of statistics. Students who were taught using the new approach could better define the key concepts of p-value and confidence interval (p < 0.001 for both). They were more likely to regard statistics as integral to medical practice (p = 0.03), and to expect to use it in their medical career (p = 0.003). There was no significant difference in the numbers who thought that statistics was essential to understand the literature (p = 0.28) and those who felt comfortable with the basics of statistics (p = 0.06). More than half the students in both cohorts felt that they were comfortable with the basics of medical statistics. Conclusion Using a variety of media, and placing emphasis on interpretation can help make teaching, learning and understanding of statistics more people-centred and relevant, resulting in better outcomes for students. PMID:18452599

A Discussion of the Measurement and Statistical Manipulation of Selected Key Variables in an Adult Basic Education Program.

ERIC Educational Resources Information Center

Cunningham, Phyllis M.

Intending to explore the interaction effects of self-esteem level and perceived program utility on the retention and cognitive achievement of adult basic education students, a self-esteem instrument, to be administered verbally, was constructed with content relevant items developed from and tested on a working class, undereducated, black, adult…

A Quantile Regression Approach to Understanding the Relations among Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

ERIC Educational Resources Information Center

Tighe, Elizabeth L.; Schatschneider, Christopher

2016-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological…

Development of Computer Play Pedagogy Intervention for Children with Low Conceptual Understanding in Basic Mathematics Operation Using the Dyscalculia Feature Approach

ERIC Educational Resources Information Center

Mohd Syah, Nor Elleeiana; Hamzaid, Nur Azah; Murphy, Belinda Pingguan; Lim, Einly

2016-01-01

This study describes the development of a basic computer-based play pedagogy intervention using a dyscalculia-remedy-oriented approach such as repetition and number orientation manipulation, and the investigation of its effect on children displaying dyscalculia characteristics. This computer play was evaluated in a group of 50 seven-year-old…

In this issue: from basic immunology to oncogenesis and inflammation.

PubMed

Bot, Adrian

2013-06-01

This issue of the International Reviews of Immunology features very diverse topics from basic immunology to inflammation, oncogenesis and immunopathology. Specifically, this volume hosts reviews describing the role of TCRγδ T cells, the significance of Epstein Barr virus-associated miRNAs and the genetic basis of Hashimoto's thyroiditis along with other reviews on the topics mentioned above.

Summary Statistics of CPB-Qualified Public Radio Stations: Fiscal Year 1971.

ERIC Educational Resources Information Center

Lee, S. Young; Pedone, Ronald J.

Basic statistics on finance, employment, and broadcast and production activities of 103 Corporation for Public Broadcasting (CPB)--qualified radio stations in the United States and Puerto Rico for Fiscal Year 1971 are collected. The first section of the report deals with total funds, income, direct operating costs, capital expenditures, and other…

Using Statistics to Lie, Distort, and Abuse Data

ERIC Educational Resources Information Center

Bintz, William; Moore, Sara; Adams, Cheryll; Pierce, Rebecca

2009-01-01

Statistics is a branch of mathematics that involves organization, presentation, and interpretation of data, both quantitative and qualitative. Data do not lie, but people do. On the surface, quantitative data are basically inanimate objects, nothing more than lifeless and meaningless symbols that appear on a page, calculator, computer, or in one's…

What Software to Use in the Teaching of Mathematical Subjects?

ERIC Educational Resources Information Center

Berežný, Štefan

2015-01-01

We can consider two basic views, when using mathematical software in the teaching of mathematical subjects. First: How to learn to use specific software for the specific tasks, e. g., software Statistica for the subjects of Applied statistics, probability and mathematical statistics, or financial mathematics. Second: How to learn to use the…

Intrex Subject/Title Inverted-File Characteristics.

ERIC Educational Resources Information Center

Uemura, Syunsuke

The characteristics of the Intrex subject/title inverted file are analyzed. Basic statistics of the inverted file are presented including various distributions of the index words and terms from which the file was derived, and statistics on stems, the file growth process, and redundancy measurements. A study of stems both with extremely high and…

The Robustness of the Studentized Range Statistic to Violations of the Normality and Homogeneity of Variance Assumptions.

ERIC Educational Resources Information Center

Ramseyer, Gary C.; Tcheng, Tse-Kia

The present study was directed at determining the extent to which the Type I Error rate is affected by violations in the basic assumptions of the q statistic. Monte Carlo methods were employed, and a variety of departures from the assumptions were examined. (Author)

Application of an Online Reference for Reviewing Basic Statistical Principles of Operating Room Management

ERIC Educational Resources Information Center

Dexter, Franklin; Masursky, Danielle; Wachtel, Ruth E.; Nussmeier, Nancy A.

2010-01-01

Operating room (OR) management differs from clinical anesthesia in that statistical literacy is needed daily to make good decisions. Two of the authors teach a course in operations research for surgical services to anesthesiologists, anesthesia residents, OR nursing directors, hospital administration students, and analysts to provide them with the…

Statistics and Data Interpretation for Social Work

ERIC Educational Resources Information Center

Rosenthal, James A.

2011-01-01

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

Using Excel in Teacher Education for Sustainability

ERIC Educational Resources Information Center

Aydin, Serhat

2016-01-01

In this study, the feasibility of using Excel software in teaching whole Basic Statistics Course and its influence on the attitudes of pre-service science teachers towards statistics were investigated. One hundred and two pre-service science teachers in their second year participated in the study. The data were collected from the prospective…

Basic Math Skills and Performance in an Introductory Statistics Course

ERIC Educational Resources Information Center

Johnson, Marianne; Kuennen, Eric

2006-01-01

We identify the student characteristics most associated with success in an introductory business statistics class, placing special focus on the relationship between student math skills and course performance, as measured by student grade in the course. To determine which math skills are important for student success, we examine (1) whether the…

An Online Course of Business Statistics: The Proportion of Successful Students

ERIC Educational Resources Information Center

Pena-Sanchez, Rolando

2009-01-01

This article describes the students' academic progress in an online course of business statistics through interactive software assignments and diverse educational homework, which helps these students to build their own e-learning through basic competences; i.e. interpreting results and solving problems. Cross-tables were built for the categorical…

School Violence: Data & Statistics

MedlinePlus

... Data LGB Youth Report School Violence Featured Topic: Bullying Research Featured Topic: Prevent Gang Membership Featured Topic: ... report covers topics such as victimization, teacher injury, bullying, school conditions, fights, weapons, and student use of ...

Foreign Language and Business. A Lifelong Experience.

ERIC Educational Resources Information Center

Fryer, T. Bruce

The Masters Degree in International Business Program at the University of South Carolina, begun in June 1974, has as its unique feature the emphasis on "lifelong experience." This emphasis affects both the student and the department. From the first year of the program (the basic features of which are intensive training in language,…

Newborns' Mooney-Face Perception

ERIC Educational Resources Information Center

Leo, Irene; Simion, Francesca

2009-01-01

The aim of this study is to investigate whether newborns detect a face on the basis of a Gestalt representation based on first-order relational information (i.e., the basic arrangement of face features) by using Mooney stimuli. The incomplete 2-tone Mooney stimuli were used because they preclude focusing both on the local features (i.e., the fine…

Essential Information for Post-Encyclopaedic Parliaments: The Italian Case.

ERIC Educational Resources Information Center

Rizzoni, Giovanni

This paper discusses the experiences of the Research Department of the Italian Chamber of Deputies over the past few years. The first section describes the origin of the department in the 1970s, including political factors, basic organizational features, and the salient features of the department's activity. The second section addresses the…

Basic Visual Merchandising. Second Edition. [Student's Manual and] Answer Book/Teacher's Guide.

ERIC Educational Resources Information Center

Luter, Robert R.

This student's manual that features content needed to do tasks related to visual merchandising is intended for students in co-op training stations and entry-level, master employee, and supervisory-level employees. It contains 13 assignments. Each assignment has questions covering specific information and also features activities in which students…

Person-Centered Planning with Youth and Adults Who Have Developmental Disabilities.

ERIC Educational Resources Information Center

Impact, 1998

1998-01-01

This feature issue of "Impact" focuses on person-centered planning with youth and adults who have developmental disabilities. Featured articles include: (1) "Centering on People: A Quiet Revolution" (Judith A. Snow); (2) "Look-and Understand-before You Leap" (Brian Abery and Marijo McBride), which describes the basic principles and values…

Experimental Methodology in English Teaching and Learning: Method Features, Validity Issues, and Embedded Experimental Design

ERIC Educational Resources Information Center

Lee, Jang Ho

2012-01-01

Experimental methods have played a significant role in the growth of English teaching and learning studies. The paper presented here outlines basic features of experimental design, including the manipulation of independent variables, the role and practicality of randomised controlled trials (RCTs) in educational research, and alternative methods…

Playing with Plug-ins

ERIC Educational Resources Information Center

Thompson, Douglas E.

2013-01-01

In today's complex music software packages, many features can remain unexplored and unused. Software plug-ins--available in most every music software package, yet easily overlooked in the software's basic operations--are one such feature. In this article, I introduce readers to plug-ins and offer tips for purchasing plug-ins I have…

The Chesapeake: A Boating Guide to Weather. Educational Series Number 25.

ERIC Educational Resources Information Center

Lucy, Jon; And Others

The purpose of this publication is to promote a better understanding of how basic weather features develop on Chesapeake Bay and enable boaters to enjoy the Bay's unique waterways. Sections include: (1) Chesapeake Bay climate; (2) general weather features; (3) seasonal trends; (4) sources of weather information and forecasts; (5) weather service…

Features versus context: An approach for precise and detailed detection and delineation of faces and facial features.

PubMed

Ding, Liya; Martinez, Aleix M

2010-11-01

The appearance-based approach to face detection has seen great advances in the last several years. In this approach, we learn the image statistics describing the texture pattern (appearance) of the object class we want to detect, e.g., the face. However, this approach has had limited success in providing an accurate and detailed description of the internal facial features, i.e., eyes, brows, nose, and mouth. In general, this is due to the limited information carried by the learned statistical model. While the face template is relatively rich in texture, facial features (e.g., eyes, nose, and mouth) do not carry enough discriminative information to tell them apart from all possible background images. We resolve this problem by adding the context information of each facial feature in the design of the statistical model. In the proposed approach, the context information defines the image statistics most correlated with the surroundings of each facial component. This means that when we search for a face or facial feature, we look for those locations which most resemble the feature yet are most dissimilar to its context. This dissimilarity with the context features forces the detector to gravitate toward an accurate estimate of the position of the facial feature. Learning to discriminate between feature and context templates is difficult, however, because the context and the texture of the facial features vary widely under changing expression, pose, and illumination, and may even resemble one another. We address this problem with the use of subclass divisions. We derive two algorithms to automatically divide the training samples of each facial feature into a set of subclasses, each representing a distinct construction of the same facial component (e.g., closed versus open eyes) or its context (e.g., different hairstyles). The first algorithm is based on a discriminant analysis formulation. The second algorithm is an extension of the AdaBoost approach. We provide extensive experimental results using still images and video sequences for a total of 3,930 images. We show that the results are almost as good as those obtained with manual detection.

[To strengthen the education on basic knowledge and skills of neuro-ophthalmology].

PubMed

Zhang, Xiao-jun; Wang, Ning-li

2011-12-01

Basic knowledge and skills are cornerstone of the diagnosis and treatment of neuro-ophthalmology diseases in ophthalmology practice. Due to the interdisciplinary features of neuro-ophthalmology, neuro-anatomy, neuro-physiology related to eyes, neuro-image and neuro-electrodiagnosis, these should be included in the education for the ophthalmologist. Special attention should be paid to training on capability of logically thinking in neuro-ophthalmology. Multiple ways can be used for the education of ophthalmologists and neurologists for the enhancement of basic knowledge and skills of neuro-ophthalmology in China.

Health Literacy Impact on National Healthcare Utilization and Expenditure.

PubMed

Rasu, Rafia S; Bawa, Walter Agbor; Suminski, Richard; Snella, Kathleen; Warady, Bradley

2015-08-17

Health literacy presents an enormous challenge in the delivery of effective healthcare and quality outcomes. We evaluated the impact of low health literacy (LHL) on healthcare utilization and healthcare expenditure. Database analysis used Medical Expenditure Panel Survey (MEPS) from 2005-2008 which provides nationally representative estimates of healthcare utilization and expenditure. Health literacy scores (HLSs) were calculated based on a validated, predictive model and were scored according to the National Assessment of Adult Literacy (NAAL). HLS ranged from 0-500. Health literacy level (HLL) and categorized in 2 groups: Below basic or basic (HLS <226) and above basic (HLS ≥226). Healthcare utilization expressed as a physician, nonphysician, or emergency room (ER) visits and healthcare spending. Expenditures were adjusted to 2010 rates using the Consumer Price Index (CPI). A P value of 0.05 or less was the criterion for statistical significance in all analyses. Multivariate regression models assessed the impact of the predicted HLLs on outpatient healthcare utilization and expenditures. All analyses were performed with SAS and STATA® 11.0 statistical software. The study evaluated 22 599 samples representing 503 374 648 weighted individuals nationally from 2005-2008. The cohort had an average age of 49 years and included more females (57%). Caucasian were the predominant racial ethnic group (83%) and 37% of the cohort were from the South region of the United States of America. The proportion of the cohort with basic or below basic health literacy was 22.4%. Annual predicted values of physician visits, nonphysician visits, and ER visits were 6.6, 4.8, and 0.2, respectively, for basic or below basic compared to 4.4, 2.6, and 0.1 for above basic. Predicted values of office and ER visits expenditures were $1284 and $151, respectively, for basic or below basic and $719 and $100 for above basic (P < .05). The extrapolated national estimates show that the annual costs for prescription alone for adults with LHL possibly associated with basic and below basic health literacy could potentially reach about $172 billion. Health literacy is inversely associated with healthcare utilization and expenditure. Individuals with below basic or basic HLL have greater healthcare utilization and expendituresspending more on prescriptions compared to individuals with above basic HLL. Public health strategies promoting appropriate education among individuals with LHL may help to improve health outcomes and reduce unnecessary healthcare visits and costs. © 2015 by Kerman University of Medical Sciences.

Knowledge, attitude and anxiety pertaining to basic life support and medical emergencies among dental interns in Mangalore City, India.

PubMed

Somaraj, Vinej; Shenoy, Rekha P; Panchmal, Ganesh Shenoy; Jodalli, Praveen S; Sonde, Laxminarayan; Karkal, Ravichandra

2017-01-01

This cross-sectional study aimed to assess the knowledge, attitude and anxiety pertaining to basic life support (BLS) and medical emergencies among interns in dental colleges of Mangalore city, Karnataka, India. The study subjects comprised of interns who volunteered from the four dental colleges. The knowledge and attitude of interns were assessed using a 30-item questionnaire prepared based on the Basic Life Support Manual from American Heart Association and the anxiety of interns pertaining to BLS and medical emergencies were assessed using a State-Trait Anxiety Inventory (STAI) Questionnaire. Chi-square test was performed on SPSS 21.0 (IBM Statistics, 2012) to determine statistically significant differences ( P <0.05) between assessed knowledge and anxiety. Out of 183 interns, 39.89% had below average knowledge. A total of 123 (67.21%) reported unavailability of professional training. The majority (180, 98.36%) felt the urgent need of training in basic life support procedures. Assessment of stress showed a total of 27.1% participants to be above high-stress level. Comparison of assessed knowledge and stress was found to be insignificant ( P =0.983). There was an evident lack of knowledge pertaining to the management of medical emergencies among the interns. As oral health care providers moving out to the society, a focus should be placed on the training of dental interns with respect to Basic Life Support procedures.

The Research of Feature Extraction Method of Liver Pathological Image Based on Multispatial Mapping and Statistical Properties

PubMed Central

Liu, Huiling; Xia, Bingbing; Yi, Dehui

2016-01-01

We propose a new feature extraction method of liver pathological image based on multispatial mapping and statistical properties. For liver pathological images of Hematein Eosin staining, the image of R and B channels can reflect the sensitivity of liver pathological images better, while the entropy space and Local Binary Pattern (LBP) space can reflect the texture features of the image better. To obtain the more comprehensive information, we map liver pathological images to the entropy space, LBP space, R space, and B space. The traditional Higher Order Local Autocorrelation Coefficients (HLAC) cannot reflect the overall information of the image, so we propose an average correction HLAC feature. We calculate the statistical properties and the average gray value of pathological images and then update the current pixel value as the absolute value of the difference between the current pixel gray value and the average gray value, which can be more sensitive to the gray value changes of pathological images. Lastly the HLAC template is used to calculate the features of the updated image. The experiment results show that the improved features of the multispatial mapping have the better classification performance for the liver cancer. PMID:27022407

Prediction of near-term breast cancer risk using local region-based bilateral asymmetry features in mammography

NASA Astrophysics Data System (ADS)

Li, Yane; Fan, Ming; Li, Lihua; Zheng, Bin

2017-03-01

This study proposed a near-term breast cancer risk assessment model based on local region bilateral asymmetry features in Mammography. The database includes 566 cases who underwent at least two sequential FFDM examinations. The `prior' examination in the two series all interpreted as negative (not recalled). In the "current" examination, 283 women were diagnosed cancers and 283 remained negative. Age of cancers and negative cases completely matched. These cases were divided into three subgroups according to age: 152 cases among the 37-49 age-bracket, 220 cases in the age-bracket 50- 60, and 194 cases with the 61-86 age-bracket. For each image, two local regions including strip-based regions and difference-of-Gaussian basic element regions were segmented. After that, structural variation features among pixel values and structural similarity features were computed for strip regions. Meanwhile, positional features were extracted for basic element regions. The absolute subtraction value was computed between each feature of the left and right local-regions. Next, a multi-layer perception classifier was implemented to assess performance of features for prediction. Features were then selected according stepwise regression analysis. The AUC achieved 0.72, 0.75 and 0.71 for these 3 age-based subgroups, respectively. The maximum adjustable odds ratios were 12.4, 20.56 and 4.91 for these three groups, respectively. This study demonstrate that the local region-based bilateral asymmetry features extracted from CC-view mammography could provide useful information to predict near-term breast cancer risk.

Research in image management and access

NASA Technical Reports Server (NTRS)

Vondran, Raymond F.; Barron, Billy J.

1993-01-01

Presently, the problem of over-all library system design has been compounded by the accretion of both function and structure to a basic framework of requirements. While more device power has led to increased functionality, opportunities for reducing system complexity at the user interface level have not always been pursued with equal zeal. The purpose of this book is therefore to set forth and examine these opportunities, within the general framework of human factors research in man-machine interfaces. Human factors may be viewed as a series of trade-off decisions among four polarized objectives: machine resources and user specifications; functionality and user requirements. In the past, a limiting factor was the availability of systems. However, in the last two years, over one hundred libraries supported by many different software configurations have been added to the Internet. This document includes a statistical analysis of human responses to five Internet library systems by key features, development of the ideal online catalog system, and ideal online catalog systems for libraries and information centers.

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.

Risk management of key issues of FPSO

NASA Astrophysics Data System (ADS)

Sun, Liping; Sun, Hai

2012-12-01

Risk analysis of key systems have become a growing topic late of because of the development of offshore structures. Equipment failures of offloading system and fire accidents were analyzed based on the floating production, storage and offloading (FPSO) features. Fault tree analysis (FTA), and failure modes and effects analysis (FMEA) methods were examined based on information already researched on modules of relex reliability studio (RRS). Equipment failures were also analyzed qualitatively by establishing a fault tree and Boolean structure function based on the shortage of failure cases, statistical data, and risk control measures examined. Failure modes of fire accident were classified according to the different areas of fire occurrences during the FMEA process, using risk priority number (RPN) methods to evaluate their severity rank. The qualitative analysis of FTA gave the basic insight of forming the failure modes of FPSO offloading, and the fire FMEA gave the priorities and suggested processes. The research has practical importance for the security analysis problems of FPSO.

Biomedical imaging and sensing using flatbed scanners.

PubMed

Göröcs, Zoltán; Ozcan, Aydogan

2014-09-07

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Equations of state for explosive detonation products: The PANDA model

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

Kerley, G.I.

1994-05-01

This paper discusses a thermochemical model for calculating equations of state (EOS) for the detonation products of explosives. This model, which was first presented at the Eighth Detonation Symposium, is available in the PANDA code and is referred to here as ``the Panda model``. The basic features of the PANDA model are as follows. (1) Statistical-mechanical theories are used to construct EOS tables for each of the chemical species that are to be allowed in the detonation products. (2) The ideal mixing model is used to compute the thermodynamic functions for a mixture of these species, and the composition ofmore » the system is determined from assumption of chemical equilibrium. (3) For hydrocode calculations, the detonation product EOS are used in tabular form, together with a reactive burn model that allows description of shock-induced initiation and growth or failure as well as ideal detonation wave propagation. This model has been implemented in the three-dimensional Eulerian code, CTH.« less

Microscopic origin and macroscopic implications of lane formation in mixtures of oppositely-driven particles

NASA Astrophysics Data System (ADS)

Whitelam, Stephen

Colloidal particles of two types, driven in opposite directions, can segregate into lanes. I will describe some results on this phenomenon obtained by simple physical arguments and computer simulations. Laning results from rectification of diffusion on the scale of a particle diameter: oppositely-driven particles must, in the time taken to encounter each other in the direction of the drive, diffuse in the perpendicular direction by about one particle diameter. This geometric constraint implies that the diffusion constant of a particle, in the presence of those of the opposite type, grows approximately linearly with Peclet number, a prediction confirmed by our numerics. Such environment-dependent diffusion is statistically similar to an effective interparticle attraction; consistent with this observation, we find that oppositely-driven colloids display features characteristic of the simplest model system possessing both interparticle attractions and persistent motion, the driven Ising lattice gas. Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Modeling the Solar Convective Dynamo and Emerging Flux

NASA Astrophysics Data System (ADS)

Fan, Y.

2017-12-01

Significant advances have been made in recent years in global-scale fully dynamic three-dimensional convective dynamo simulations of the solar/stellar convective envelopes to reproduce some of the basic features of the Sun's large-scale cyclic magnetic field. It is found that the presence of the dynamo-generated magnetic fields plays an important role for the maintenance of the solar differential rotation, without which the differential rotation tends to become anti-solar (with a faster rotating pole instead of the observed faster rotation at the equator). Convective dynamo simulations are also found to produce emergence of coherent super-equipartition toroidal flux bundles with a statistically significant mean tilt angle that is consistent with the mean tilt of solar active regions. The emerging flux bundles are sheared by the giant cell convection into a forward leaning loop shape with its leading side (in the direction of rotation) pushed closer to the strong downflow lanes. Such asymmetric emerging flux pattern may lead to the observed asymmetric properties of solar active regions.

Biomedical Imaging and Sensing using Flatbed Scanners

PubMed Central

Göröcs, Zoltán; Ozcan, Aydogan

2014-01-01

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600–700 cm2) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings. PMID:24965011

Global characteristics of zonal flows due to the effect of finite bandwidth in drift wave turbulence

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

Uzawa, K.; Li Jiquan; Kishimoto, Y.

2009-04-15

The spectral effect of the zonal flow (ZF) on its generation is investigated based on the Charney-Hasegawa-Mima turbulence model. It is found that the effect of finite ZF bandwidth qualitatively changes the characteristics of ZF instability. A spatially localized (namely, global) nonlinear ZF state with an enhanced, unique growth rate for all spectral components is created under a given turbulent fluctuation. It is identified that such state originates from the successive cross couplings among Fourier components of the ZF and turbulence spectra through the sideband modulation. Furthermore, it is observed that the growth rate of the global ZF is determinedmore » not only by the spectral distribution and amplitudes of turbulent pumps as usual, but also statistically by the turbulence structure, namely, their probabilistic initial phase factors. A ten-wave coupling model of the ZF modulation instability involving the essential effect of the ZF spectrum is developed to clarify the basic features of the global nonlinear ZF state.« less

Neuroimaging in aphasia treatment research: Consensus and practical guidelines for data analysis

PubMed Central

Meinzer, Marcus; Beeson, Pélagie M.; Cappa, Stefano; Crinion, Jenny; Kiran, Swathi; Saur, Dorothee; Parrish, Todd; Crosson, Bruce; Thompson, Cynthia K.

2012-01-01

Functional magnetic resonance imaging is the most widely used imaging technique to study treatment-induced recovery in post-stroke aphasia. The longitudinal design of such studies adds to the challenges researchers face when studying patient populations with brain damage in cross-sectional settings. The present review focuses on issues specifically relevant to neuroimaging data analysis in aphasia treatment research identified in discussions among international researchers at the Neuroimaging in Aphasia Treatment Research Workshop held at Northwestern University (Evanston, Illinois, USA). In particular, we aim to provide the reader with a critical review of unique problems related to the pre-processing, statistical modeling and interpretation of such data sets. Despite the fact that data analysis procedures critically depend on specific design features of a given study, we aim to discuss and communicate a basic set of practical guidelines that should be applicable to a wide range of studies and useful as a reference for researchers pursuing this line of research. PMID:22387474

Quark-Gluon Plasma

NASA Astrophysics Data System (ADS)

Sinha, Bikash; Pal, Santanu; Raha, Sibaji

Quark-Gluon Plasma (QGP) is a state of matter predicted by the theory of strong interactions - Quantum Chromodynamics (QCD). The area of QGP lies at the interface of particle physics, field theory, nuclear physics and many-body theory, statistical physics, cosmology and astrophysics. In its brief history (about a decade), QGP has seen a rapid convergence of ideas from these previously diverging disciplines. This volume includes the lectures delivered by eminent specialists to students without prior experience in QGP. Each course thus starts from the basics and takes the students by steps to the current problems. The chapters are self-contained and pedagogic in style. The book may therefore serve as an introduction for advanced graduate students intending to enter this field or for physicists working in other areas. Experts in QGP may also find this volume a handy reference. Specific examples, used to elucidate how theoretical predictions and experimentally accessible quantities may not always correspond to one another, make this book ideal for self-study for beginners. This feature will also make the volume thought-provoking for QGP practitioners.

Are emergency medical technician-basics able to use a selective immobilization of the cervical spine protocol?: a preliminary report.

PubMed

Dunn, Thomas M; Dalton, Alice; Dorfman, Todd; Dunn, William W

2004-01-01

To be a first step in determining whether emergency medicine technician (EMT)-Basics are capable of using a protocol that allows for selective immobilization of the cervical spine. Such protocols are coming into use at an advanced life support level and could be beneficial when used by basic life support providers. A convenience sample of participants (n=95) from 11 emergency medical services agencies and one college class participated in the study. All participants evaluated six patients in written scenarios and decided which should be placed into spinal precautions according to a selective spinal immobilization protocol. Systems without an existing selective spinal immobilization protocol received a one-hour continuing education lecture regarding the topic. College students received a similar lecture written so laypersons could understand the protocol. All participants showed proficiency when applying a selective immobilization protocol to patients in paper-based scenarios. Furthermore, EMT-Basics performed at the same level as paramedics when following the protocol. Statistical analysis revealed no significant differences between EMT-Basics and paramedics. A follow-up group of college students (added to have a non-EMS comparison group) also performed as well as paramedics when making decisions to use spinal precautions. Differences between college students and paramedics were also statistically insignificant. The results suggest that EMT-Basics are as accurate as paramedics when making decisions regarding selective immobilization of the cervical spine during paper-based scenarios. That laypersons are also proficient when using the protocol could indicate that it is extremely simple to follow. This study is a first step toward the necessary additional studies evaluating the efficacy of EMT-Basics using selective immobilization as a regular practice.

Dynamical Constraints On The Galaxy-Halo Connection

NASA Astrophysics Data System (ADS)

Desmond, Harry

2017-07-01

Dark matter halos comprise the bulk of the universe's mass, yet must be probed by the luminous galaxies that form within them. A key goal of modern astrophysics, therefore, is to robustly relate the visible and dark mass, which to first order means relating the properties of galaxies and halos. This may be expected not only to improve our knowledge of galaxy formation, but also to enable high-precision cosmological tests using galaxies and hence maximise the utility of future galaxy surveys. As halos are inaccessible to observations - as galaxies are to N-body simulations - this relation requires an additional modelling step.The aim of this thesis is to develop and evaluate models of the galaxy-halo connection using observations of galaxy dynamics. In particular, I build empirical models based on the technique of halo abundance matching for five key dynamical scaling relations of galaxies - the Tully-Fisher, Faber-Jackson, mass-size and mass discrepancy-acceleration relations, and Fundamental Plane - which relate their baryon distributions and rotation or velocity dispersion profiles. I then develop a statistical scheme based on approximate Bayesian computation to compare the predicted and measured values of a number of summary statistics describing the relations' important features. This not only provides quantitative constraints on the free parameters of the models, but also allows absolute goodness-of-fit measures to be formulated. I find some features to be naturally accounted for by an abundance matching approach and others to impose new constraints on the galaxy-halo connection; the remainder are challenging to account for and may imply galaxy-halo correlations beyond the scope of basic abundance matching.Besides providing concrete statistical tests of specific galaxy formation theories, these results will be of use for guiding the inputs of empirical and semi-analytic galaxy formation models, which require galaxy-halo correlations to be imposed by hand. As galaxy datasets become larger and more precise in the future, we may expect these methods to continue providing insight into the relation between the visible and dark matter content of the universe and the physical processes that underlie it.

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

SDAR 1.0 a New Quantitative Toolkit for Analyze Stratigraphic Data

NASA Astrophysics Data System (ADS)

Ortiz, John; Moreno, Carlos; Cardenas, Andres; Jaramillo, Carlos

2015-04-01

Since the foundation of stratigraphy geoscientists have recognized that data obtained from stratigraphic columns (SC), two dimensional schemes recording descriptions of both geological and paleontological features (e.g., thickness of rock packages, grain size, fossil and lithological components, and sedimentary structures), are key elements for establishing reliable hypotheses about the distribution in space and time of rock sequences, and ancient sedimentary environmental and paleobiological dynamics. Despite the tremendous advances on the way geoscientists store, plot, and quantitatively analyze sedimentological and paleontological data (e.g., Macrostrat [http://www.macrostrat.org/], Paleobiology Database [http://www.paleodb.org/], respectively), there is still a lack of computational methodologies designed to quantitatively examine data from a highly detailed SCs. Moreover, frequently the stratigraphic information is plotted "manually" using vector graphics editors (e.g., Corel Draw, Illustrator), however, this information although store on a digital format, cannot be used readily for any quantitative analysis. Therefore, any attempt to examine the stratigraphic data in an analytical fashion necessarily takes further steps. Given these issues, we have developed the sofware 'Stratigraphic Data Analysis in R' (SDAR), which stores in a database all sedimentological, stratigraphic, and paleontological information collected from a SC, allowing users to generate high-quality graphic plots (including one or multiple features stored in the database). SDAR also encompasses quantitative analyses helping users to quantify stratigraphic information (e.g. grain size, sorting and rounding, proportion of sand/shale). Finally, given that the SDAR analysis module, has been written in the open-source high-level computer language "R graphics/statistics language" [R Development Core Team, 2014], it is already loaded with many of the crucial features required to accomplish basic and complex tasks of statistical analysis (i.e., R language provide more than hundred spatial libraries that allow users to explore various Geostatistics and spatial analysis). Consequently, SDAR allows a deeper exploration of the stratigraphic data collected in the field, it will allow the geoscientific community in the near future to develop complex analyses related with the distribution in space and time of rock sequences, such as lithofacial correlations, by a multivariate comparison between empirical SCs with quantitative lithofacial models established from modern sedimentary environments.

Orientations for the successful categorization of facial expressions and their link with facial features.

PubMed

Duncan, Justin; Gosselin, Frédéric; Cobarro, Charlène; Dugas, Gabrielle; Blais, Caroline; Fiset, Daniel

2017-12-01

Horizontal information was recently suggested to be crucial for face identification. In the present paper, we expand on this finding and investigate the role of orientations for all the basic facial expressions and neutrality. To this end, we developed orientation bubbles to quantify utilization of the orientation spectrum by the visual system in a facial expression categorization task. We first validated the procedure in Experiment 1 with a simple plaid-detection task. In Experiment 2, we used orientation bubbles to reveal the diagnostic-i.e., task relevant-orientations for the basic facial expressions and neutrality. Overall, we found that horizontal information was highly diagnostic for expressions-surprise excepted. We also found that utilization of horizontal information strongly predicted performance level in this task. Despite the recent surge of research on horizontals, the link with local features remains unexplored. We were thus also interested in investigating this link. In Experiment 3, location bubbles were used to reveal the diagnostic features for the basic facial expressions. Crucially, Experiments 2 and 3 were run in parallel on the same participants, in an interleaved fashion. This way, we were able to correlate individual orientation and local diagnostic profiles. Our results indicate that individual differences in horizontal tuning are best predicted by utilization of the eyes.

[Contemporary criteria of the diagnosis and current recommendations for nutritional therapy in anorexia nervosa].

PubMed

Skrypnik, Damian; Bogdański, Paweł; Musialik, Katarzyna; Skrypnik, Katarzyna

2014-05-01

The basic criterion for the diagnosis of anorexia (AN - anorexia nervosa) by ICD-10 (International Classification of Diseases, version 10) is the body weight less than 15% of the expected normal body weight. According to DSM-IV (Diagnostic and Statistical Manual for Mental Disorders, version IV) the basic feature of AN is a refusal to maintain body weight equal or greater than the minimal normal weight. The prevalence of anorexia nervosa is 0.3-0.5% or even 1.3-3.7% if include pre-anorexic states (eg. the phenomenon of pro-ana). The main feature of anorexia is a reduction of caloric intake. According to the recommendations of the American Psychiatric Association (APA) for nutritional treatment of patients with AN the main goals in therapy of AN are: restoration of body weight, normalization of eating patterns, achievement a normal feeling of hunger and satiety and correction of the consequences of improper nutrition. APA suggests that achievable weight gain is about 0.9-1.4 kg per week in the case of hospitalized patients and approximately 0.23-0.45 kg per week in the case of outpatients. During the nutritional treatment of AN numerous side effects including anxiety, phobia, occurrence of obsessive thoughts and compulsive behavior, suicidal thoughts and intentions may occur. According to National Institute for Clinical Excellence (NICE) the most important goal of AN therapy is weight gain in the range of 0.5-1 kg per week in hospitalized patients and 0.5 kg per week for outpatients. A person suffering from anorexia in the initial period of nutritional treatment spends twice more energy to maintain elevated body temperature, which significantly increases during the night rest. This phenomenon is called nocturnal hyperthermia and has a negative effect on the healing process. "Refeeding syndrome" is an adverse effect of nutritional treatment in anorexia. It is caused by too rapid nutrition in a patient suffering from chronic starvation. It can endanger the patient's life.

Snow micro-structure at Kongsvegen glacier, Svalbard

NASA Astrophysics Data System (ADS)

Bilgeri, F.; Karner, F.; Steinkogler, W.; Fromm, R.; Obleitner, F.; Kohler, J.

2012-04-01

Measurements of physical snow properties have been performed at several sites at Kongsvegen glacier, which is a key Arctic glacier in western Spitzbergen (79N, 13E). The data were collected at six locations along the flow line of the glacier at different elevations (161 to 741m asl.) and describe snow that was deposited during winter 2010/11. We basically consider the vertical profiles of snow temperature, density, hardness, grain size and crystal shapes derived from standard stratigraphic methods (snow pits)and measurements using advanced instruments like Snow Micropen® and NIR imagery. Some parameters were measured repeatedly and with different instruments which proves a high quality as well as long-term and spatial representativeness of the data. The general snow conditions at the end of winter are characterized by a linear increase of snow depth and water equivalent with elevation. Snow hardness also increases with elevation while density remains remarkably constant. At most sites the snow temperature, density, hardness and grain size increase from the surface towards the snow-ice interface. The surface and the bottom layers stand out by specific changes in snow signature (crystal types) and delineate the bulk of the snow pack which itself features a rather complex layering. Comparison of the high-resolution profiles measured at different elevations at the glacier suggests some principal correlations of the signatures of hardness, grain size and crystal type. Thus, some major features (e.g. particularly hard layers) can be traced along the glacier, but the high-resolution layering can not straightforwardly be related from one site to the other. This basically reflects a locally different history of the snow pack in terms of precipitation events and post-depositional snow metamorphism. The issue is investigated more quantitatively by enhanced statistical processing of the observed signatures and simulation of the history of individual layers. These studies are supported by meteorological measurements at the snow observation sites.

Inferring epidemiological dynamics of infectious diseases using Tajima's D statistic on nucleotide sequences of pathogens.

PubMed

Kim, Kiyeon; Omori, Ryosuke; Ito, Kimihito

2017-12-01

The estimation of the basic reproduction number is essential to understand epidemic dynamics, and time series data of infected individuals are usually used for the estimation. However, such data are not always available. Methods to estimate the basic reproduction number using genealogy constructed from nucleotide sequences of pathogens have been proposed so far. Here, we propose a new method to estimate epidemiological parameters of outbreaks using the time series change of Tajima's D statistic on the nucleotide sequences of pathogens. To relate the time evolution of Tajima's D to the number of infected individuals, we constructed a parsimonious mathematical model describing both the transmission process of pathogens among hosts and the evolutionary process of the pathogens. As a case study we applied this method to the field data of nucleotide sequences of pandemic influenza A (H1N1) 2009 viruses collected in Argentina. The Tajima's D-based method estimated basic reproduction number to be 1.55 with 95% highest posterior density (HPD) between 1.31 and 2.05, and the date of epidemic peak to be 10th July with 95% HPD between 22nd June and 9th August. The estimated basic reproduction number was consistent with estimation by birth-death skyline plot and estimation using the time series of the number of infected individuals. These results suggested that Tajima's D statistic on nucleotide sequences of pathogens could be useful to estimate epidemiological parameters of outbreaks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Vortex Rossby Waves in Asymmetric Basic Flow of Typhoons

NASA Astrophysics Data System (ADS)

Wang, Tianju; Zhong, Zhong; Wang, Ju

2018-05-01

Wave ray theory is employed to study features of propagation pathways (rays) of vortex Rossby waves in typhoons with asymmetric basic flow, where the tangential asymmetric basic flow is constructed by superimposing the wavenumber-1 perturbation flow on the symmetric basic flow, and the radial basic flow is derived from the non-divergence equation. Results show that, in a certain distance, the influences of the asymmetry in the basic flow on group velocities and slopes of rays of vortex Rossby waves are mainly concentrated near the radius of maximum wind (RMW), whereas it decreases outside the RMW. The distributions of radial and tangential group velocities of the vortex Rossby waves in the asymmetric basic flow are closely related to the azimuth location of the maximum speed of the asymmetric basic flow, and the importance of radial and tangential basic flow on the group velocities would change with radius. In addition, the stronger asymmetry in the basic flow always corresponds to faster outward energy propagation of vortex Rossby waves. In short, the group velocities, and thereby the wave energy propagation and vortex Rossby wave ray slope in typhoons, would be changed by the asymmetry of the basic flow.

Randomized clinical trials in implant therapy: relationships among methodological, statistical, clinical, paratextual features and number of citations.

PubMed

Nieri, Michele; Clauser, Carlo; Franceschi, Debora; Pagliaro, Umberto; Saletta, Daniele; Pini-Prato, Giovanpaolo

2007-08-01

The aim of the present study was to investigate the relationships among reported methodological, statistical, clinical and paratextual variables of randomized clinical trials (RCTs) in implant therapy, and their influence on subsequent research. The material consisted of the RCTs in implant therapy published through the end of the year 2000. Methodological, statistical, clinical and paratextual features of the articles were assessed and recorded. The perceived clinical relevance was subjectively evaluated by an experienced clinician on anonymous abstracts. The impact on research was measured by the number of citations found in the Science Citation Index. A new statistical technique (Structural learning of Bayesian Networks) was used to assess the relationships among the considered variables. Descriptive statistics revealed that the reported methodology and statistics of RCTs in implant therapy were defective. Follow-up of the studies was generally short. The perceived clinical relevance appeared to be associated with the objectives of the studies and with the number of published images in the original articles. The impact on research was related to the nationality of the involved institutions and to the number of published images. RCTs in implant therapy (until 2000) show important methodological and statistical flaws and may not be appropriate for guiding clinicians in their practice. The methodological and statistical quality of the studies did not appear to affect their impact on practice and research. Bayesian Networks suggest new and unexpected relationships among the methodological, statistical, clinical and paratextual features of RCTs.

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

Global map of eolian features on Mars.

USGS Publications Warehouse

Ward, A.W.; Doyle, K.B.; Helm, P.J.; Weisman, M.K.; Witbeck, N.E.

1985-01-01

Ten basic categories of eolian features on Mars were identified from a survey of Mariner 9 and Viking orbiter images. The ten features mapped are 1) light streaks (including frost streaks), 2) dark streaks, 3) sand sheets or splotches, 4) barchan dunes, 5) transverse dunes, 6) crescentic dunes, 7) anomalous dunes, 8) yardangs, 9) wind grooves, and 10) deflation pits. The features were mapped in groups, not as individual landforms, and recorded according to their geographic positions and orientations on maps of 1:12.5 million or 1:25 million scale. -from Authors

Combining Statistical and Geometric Features for Colonic Polyp Detection in CTC Based on Multiple Kernel Learning

PubMed Central

Wang, Shijun; Yao, Jianhua; Petrick, Nicholas; Summers, Ronald M.

2010-01-01

Colon cancer is the second leading cause of cancer-related deaths in the United States. Computed tomographic colonography (CTC) combined with a computer aided detection system provides a feasible approach for improving colonic polyps detection and increasing the use of CTC for colon cancer screening. To distinguish true polyps from false positives, various features extracted from polyp candidates have been proposed. Most of these traditional features try to capture the shape information of polyp candidates or neighborhood knowledge about the surrounding structures (fold, colon wall, etc.). In this paper, we propose a new set of shape descriptors for polyp candidates based on statistical curvature information. These features called histograms of curvature features are rotation, translation and scale invariant and can be treated as complementing existing feature set. Then in order to make full use of the traditional geometric features (defined as group A) and the new statistical features (group B) which are highly heterogeneous, we employed a multiple kernel learning method based on semi-definite programming to learn an optimized classification kernel from the two groups of features. We conducted leave-one-patient-out test on a CTC dataset which contained scans from 66 patients. Experimental results show that a support vector machine (SVM) based on the combined feature set and the semi-definite optimization kernel achieved higher FROC performance compared to SVMs using the two groups of features separately. At a false positive per scan rate of 5, the sensitivity of the SVM using the combined features improved from 0.77 (Group A) and 0.73 (Group B) to 0.83 (p ≤ 0.01). PMID:20953299

Association between MRI structural features and cognitive measures in pediatric multiple sclerosis

NASA Astrophysics Data System (ADS)

Amoroso, N.; Bellotti, R.; Fanizzi, A.; Lombardi, A.; Monaco, A.; Liguori, M.; Margari, L.; Simone, M.; Viterbo, R. G.; Tangaro, S.

2017-09-01

Multiple sclerosis (MS) is an inflammatory and demyelinating disease associated with neurodegenerative processes that lead to brain structural changes. The disease affects mostly young adults, but 3-5% of cases has a pediatric onset (POMS). Magnetic Resonance Imaging (MRI) is generally used for diagnosis and follow-up in MS patients, however the most common MRI measures (e.g. new or enlarging T2-weighted lesions, T1-weighted gadolinium- enhancing lesions) have often failed as surrogate markers of MS disability and progression. MS is clinically heterogenous with symptoms that can include both physical changes (such as visual loss or walking difficulties) and cognitive impairment. 30-50% of POMS experience prominent cognitive dysfunction. In order to investigate the association between cognitive measures and brain morphometry, in this work we present a fully automated pipeline for processing and analyzing MRI brain scans. Relevant anatomical structures are segmented with FreeSurfer; besides, statistical features are computed. Thus, we describe the data referred to 12 patients with early POMS (mean age at MRI: 15.5 +/- 2.7 years) with a set of 181 structural features. The major cognitive abilities measured are verbal and visuo-spatial learning, expressive language and complex attention. Data was collected at the Department of Basic Sciences, Neurosciences and Sense Organs, University of Bari, and exploring different abilities like the verbal and visuo-spatial learning, expressive language and complex attention. Different regression models and parameter configurations are explored to assess the robustness of the results, in particular Generalized Linear Models, Bayes Regression, Random Forests, Support Vector Regression and Artificial Neural Networks are discussed.

Active contours on statistical manifolds and texture segmentation

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Neil A. Clark; Philip A. Araman

2005-01-01

A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2- dimensional Riemannian manifolds that are statistically defined by maps that transform a parameter domain onto a set of probability density functions. In this novel framework, color or texture features are measured at each image point and their statistical...

Active contours on statistical manifolds and texture segmentaiton

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Neil A. Clark; Philip A. Araman

2005-01-01

A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2- dimensional Riemannian manifolds that are statistically defined by maps that transform a parameter domain onto-a set of probability density functions. In this novel framework, color or texture features are measured at each Image point and their statistical...

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

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

Oliver, J; Budzevich, M; Moros, E

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images),more » image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.« less

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

A Correlational Study of the Relationships between Music Aptitude and Phonemic Awareness of Kindergarten Children

ERIC Educational Resources Information Center

Rubinson, Laura E.

2010-01-01

More than one third of American children cannot read at a basic level by fourth grade (Lee, Grigg, & Donahue, 2007) and those numbers are even higher for African American, Hispanic and poor White students (Boorman et al., 2007). These are alarming statistics given that the ability to read is the most basic and fundamental skill for academic…

Availability of Instructional Materials at the Basic Education Level in Enugu Educational Zone of Enugu State, Nigeria

ERIC Educational Resources Information Center

Chukwu, Leo C.; Eze, Thecla A. Y.; Agada, Fidelia Chinyelugo

2016-01-01

The study examined the availability of instructional materials at the basic education level in Enugu Education Zone of Enugu State, Nigeria. One research question and one hypothesis guided the study. The research question was answered using mean and grand mean ratings, while the hypothesis was tested using t-test statistics at 0.05 level of…

Characterizing microstructural features of biomedical samples by statistical analysis of Mueller matrix images

NASA Astrophysics Data System (ADS)

He, Honghui; Dong, Yang; Zhou, Jialing; Ma, Hui

2017-03-01

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

Prevalence of herpes simplex, Epstein Barr and human papilloma viruses in oral lichen planus.

PubMed

Yildirim, Benay; Sengüven, Burcu; Demir, Cem

2011-03-01

The aim of the present study was to assess the prevalence of Herpes Simplex virus, Epstein Barr virus and Human Papilloma virus -16 in oral lichen planus cases and to evaluate whether any clinical variant, histopathological or demographic feature correlates with these viruses. The study was conducted on 65 cases. Viruses were detected immunohistochemically. We evaluated the histopathological and demographic features and statistically analysed correlation of these features with Herpes Simplex virus, Epstein Barr virus and Human Papilloma virus-16 positivity. Herpes Simplex virus was positive in six (9%) cases and this was not statistically significant. The number of Epstein Barr virus positive cases was 23 (35%) and it was statistically significant. Human Papilloma virus positivity in 14 cases (21%) was statistically significant. Except basal cell degeneration in Herpes Simplex virus positive cases, we did not observe any significant correlation between virus positivity and demographic or histopathological features. However an increased risk of Epstein Barr virus and Human Papilloma virus infection was noted in oral lichen planus cases. Taking into account the oncogenic potential of both viruses, oral lichen planus cases should be detected for the presence of these viruses.

Defense Language Institute Russian Basic Course. Volumes XXVIII, Lessons 131-140. Volume XXX, Lessons 151-159.

ERIC Educational Resources Information Center

Defense Language Inst., Washington, DC.

The 19 lessons in these two volumes are intended for the advanced phase of a 159-lesson intensive audiolingual basic Russian course developed recently by the Defense Language Institute to train native speakers of English to a Level 3 second language proficiency. These third and fifth volumes contain such features as (1) texts on the Russian Civil…

On the Language Specificity of Basic Number Processing: Transcoding in a Language with Inversion and Its Relation to Working Memory Capacity

ERIC Educational Resources Information Center

Zuber, Julia; Pixner, Silvia; Moeller, Korbinian; Nuerk, Hans-Christoph

2009-01-01

Transcoding Arabic numbers from and into verbal number words is one of the most basic number processing tasks commonly used to index the verbal representation of numbers. The inversion property, which is an important feature of some number word systems (e.g., German "einundzwanzig" [one and twenty]), might represent a major difficulty in…

Variations in leopard cat (Prionailurus bengalensis) skull morphology and body size: sexual and geographic influences

PubMed Central

Oliveira, Luiz Flamarion B.

2015-01-01

The leopard cat, Prionailurus bengalensis (Kerr, 1792), is one of the most widespread Asian cats, occurring in continental eastern and southeastern Asia. Since 1929, several studies have focused on the morphology, ecology, and taxonomy of leopard cats. Nevertheless, hitherto there has been no agreement on basic aspects of leopard cat biology, such as the presence or absence of sexual dimorphism, morphological skull and body differences between the eleven recognized subspecies, and the biogeography of the different morphotypes. Twenty measurements on 25 adult leopard cat skulls from different Asian localities were analyzed through univariate and multivariate statistical approaches. Skull and external body measurements from studies over the last 77 years were assembled and organized in two categories: full data and summary data. Most of this database comprises small samples, which have never been statistically tested and compared with each other. Full data sets were tested with univariate and multivariate statistical analyses; summary data sets (i.e., means, SDs, and ranges) were analyzed through suitable univariate approaches. The independent analyses of the data from these works confirmed our original results and improved the overview of sexual dimorphism and geographical morphological variation among subspecies. Continental leopard cats have larger skulls and body dimensions. Skulls of Indochinese morphotypes have broader and higher features than those of continental morphotypes, while individuals from the Sunda Islands have skulls with comparatively narrow and low profiles. Cranial sexual dimorphism is present in different degrees among subspecies. Most display subtle sex-related variations in a few skull features. However, in some cases, sexual dimorphism in skull morphology is absent, such as in P. b. sumatranus and P. b. borneoensis. External body measurement comparisons also indicate the low degree of sexual dimorphism. Apart from the gonads, the longer hind foot of male leopard cats is the main feature of sexual dimorphism among P. b. bengalensis (and probably among P. b. horsfieldii too). External body measurements also indicated the absence of sexual dimorphism among individuals of P. b. borneoensis. Inter-subspecific skull comparisons provided a morphometric basis for differentiating some subspecies. Prionailurus b. horsfieldii and P. b. bengalensis were distinguished only by a subtle difference in PM4 size, indicating that overall skull morphology does not appear to support their separate taxonomical status, in spite of the marked differences reported in their coat patterns. Geological events affecting the Sunda Shelf connection between the Sunda Islands and the mainland during the Last Glacial Maximum seem to have influenced directly the morphological pattern shown by leopard cat subspecies nowadays. PMID:26500818

Basic statistics with Microsoft Excel: a review.

PubMed

Divisi, Duilio; Di Leonardo, Gabriella; Zaccagna, Gino; Crisci, Roberto

2017-06-01

The scientific world is enriched daily with new knowledge, due to new technologies and continuous discoveries. The mathematical functions explain the statistical concepts particularly those of mean, median and mode along with those of frequency and frequency distribution associated to histograms and graphical representations, determining elaborative processes on the basis of the spreadsheet operations. The aim of the study is to highlight the mathematical basis of statistical models that regulate the operation of spreadsheets in Microsoft Excel.

Basic statistics with Microsoft Excel: a review

PubMed Central

Di Leonardo, Gabriella; Zaccagna, Gino; Crisci, Roberto

2017-01-01

The scientific world is enriched daily with new knowledge, due to new technologies and continuous discoveries. The mathematical functions explain the statistical concepts particularly those of mean, median and mode along with those of frequency and frequency distribution associated to histograms and graphical representations, determining elaborative processes on the basis of the spreadsheet operations. The aim of the study is to highlight the mathematical basis of statistical models that regulate the operation of spreadsheets in Microsoft Excel. PMID:28740690

A. C. C. Fact Book: A Statistical Profile of Allegany Community College and the Community It Serves.

ERIC Educational Resources Information Center

Andersen, Roger C.

This document is intended to be an authoritative compilation of frequently referenced basic facts concerning Allegany Community College (ACC) in Maryland. It is a statistical profile of ACC and the community it serves, divided into six sections: enrollment, students, faculty, community, support services, and general college related information.…

Basic Mathematics Test Predicts Statistics Achievement and Overall First Year Academic Success

ERIC Educational Resources Information Center

Fonteyne, Lot; De Fruyt, Filip; Dewulf, Nele; Duyck, Wouter; Erauw, Kris; Goeminne, Katy; Lammertyn, Jan; Marchant, Thierry; Moerkerke, Beatrijs; Oosterlinck, Tom; Rosseel, Yves

2015-01-01

In the psychology and educational science programs at Ghent University, only 36.1% of the new incoming students in 2011 and 2012 passed all exams. Despite availability of information, many students underestimate the scientific character of social science programs. Statistics courses are a major obstacle in this matter. Not all enrolling students…

The Structure of Research Methodology Competency in Higher Education and the Role of Teaching Teams and Course Temporal Distance

ERIC Educational Resources Information Center

Schweizer, Karl; Steinwascher, Merle; Moosbrugger, Helfried; Reiss, Siegbert

2011-01-01

The development of research methodology competency is a major aim of the psychology curriculum at universities. Usually, three courses concentrating on basic statistics, advanced statistics and experimental methods, respectively, serve the achievement of this aim. However, this traditional curriculum-based course structure gives rise to 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…

Statistical estimators for monitoring spotted owls in Oregon and Washington in 1987.

Treesearch

Tlmothy A. Max; Ray A. Souter; Kathleen A. O' Halloran

1990-01-01

Spotted owls (Strix occidentalis) were monitored on 11 National Forests in the Pacific Northwest Region of the USDA Forest Service between March and August of 1987. The basic intent of monitoring was to provide estimates of occupancy and reproduction rates for pairs of spotted owls. This paper documents the technical details of the statistical...

Statistical techniques for sampling and monitoring natural resources

Treesearch

Hans T. Schreuder; Richard Ernst; Hugo Ramirez-Maldonado

2004-01-01

We present the statistical theory of inventory and monitoring from a probabilistic point of view. We start with the basics and show the interrelationships between designs and estimators illustrating the methods with a small artificial population as well as with a mapped realistic population. For such applications, useful open source software is given in Appendix 4....

Peer-Assisted Learning in Research Methods and Statistics

ERIC Educational Resources Information Center

Stone, Anna; Meade, Claire; Watling, Rosamond

2012-01-01

Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…

Adult Basic and Secondary Education Program Statistics. Fiscal Year 1976.

ERIC Educational Resources Information Center

Cain, Sylvester H.; Whalen, Barbara A.

Reports submitted to the National Center for Education Statistics provided data for this compilation and tabulation of data on adult participants in U.S. educational programs in fiscal year 1976. In the summary section introducing the charts, it is noted that adult education programs funded under P.L. 91-230 served over 1.6 million persons--an…

Deformable image registration as a tool to improve survival prediction after neoadjuvant chemotherapy for breast cancer: results from the ACRIN 6657/I-SPY-1 trial

NASA Astrophysics Data System (ADS)

Jahani, Nariman; Cohen, Eric; Hsieh, Meng-Kang; Weinstein, Susan P.; Pantalone, Lauren; Davatzikos, Christos; Kontos, Despina

2018-02-01

We examined the ability of DCE-MRI longitudinal features to give early prediction of recurrence-free survival (RFS) in women undergoing neoadjuvant chemotherapy for breast cancer, in a retrospective analysis of 106 women from the ISPY 1 cohort. These features were based on the voxel-wise changes seen in registered images taken before treatment and after the first round of chemotherapy. We computed the transformation field using a robust deformable image registration technique to match breast images from these two visits. Using the deformation field, parametric response maps (PRM) — a voxel-based feature analysis of longitudinal changes in images between visits — was computed for maps of four kinetic features (signal enhancement ratio, peak enhancement, and wash-in/wash-out slopes). A two-level discrete wavelet transform was applied to these PRMs to extract heterogeneity information about tumor change between visits. To estimate survival, a Cox proportional hazard model was applied with the C statistic as the measure of success in predicting RFS. The best PRM feature (as determined by C statistic in univariable analysis) was determined for each of the four kinetic features. The baseline model, incorporating functional tumor volume, age, race, and hormone response status, had a C statistic of 0.70 in predicting RFS. The model augmented with the four PRM features had a C statistic of 0.76. Thus, our results suggest that adding information on the texture of voxel-level changes in tumor kinetic response between registered images of first and second visits could improve early RFS prediction in breast cancer after neoadjuvant chemotherapy.

Image feature detection and extraction techniques performance evaluation for development of panorama under different light conditions

NASA Astrophysics Data System (ADS)

Patil, Venkat P.; Gohatre, Umakant B.

2018-04-01

The technique of obtaining a wider field-of-view of an image to get high resolution integrated image is normally required for development of panorama of a photographic images or scene from a sequence of part of multiple views. There are various image stitching methods developed recently. For image stitching five basic steps are adopted stitching which are Feature detection and extraction, Image registration, computing homography, image warping and Blending. This paper provides review of some of the existing available image feature detection and extraction techniques and image stitching algorithms by categorizing them into several methods. For each category, the basic concepts are first described and later on the necessary modifications made to the fundamental concepts by different researchers are elaborated. This paper also highlights about the some of the fundamental techniques for the process of photographic image feature detection and extraction methods under various illumination conditions. The Importance of Image stitching is applicable in the various fields such as medical imaging, astrophotography and computer vision. For comparing performance evaluation of the techniques used for image features detection three methods are considered i.e. ORB, SURF, HESSIAN and time required for input images feature detection is measured. Results obtained finally concludes that for daylight condition, ORB algorithm found better due to the fact that less tome is required for more features extracted where as for images under night light condition it shows that SURF detector performs better than ORB/HESSIAN detectors.

Handwriting in Children and Adults with Down Syndrome: Developmental Delay or Specific Features?

ERIC Educational Resources Information Center

Tsao, Raphaele

2017-01-01

While there is a long history and tradition of behavioral research on basic motor skills in Down syndrome (DS), there has been only limited research on handwriting ability. We analyzed the spatiotemporal features of handwriting produced by children and adults with DS (n = 24), and compared their productions with those of comparison groups matched…

Semantically Induced Distortions of Visual Awareness in a Patient with Balint's Syndrome

ERIC Educational Resources Information Center

Soto, David; Humphreys, Glyn W.

2009-01-01

We present data indicating that visual awareness for a basic perceptual feature (colour) can be influenced by the relation between the feature and the semantic properties of the stimulus. We examined semantic interference from the meaning of a colour word ("RED") on simple colour (ink related) detection responses in a patient with simultagnosia…

Cerebro-costo-mandibular syndrome: Report of two cases.

PubMed

Abdalla, Wael; Panigrahy, Ashok; Bartoletti, Stefano C

2011-01-01

Cerebro-costo-mandibular syndrome (CCMS) is a rare syndrome that includes a constellation of mandibular hypoplasia and posterior rib defects as its basic features. Additional features can include hearing loss, tracheal cartilage abnormalities, scoliosis, elbow hypoplasia, and spina bifida. Here we report two cases of CCMS and discuss the reported long-term outcome of the disease.

Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients.

PubMed

Tunali, Ilke; Stringfield, Olya; Guvenis, Albert; Wang, Hua; Liu, Ying; Balagurunathan, Yoganand; Lambin, Philippe; Gillies, Robert J; Schabath, Matthew B

2017-11-10

The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features.

Theory of Financial Risk and Derivative Pricing

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2009-01-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Theory of Financial Risk and Derivative Pricing - 2nd Edition

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2003-12-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Study on Hybrid Image Search Technology Based on Texts and Contents

NASA Astrophysics Data System (ADS)

Wang, H. T.; Ma, F. L.; Yan, C.; Pan, H.

2018-05-01

Image search was studied first here based on texts and contents, respectively. The text-based image feature extraction was put forward by integrating the statistical and topic features in view of the limitation of extraction of keywords only by means of statistical features of words. On the other hand, a search-by-image method was put forward based on multi-feature fusion in view of the imprecision of the content-based image search by means of a single feature. The layered-searching method depended on primarily the text-based image search method and additionally the content-based image search was then put forward in view of differences between the text-based and content-based methods and their difficult direct fusion. The feasibility and effectiveness of the hybrid search algorithm were experimentally verified.

Electro optical system to measure strains

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.; Bhat, G.

With the advent of the so called speckle interferometry, interferograms of objects can be obtained in real time by using a TV camera as the recording medium. The basic idea of this instrument is to couple the photoelectric registration by a TV camera with the subsequent electronic processing, to develop an efficient device for the measurement of deformations. This paper presents a new and improved instrument, which has a very important feature, portability, that can be operated in different modes and is capable of producing interferograms using holography, speckle, and moire methods. The basic features of the instrument are presented and some of the theoretical points at the foundation of operation of the instrument are analyzed. Examples are given of the application to moire, speckle, and holographic interferometry.

CORSSA: Community Online Resource for Statistical Seismicity Analysis

NASA Astrophysics Data System (ADS)

Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.

2011-12-01

Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.

GAISE 2016 Promotes Statistical Literacy

ERIC Educational Resources Information Center

Schield, Milo

2017-01-01

In the 2005 Guidelines for Assessment and Instruction in Statistics Education (GAISE), statistical literacy featured as a primary goal. The 2016 revision eliminated statistical literacy as a stated goal. Although this looks like a rejection, this paper argues that by including multivariate thinking and--more importantly--confounding as recommended…

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer.

PubMed

Neofytou, Marios S; Tanos, Vasilis; Pattichis, Marios S; Pattichis, Constantinos S; Kyriacou, Efthyvoulos C; Koutsouris, Dimitris D

2007-11-29

In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 x 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations to the original images. Within the proposed protocol, for human ROIs, we have found that there is a large number of texture features that showed significant differences between normal and abnormal endometrium. This study provides a standardized protocol for avoiding any significant texture feature differences that may arise due to variability in the acquisition procedure or the lack of color correction. After applying the protocol, we have found that significant differences in texture features will only be due to the fact that the features were extracted from different types of tissue (normal vs abnormal).

Uncoupling of Secretion From Growth in Some Hormone Secretory Tissues

PubMed Central

2014-01-01

Context: Most syndromes with benign primary excess of a hormone show positive coupling of hormone secretion to size or proliferation in the affected hormone secretory tissue. Syndromes that lack this coupling seem rare and have not been examined for unifying features among each other. Evidence Acquisition: Selected clinical and basic features were analyzed from original reports and reviews. We examined indices of excess secretion of a hormone and indices of size of secretory tissue within the following three syndromes, each suggestive of uncoupling between these two indices: familial hypocalciuric hypercalcemia, congenital diazoxide-resistant hyperinsulinism, and congenital primary hyperaldosteronism type III (with G151E mutation of the KCNJ5 gene). Evidence Synthesis: Some unifying features among the three syndromes were different from features present among common tumors secreting the same hormone. The unifying and distinguishing features included: 1) expression of hormone excess as early as the first days of life; 2) normal size of tissue that oversecretes a hormone; 3) diffuse histologic expression in the hormonal tissue; 4) resistance to treatment by subtotal ablation of the hormone-secreting tissue; 5) causation by a germline mutation; 6) low potential of the same mutation to cause a tumor by somatic mutation; and 7) expression of the mutated molecule in a pathway between sensing of a serum metabolite and secretion of hormone regulating that metabolite. Conclusion: Some shared clinical and basic features of uncoupling of secretion from size in a hormonal tissue characterize three uncommon states of hormone excess. These features differ importantly from features of common hormonal neoplasm of that tissue. PMID:25004249

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

Segmentation of prostate boundaries from ultrasound images using statistical shape model.

PubMed

Shen, Dinggang; Zhan, Yiqiang; Davatzikos, Christos

2003-04-01

This paper presents a statistical shape model for the automatic prostate segmentation in transrectal ultrasound images. A Gabor filter bank is first used to characterize the prostate boundaries in ultrasound images in both multiple scales and multiple orientations. The Gabor features are further reconstructed to be invariant to the rotation of the ultrasound probe and incorporated in the prostate model as image attributes for guiding the deformable segmentation. A hierarchical deformation strategy is then employed, in which the model adaptively focuses on the similarity of different Gabor features at different deformation stages using a multiresolution technique, i.e., coarse features first and fine features later. A number of successful experiments validate the algorithm.

On the deep structure of social affect: Attitudes, emotions, sentiments, and the case of "contempt".

PubMed

Gervais, Matthew M; Fessler, Daniel M T

2017-01-01

Contempt is typically studied as a uniquely human moral emotion. However, this approach has yielded inconclusive results. We argue this is because the folk affect concept "contempt" has been inaccurately mapped onto basic affect systems. "Contempt" has features that are inconsistent with a basic emotion, especially its protracted duration and frequently cold phenomenology. Yet other features are inconsistent with a basic attitude. Nonetheless, the features of "contempt" functionally cohere. To account for this, we revive and reconfigure the sentiment construct using the notion of evolved functional specialization. We develop the Attitude-Scenario-Emotion (ASE) model of sentiments, in which enduring attitudes represent others' social-relational value and moderate discrete emotions across scenarios. Sentiments are functional networks of attitudes and emotions. Distinct sentiments, including love, respect, like, hate, and fear, track distinct relational affordances, and each is emotionally pluripotent, thereby serving both bookkeeping and commitment functions within relationships. The sentiment contempt is an absence of respect; from cues to others' low efficacy, it represents them as worthless and small, muting compassion, guilt, and shame and potentiating anger, disgust, and mirth. This sentiment is ancient yet implicated in the ratcheting evolution of human ultrasocialty. The manifolds of the contempt network, differentially engaged across individuals and populations, explain the features of "contempt," its translatability, and its variable experience as "hot" or "cold," occurrent or enduring, and anger-like or disgust-like. This rapprochement between psychological anthropology and evolutionary psychology contributes both methodological and empirical insights, with broad implications for understanding the functional and cultural organization of social affect.

Statistical process control using optimized neural networks: a case study.

PubMed

Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

2014-09-01

The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

MedlinePlus FAQ: Statistics about MedlinePlus

MedlinePlus

... faq/stats.html Can you give me some statistics about MedlinePlus? To use the sharing features on ... For page requests and unique visitors, see MedlinePlus statistics . Return to the list of MedlinePlus FAQs About ...

Features of statistical dynamics in a finite system

NASA Astrophysics Data System (ADS)

Yan, Shiwei; Sakata, Fumihiko; Zhuo, Yizhong

2002-03-01

We study features of statistical dynamics in a finite Hamilton system composed of a relevant one degree of freedom coupled to an irrelevant multidegree of freedom system through a weak interaction. Special attention is paid on how the statistical dynamics changes depending on the number of degrees of freedom in the irrelevant system. It is found that the macrolevel statistical aspects are strongly related to an appearance of the microlevel chaotic motion, and a dissipation of the relevant motion is realized passing through three distinct stages: dephasing, statistical relaxation, and equilibrium regimes. It is clarified that the dynamical description and the conventional transport approach provide us with almost the same macrolevel and microlevel mechanisms only for the system with a very large number of irrelevant degrees of freedom. It is also shown that the statistical relaxation in the finite system is an anomalous diffusion and the fluctuation effects have a finite correlation time.

Features of statistical dynamics in a finite system.

PubMed

Yan, Shiwei; Sakata, Fumihiko; Zhuo, Yizhong

2002-03-01

We study features of statistical dynamics in a finite Hamilton system composed of a relevant one degree of freedom coupled to an irrelevant multidegree of freedom system through a weak interaction. Special attention is paid on how the statistical dynamics changes depending on the number of degrees of freedom in the irrelevant system. It is found that the macrolevel statistical aspects are strongly related to an appearance of the microlevel chaotic motion, and a dissipation of the relevant motion is realized passing through three distinct stages: dephasing, statistical relaxation, and equilibrium regimes. It is clarified that the dynamical description and the conventional transport approach provide us with almost the same macrolevel and microlevel mechanisms only for the system with a very large number of irrelevant degrees of freedom. It is also shown that the statistical relaxation in the finite system is an anomalous diffusion and the fluctuation effects have a finite correlation time.

No-reference image quality assessment based on statistics of convolution feature maps

NASA Astrophysics Data System (ADS)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

Facts about Folic Acid

MedlinePlus

... Surveillance References Birth Defects COUNT Data & Statistics Research Articles & Key Findings About Us Partners Links to Other Websites Information For… Media Policy Makers Folic Acid Basics Language: English (US) ...

Neural Systems with Numerically Matched Input-Output Statistic: Isotonic Bivariate Statistical Modeling

PubMed Central

Fiori, Simone

2007-01-01

Bivariate statistical modeling from incomplete data is a useful statistical tool that allows to discover the model underlying two data sets when the data in the two sets do not correspond in size nor in ordering. Such situation may occur when the sizes of the two data sets do not match (i.e., there are “holes” in the data) or when the data sets have been acquired independently. Also, statistical modeling is useful when the amount of available data is enough to show relevant statistical features of the phenomenon underlying the data. We propose to tackle the problem of statistical modeling via a neural (nonlinear) system that is able to match its input-output statistic to the statistic of the available data sets. A key point of the new implementation proposed here is that it is based on look-up-table (LUT) neural systems, which guarantee a computationally advantageous way of implementing neural systems. A number of numerical experiments, performed on both synthetic and real-world data sets, illustrate the features of the proposed modeling procedure. PMID:18566641

SEDIDAT: A BASIC program for the collection and statistical analysis of particle settling velocity data

NASA Astrophysics Data System (ADS)

Wright, Robyn; Thornberg, Steven M.

SEDIDAT is a series of compiled IBM-BASIC (version 2.0) programs that direct the collection, statistical calculation, and graphic presentation of particle settling velocity and equivalent spherical diameter for samples analyzed using the settling tube technique. The programs follow a menu-driven format that is understood easily by students and scientists with little previous computer experience. Settling velocity is measured directly (cm,sec) and also converted into Chi units. Equivalent spherical diameter (reported in Phi units) is calculated using a modified Gibbs equation for different particle densities. Input parameters, such as water temperature, settling distance, particle density, run time, and Phi;Chi interval are changed easily at operator discretion. Optional output to a dot-matrix printer includes a summary of moment and graphic statistical parameters, a tabulation of individual and cumulative weight percents, a listing of major distribution modes, and cumulative and histogram plots of a raw time, settling velocity. Chi and Phi data.

[Comment on] Statistical discrimination

NASA Astrophysics Data System (ADS)

Chinn, Douglas

In the December 8, 1981, issue of Eos, a news item reported the conclusion of a National Research Council study that sexual discrimination against women with Ph.D.'s exists in the field of geophysics. Basically, the item reported that even when allowances are made for motherhood the percentage of female Ph.D.'s holding high university and corporate positions is significantly lower than the percentage of male Ph.D.'s holding the same types of positions. The sexual discrimination conclusion, based only on these statistics, assumes that there are no basic psychological differences between men and women that might cause different populations in the employment group studied. Therefore, the reasoning goes, after taking into account possible effects from differences related to anatomy, such as women stopping their careers in order to bear and raise children, the statistical distributions of positions held by male and female Ph.D.'s ought to be very similar to one another. Any significant differences between the distributions must be caused primarily by sexual discrimination.

Automated surgical skill assessment in RMIS training.

PubMed

Zia, Aneeq; Essa, Irfan

2018-05-01

Manual feedback in basic robot-assisted minimally invasive surgery (RMIS) training can consume a significant amount of time from expert surgeons' schedule and is prone to subjectivity. In this paper, we explore the usage of different holistic features for automated skill assessment using only robot kinematic data and propose a weighted feature fusion technique for improving score prediction performance. Moreover, we also propose a method for generating 'task highlights' which can give surgeons a more directed feedback regarding which segments had the most effect on the final skill score. We perform our experiments on the publicly available JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS) and evaluate four different types of holistic features from robot kinematic data-sequential motion texture (SMT), discrete Fourier transform (DFT), discrete cosine transform (DCT) and approximate entropy (ApEn). The features are then used for skill classification and exact skill score prediction. Along with using these features individually, we also evaluate the performance using our proposed weighted combination technique. The task highlights are produced using DCT features. Our results demonstrate that these holistic features outperform all previous Hidden Markov Model (HMM)-based state-of-the-art methods for skill classification on the JIGSAWS dataset. Also, our proposed feature fusion strategy significantly improves performance for skill score predictions achieving up to 0.61 average spearman correlation coefficient. Moreover, we provide an analysis on how the proposed task highlights can relate to different surgical gestures within a task. Holistic features capturing global information from robot kinematic data can successfully be used for evaluating surgeon skill in basic surgical tasks on the da Vinci robot. Using the framework presented can potentially allow for real-time score feedback in RMIS training and help surgical trainees have more focused training.

Can responses to basic non-numerical visual features explain neural numerosity responses?

PubMed

Harvey, Ben M; Dumoulin, Serge O

2017-04-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs. Copyright © 2017 Elsevier Inc. All rights reserved.

FY16 ASME High Temperature Code Activities

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

Swindeman, M. J.; Jetter, R. I.; Sham, T. -L.

2016-09-01

One of the objectives of the ASME high temperature Code activities is to develop and validate both improvements and the basic features of Section III, Division 5, Subsection HB, Subpart B (HBB). The overall scope of this task is to develop a computer program to be used to assess whether or not a specific component under specified loading conditions will satisfy the elevated temperature design requirements for Class A components in Section III, Division 5, Subsection HB, Subpart B (HBB). There are many features and alternative paths of varying complexity in HBB. The initial focus of this task is amore » basic path through the various options for a single reference material, 316H stainless steel. However, the program will be structured for eventual incorporation all the features and permitted materials of HBB. Since this task has recently been initiated, this report focuses on the description of the initial path forward and an overall description of the approach to computer program development.« less

Segmenting lung fields in serial chest radiographs using both population-based and patient-specific shape statistics.

PubMed

Shi, Y; Qi, F; Xue, Z; Chen, L; Ito, K; Matsuo, H; Shen, D

2008-04-01

This paper presents a new deformable model using both population-based and patient-specific shape statistics to segment lung fields from serial chest radiographs. There are two novelties in the proposed deformable model. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel. Second, the deformable contour is constrained by both population-based and patient-specific shape statistics, and it yields more robust and accurate segmentation of lung fields for serial chest radiographs. In particular, for segmenting the initial time-point images, the population-based shape statistics is used to constrain the deformable contour; as more subsequent images of the same patient are acquired, the patient-specific shape statistics online collected from the previous segmentation results gradually takes more roles. Thus, this patient-specific shape statistics is updated each time when a new segmentation result is obtained, and it is further used to refine the segmentation results of all the available time-point images. Experimental results show that the proposed method is more robust and accurate than other active shape models in segmenting the lung fields from serial chest radiographs.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

PubMed

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

Unconscious analyses of visual scenes based on feature conjunctions.

PubMed

Tachibana, Ryosuke; Noguchi, Yasuki

2015-06-01

To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

Statistical evolution of quiet-Sun small-scale magnetic features using Sunrise observations

NASA Astrophysics Data System (ADS)

Anusha, L. S.; Solanki, S. K.; Hirzberger, J.; Feller, A.

2017-02-01

The evolution of small magnetic features in quiet regions of the Sun provides a unique window for probing solar magneto-convection. Here we analyze small-scale magnetic features in the quiet Sun, using the high resolution, seeing-free observations from the Sunrise balloon borne solar observatory. Our aim is to understand the contribution of different physical processes, such as splitting, merging, emergence and cancellation of magnetic fields to the rearrangement, addition and removal of magnetic flux in the photosphere. We have employed a statistical approach for the analysis and the evolution studies are carried out using a feature-tracking technique. In this paper we provide a detailed description of the feature-tracking algorithm that we have newly developed and we present the results of a statistical study of several physical quantities. The results on the fractions of the flux in the emergence, appearance, splitting, merging, disappearance and cancellation qualitatively agrees with other recent studies. To summarize, the total flux gained in unipolar appearance is an order of magnitude larger than the total flux gained in emergence. On the other hand, the bipolar cancellation contributes nearly an equal amount to the loss of magnetic flux as unipolar disappearance. The total flux lost in cancellation is nearly six to eight times larger than the total flux gained in emergence. One big difference between our study and previous similar studies is that, thanks to the higher spatial resolution of Sunrise, we can track features with fluxes as low as 9 × 1014 Mx. This flux is nearly an order of magnitude lower than the smallest fluxes of the features tracked in the highest resolution previous studies based on Hinode data. The area and flux of the magnetic features follow power-law type distribution, while the lifetimes show either power-law or exponential type distribution depending on the exact definitions used to define various birth and death events. We have also statistically determined the evolution of the flux within the features in the course of their lifetime, finding that this evolution depends very strongly on the birth and death process that the features undergo.

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan

PubMed Central

Ng, Ka-Chon; Nguyen, Thi Luong

2018-01-01

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover. PMID:29495351

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan.

PubMed

Chuang, Ting-Wu; Ng, Ka-Chon; Nguyen, Thi Luong; Chaves, Luis Fernando

2018-02-26

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover.

A lidar, GIS and basic spatial statistic application for the study of ravine and palaeo-ravine evolution in the upper Vipava valley, SW Slovenia

NASA Astrophysics Data System (ADS)

Popit, Tomislav; Rožič, Boštjan; Šmuc, Andrej; Kokalj, Žiga; Verbovšek, Timotej; Košir, Adrijan

2014-01-01

The analysis of high resolution airborne lidar topography represents an essential tool for the geomorphological investigation of surface features. Here we present a detailed lidar-based geomorphological analysis of the ravines cut into the slopes of the upper Vipava valley, NW Slovenia. The NE slopes are defined by an Oligocene thrust-front of Mesozoic carbonates overthrusted on Tertiary flysch and covered by numerous fan-shaped Quaternary gravity flows, deposited in palaeo-ravines cut into the flysch base rock. In contrast, the opposite SW slopes are composed solely of flysch. The large dextral-slip Vipava fault extending in the NW-SE direction is present in the central part of the valley. Our research revealed that although the ravines on both slopes of the Vipava valley are lithologically and tectonically controlled, significant statistical differences in their directions exist. Thus, ravines on opposite slopes are not solely related to the Vipava fault system deformation, but instead reflect a more complex tectonic setting. We believe that the ravines are controlled by second-order faults and fault zones that connect the Vipava fault with adjacent faults. On the SW slopes, these include connecting faults between the Vipava and the southwestern Raša fault, with the ravines on the NE slopes formed in fault zones connecting the Vipava and northeastern Predjama faults.

Choice Experiments to Quantify Preferences for Health and Healthcare: State of the Practice.

PubMed

Mühlbacher, Axel; Johnson, F Reed

2016-06-01

Stated-preference methods increasingly are used to quantify preferences in health economics, health technology assessment, benefit-risk analysis and health services research. The objective of stated-preference studies is to acquire information about trade-off preferences among treatment outcomes, prioritization of clinical decision criteria, likely uptake or adherence to healthcare products and acceptability of healthcare services or policies. A widely accepted approach to eliciting preferences is discrete-choice experiments. Patient, physician, insurant or general-public respondents choose among constructed, experimentally controlled alternatives described by decision-relevant features or attributes. Attributes can represent complete health states, sets of treatment outcomes or characteristics of a healthcare system. The observed pattern of choice reveals how different respondents or groups of respondents implicitly weigh, value and assess different characteristics of treatments, products or services. An important advantage of choice experiments is their foundation in microeconomic utility theory. This conceptual framework provides tests of internal validity, guidance for statistical analysis of latent preference structures, and testable behavioural hypotheses. Choice experiments require expertise in survey-research methods, random-utility theory, experimental design and advanced statistical analysis. This paper should be understood as an introduction to setting up a basic experiment rather than an exhaustive critique of the latest findings and procedures. Where appropriate, we have identified topics of active research where a broad consensus has not yet been established.

Hydrological analysis in R: Topmodel and beyond

NASA Astrophysics Data System (ADS)

Buytaert, W.; Reusser, D.

2011-12-01

R is quickly gaining popularity in the hydrological sciences community. The wide range of statistical and mathematical functionality makes it an excellent tool for data analysis, modelling and uncertainty analysis. Topmodel was one of the first hydrological models being implemented as an R package and distributed through R's own distribution network CRAN. This facilitated pre- and postprocessing of data such as parameter sampling, calculation of prediction bounds, and advanced visualisation. However, apart from these basic functionalities, the package did not use many of the more advanced features of the R environment, especially from R's object oriented functionality. With R's increasing expansion in arenas such as high performance computing, big data analysis, and cloud services, we revisit the topmodel package, and use it as an example of how to build and deploy the next generation of hydrological models. R provides a convenient environment and attractive features to build and couple hydrological - and in extension other environmental - models, to develop flexible and effective data assimilation strategies, and to take the model beyond the individual computer by linking into cloud services for both data provision and computing. However, in order to maximise the benefit of these approaches, it will be necessary to adopt standards and ontologies for model interaction and information exchange. Some of those are currently being developed, such as the OGC web processing standards, while other will need to be developed.

Proceedings of the NASTRAN (Tradename) Users’ Colloquium (15th) Held in Kansas City, Missouri on 4-8 May 1987

DTIC Science & Technology

1987-08-01

HVAC duct hanger system over an extensive frequency range. The finite element, component mode synthesis, and statistical energy analysis methods are...800-5,000 Hz) analysis was conducted with Statistical Energy Analysis (SEA) coupled with a closed-form harmonic beam analysis program. These...resonances may be obtained by using a finer frequency increment. Statistical Energy Analysis The basic assumption used in SEA analysis is that within each band

Columbia/Willamette Skill Builders Consortium. Final Performance Report. Appendix 5B Anodizing Inc. (Aluminum Extrusion Manufacturing). Basic Measurement Math. Instructors' Reports and Sample Curriculum Materials.

ERIC Educational Resources Information Center

Taylor, Marjorie; And Others

Anodizing, Inc., Teamsters Local 162, and Mt. Hood Community College (Oregon) developed a workplace literacy program for workers at Anodizing. These workers did not have the basic skill competencies to benefit from company training efforts in statistical process control and quality assurance and were not able to advance to lead and supervisory…

Opportunities Unlimited: Minnesota Indians Adult Basic Education; Narrative and Statistical Evaluation Third Year 1971-72, with a Review of the First and Second Years.

ERIC Educational Resources Information Center

Vizenor, Gerald

Opportunities Unlimited is a State-wide program to provide adult basic education (ABE) and training for Indians on Minnesota reservations and in Indian communities. An administrative center in Bemidji serves communities on the Red Lake, White Earth, and Leech Lake Reservations, and a Duluth center provides ABE and training for communities on the…

A quantitative comparison of corrective and perfective maintenance

NASA Technical Reports Server (NTRS)

Henry, Joel; Cain, James

1994-01-01

This paper presents a quantitative comparison of corrective and perfective software maintenance activities. The comparison utilizes basic data collected throughout the maintenance process. The data collected are extensive and allow the impact of both types of maintenance to be quantitatively evaluated and compared. Basic statistical techniques test relationships between and among process and product data. The results show interesting similarities and important differences in both process and product characteristics.