"Mining" is the extraction of valuable materials from the core of the earth which are of great economic interest or importance. Traditionally, mining has been used at excavation sites for extraction of minerals like gold and copper. Data mining comprises of unearthing useful patterns from a data warehouse which is the source of integrated data. Data mining can also be used as a BI (Business Intelligence) tool to predict or derive useful patterns by the analysis of current and...

Topics: Data Mining, Data Analysis

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442

Feb 3, 2011
02/11

by
NASA; Langley Research Center

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NASA engineers and researchers use data analysis and measurement to predict solar storms, anticipate how they will affect the Earth, and improve our understanding of the Sun-Earth system. To license this film and get a higher quality version for broadcast/film purposes, contact A/V Geeks LLC .

Topics: NASA, data analysis, Sun

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816

Feb 3, 2011
02/11

by
NASA; Langley Research Center

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In this program, NASA engineers and researchers use data analysis and measurement to study the auroras, key regions of the Earth’s geospace or space environment. To license this film and get a higher quality version for broadcast/film purposes, contact A/V Geeks LLC .

Topics: NASA, data analysis, Earth

Quantitative Data Analysis Using Spss

Topic: Quantitative Data Analysis Using Spss

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610

Feb 6, 2011
02/11

by
NASA; Langley Research Center

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In Measurement, Ratios, and Graphing: 3…2…1…Crash!, students will learn the history of the National Aeronautics and Space Administration (NASA) and discover how NASA Langley Research Center improves aircraft performance and safety by conducting extreme tests such as crashing planes, skidding tires, and blasting water. Students will observe NASA engineers using measurement, ratios, and graphing to make predictions and draw conclusions during their extreme tests. Students will learn how...

Topics: NASA, aviation, aeronautics, data analysis

In today’s data-intensive world, the power to analyze huge amounts of data is critical to the success of any organization, including the military. Many data analysis tools have been developed in the past decade along with the high-performance machine learning algorithms. At present, many of these tools unfortunately are out of reach of the target audience—subject matter experts—because one must master some of the advanced computer science concepts to use these tools effectively. This...

Topics: data analysis, machine learning, Spark

In data mining, Cyber Crime management is an interesting application where it plays an important role in handling of crime data. Cyber Crime investigation has very significant role of police system in any country. There had been an enormous increase in the crime in recent years. With rapid popularity of the internet, crime information maintained in web is becoming increasingly rampant. In this paper the data mining techniques are used to analyze the web data. This paper presents detailed...

Topics: Crime data analysis, classification, clustering

Quantitative Data Analysis Using SPSS

Topic: Quantitative Data Analysis Using SPSS

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13

Jun 27, 2018
06/18

by
V. Kapoor

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The traditional approach of health risk modelling with multiple data sources proceeds via regression-based methods assuming a marginal distribution for the outcome variable. The data is collected for $N$ subjects over a $J$ time-period or from $J$ data sources. The response obtained from $i^{th}$ subject is $\vec{Y}_i=({Y}_{i1},\cdots, {Y}_{iJ})$. For $N$ subjects we obtain a $J$ dimensional joint distribution for the subjects. In this work we propose a novel approach of transforming any $J$...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1504.05796

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12

Jun 30, 2018
06/18

by
Gaurav Bhole; Abhishek Shukla; T. S. Mahesh

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Benford's law is a statistical inference to predict the frequency of significant digits in naturally occurring numerical databases. In such databases this law predicts a higher occurrence of the digit 1 in the most significant place and decreasing occurrences to other larger digits. Although counter-intuitive at first sight, Benford's law has seen applications in a wide variety of fields like physics, earth-science, biology, finance etc. In this work, we have explored the use of Benford's law...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1408.5735

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9.0

Jun 29, 2018
06/18

by
Luca Lista

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A simple computer-based algorithm has been developed to identify pre-modern coins minted from the same dies, intending mainly coins minted by hand-made dies designed to be applicable to images taken from auction websites or catalogs. Though the method is not intended to perform a complete automatic classification, which would require more complex and intensive algorithms accessible to experts of computer vision its simplicity of use and lack of specific requirement about the quality of pictures...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1604.04074

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4.0

Jun 29, 2018
06/18

by
Simon Labouesse; Awoke Negash; Jérôme Idier; Sébastien Bourguignon; Thomas Mangeat; Penghuan Liu; Anne Sentenac; Marc Allain

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The blind structured illumination microscopy (SIM) strategy proposed in (Mudry et al., 1992) is fully re-founded in this paper, unveiling the central role of the sparsity of the illumination patterns in the mechanism that drives super-resolution in the method. A numerical analysis shows that the resolving power of the method can be further enhanced with optimized one-photon or two-photon speckle illuminations. A much improved numerical implementation is provided for the reconstruction problem...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1607.01980

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8.0

Jun 30, 2018
06/18

by
Wagner S. de Lima; Emerson L. de Santa Helena

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q-Gaussian distribution appear in many science areas where we can find systems that could be described within a nonextensive framework. Usually, a way to assert that these systems belongs to nonextensive framework is by means of numerical data analysis. To this end, we implement random number generator for q-Gaussian distribution, while we present how to computing its probability density function, cumulative density function and quantile function besides a tail weight measurement using robust...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1703.06172

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6.0

Jun 30, 2018
06/18

by
James M. McCracken; Robert S. Weigel

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Convergent Cross-Mapping (CCM) is a technique for computing specific kinds of correlations between sets of times series. It was introduced by Sugihara et al. and is reported to be "a necessary condition for causation" capable of distinguishing causality from standard correlation. We show that the relationships between CCM correlations proposed in \cite{Sugihara2012} do not, in general, agree with intuitive concepts of "driving", and as such, should not be considered...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1407.5696

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9.0

Jun 27, 2018
06/18

by
Sergio Davis

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It is shown that a consistent application of Bayesian updating from a prior probability density to a posterior using evidence in the form of expectation constraints leads to exactly the same results as the application of the maximum entropy principle, namely a posterior belonging to the exponential family. The Bayesian updating procedure presented in this work is not expressed as a variational principle, and does not involve the concept of entropy. Therefore it conceptually constitutes a...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1503.03451

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4.0

Jun 30, 2018
06/18

by
Denis Horvath; Jozef Ulicny; Branislav Brutovsky

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Classical metric and non-metric multidimensional scaling (MDS) variants are widely known manifold learning (ML) methods which enable construction of low dimensional representation (projections) of high dimensional data inputs. However, their use is crucially limited to the cases when data are inherently reducible to low dimensionality. In general, drawbacks and limitations of these, as well as pure, MDS variants become more apparent when the exploration (learning) is exposed to the structured...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1406.3440

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4.0

Jun 30, 2018
06/18

by
Uziel Sandler

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In this paper, we show how to study the evolution of a system, given imprecise knowledge about the state of the system and the dynamics laws. Our approach is based on Fuzzy Set Theory, and it will be shown that the \emph{Fuzzy Dynamics} of a $n$-dimensional system is equivalent to Lagrangian (or Hamiltonian) mechanics in a $n+1$-dimensional space. In some cases, however, the corresponding Lagrangian is more general than the usual one and could depend on the action. In this case, Lagrange's...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1405.3600

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7.0

Jun 28, 2018
06/18

by
Jérôme Idier; Simon Labouesse; Marc Allain; Penghuan Liu; Sébastien Bourguignon; Anne Sentenac

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Speckle based imaging consists in forming a super- resolved reconstruction of an unknown sample from low- resolution images obtained under random inhomogeneous illuminations (speckles). In a blind context where the illuminations are unknown, we study the intrinsic capacity to recover spatial frequencies beyond the cut-off frequency, without a priori assumption on the sample. We demonstrate that, under physically realistic conditions, the correlation of the data have a super-resolution power...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1512.06260

Journal of Research of the National Institute of Standards and Technology

Topics: experiments, accuracy assessment, data analysis, instruments

7
7.0

Jun 30, 2018
06/18

by
Javier E. Contreras-Reyes

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In this paper, we provide the R\'enyi entropy and complexity measure for a novel, flexible class of skew-gaussian distributions and their related families, as a characteristic form of the skew-gaussian Shannon entropy. We give closed expressions considering a more general class of closed skew-gaussian distributions and the weighted moments estimation method. In addition, closed expressions of R\'enyi entropy are presented for extended skew-gaussian and truncated skew-gaussian distributions....

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1406.0111

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5.0

Jun 30, 2018
06/18

by
Luca Lista

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The best linear unbiased estimator (BLUE) is a popular statistical method adopted to combine multiple measurements of the same observable taking into account individual uncertainties and their correlation. The method is unbiased by construction if the true uncertainties and their correlation are known, but it may exhibit a bias if uncertainty estimates are used in place of the true ones, in particular if those estimated uncertainties depend on measured values. This is the case for instance when...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1405.3425

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Jun 28, 2018
06/18

by
Shintaro Mori; Masafumi Hino; Masato Hisakado; Taiki Takahashi

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We propose a method of detecting non-self-correcting information cascades in experiments in which subjects choose an option sequentially by observing the choices of previous subjects. The method uses the correlation function $C(t)$ between the first and the $t+1$-th subject's choices. $C(t)$ measures the strength of the domino effect, and the limit value $c\equiv \lim_{t\to \infty}C(t)$ determines whether the domino effect lasts forever $(c>0)$ or not $(c=0)$. The condition $c>0$ is an...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1507.07265

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31

Jun 27, 2018
06/18

by
Giulio D'Agostini

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The properties of the normal distribution under linear transformation, as well the easy way to compute the covariance matrix of marginals and conditionals, offer a unique opportunity to get an insight about several aspects of uncertainties in measurements. The way to build the overall covariance matrix in a few, but conceptually relevant cases is illustrated: several observations made with (possibly) different instruments measuring the same quantity; effect of systematics (although limited to...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1504.02065

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4.0

Jun 29, 2018
06/18

by
Elliot A. Martin; Jaroslav Hlinka; Alexander Meinke; Filip Děchtěrenko; Jörn Davidsen

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Maximum entropy estimation is of broad interest for inferring properties of systems across many different disciplines. In this work, we significantly extend a technique we previously introduced for estimating the maximum entropy of a set of random discrete variables when conditioning on bivariate mutual informations and univariate entropies. Specifically, we show how to apply the concept to continuous random variables and vastly expand the types of information-theoretic quantities one can...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1601.00336

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5.0

Jun 29, 2018
06/18

by
Dorothee Hüser; Jonathan Hüser; Sebastian Rief; Jörg Seewig; Peter Thomsen-Schmidt

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Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of reproducibility (homogeneity) of the specimen. This makes it difficult to discriminate between different values of single roughness parameters. Therefore uncertainty assessment methods are required that take all relevant aspects into account. In the...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1603.00746

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3.0

Jun 29, 2018
06/18

by
Luca Lista

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The most accurate method to combine measurement from different experiments is to build a combined likelihood function and use it to perform the desired inference. This is not always possible for various reasons, hence approximate methods are often convenient. Among those, the best linear unbiased estimator (BLUE) is the most popular, allowing to take into account individual uncertainties and their correlations. The method is unbiased by construction if the true uncertainties and their...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1610.00422

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15

Jun 29, 2018
06/18

by
Carlos Mana

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Notes for a Course on Probability and Statistics: L1: Elements of Probability; L2: Bayesian Inference; L3: Monte Carlo Methods

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1610.05590

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20

Jun 27, 2018
06/18

by
Aashay Patil; M. S. Santhanam

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Correlation and similarity measures are widely used in all the areas of sciences and social sciences. Often the variables are not numbers but are instead qualitative descriptors called categorical data. We define and study similarity matrix, as a measure of similarity, for the case of categorical data. This is of interest due to a deluge of categorical data, such as movie ratings, top-10 rankings and data from social media, in the public domain that require analysis. We show that the...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1503.06559

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3.0

Jun 30, 2018
06/18

by
Mariia Sorokina; Stylianos Sygletos; Sergei Turitsyn

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We introduce low complexity machine learning based approach for mitigating nonlinear impairments in optical fiber communications systems. The immense intricacy of the problem calls for the development of "smart" methodology, simplifying the analysis without losing the key features that are important for recovery of transmitted data. The proposed sparse identification method for optical systems (SINO) allows to determine the minimal (optimal) number of degrees of freedom required for...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1701.01650

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4.0

Jun 30, 2018
06/18

by
Iliusi Vega; Christof Schütte; Tim O. F. Conrad

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In the framework of time series analysis with recurrence networks, we introduce a self-adaptive method that determines the elusive recurrence threshold and identifies metastable states in complex real-world time series. As initial step, we introduce a way to set the embedding parameters used to reconstruct the state space from the time series. We set them as the ones giving the maximum Shannon entropy for the first simultaneous minima of recurrence rate and Shannon entropy. To identify...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1404.7807

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21

Jun 30, 2018
06/18

by
J. Ocariz

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Lectures presented at the 1st CERN Asia-Europe-Pacific School of High-Energy Physics, Fukuoka, Japan, 14-27 October 2012. A pedagogical selection of topics in probability and statistics is presented. Choice and emphasis are driven by the author's personal experience, predominantly in the context of physics analyses using experimental data from high-energy physics detectors.

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1405.3402

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11

Jun 28, 2018
06/18

by
Anna Deluca; Pedro Puig; Alvaro Corral

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One of the key clues to consider rainfall as a self-organized critical phenomenon is the existence of power-law distributions for rain-event sizes. We have studied the problem of universality in the exponents of these distributions by means of a suitable statistic whose distribution is inferred by several variations of a permutational test. In contrast to more common approaches, our procedure does not suffer from the difficulties of multiple testing and does not require the precise knowledge of...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1508.06516

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5.0

Jun 30, 2018
06/18

by
Mohamed H. Dridi

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For the verification and validation of microscopic simulation models of pedestrian flow, we have performed experiments for different kind of facilities and sites where most conflicts and congestion happens e.g. corridors, narrow passages, and crosswalks. The validity of the model should compare the experimental conditions and simulation results with video recording carried out in the same condition like in real life e.g. pedestrian flux and density distributions. The strategy in this technique...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1410.0603

4
4.0

Jun 30, 2018
06/18

by
Yong Zou; Reik V. Donner; Jürgen Kurths

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Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm (Liu \textit{et...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1409.3613

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5.0

Jun 29, 2018
06/18

by
Rafał Połoczański; Agnieszka Wyłomańska; Janusz Gajda; Monika Maciejewska; Andrzej Szczurek

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The continuous time random walk model plays an important role in modeling of so called anomalous diffusion behaviour. One of the specific property of such model are constant time periods visible in trajectory. In the continuous time random walk approach they are realizations of the sequence called waiting times. The main attention of the paper is paid on the analysis of waiting times distribution. We introduce here novel methods of estimation and statistical investigation of such distribution....

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1604.02653

5
5.0

Jun 28, 2018
06/18

by
Tanja A. Mücke; Matthias Wächter; Patrick Milan; Joachim Peinke

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Based on the Langevin equation it has been proposed to obtain power curves for wind turbines from high frequency data of wind speed measurements u(t) and power output P (t). The two parts of the Langevin approach, power curve and drift field, give a comprehensive description of the conversion dynamic over the whole operating range of the wind turbine. The method deals with high frequent data instead of 10 min means. It is therefore possible to gain a reliable power curve already from a small...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1511.01765

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8.0

Jun 29, 2018
06/18

by
Afef Cherni; Emilie Chouzenoux; Marc-André Delsuc

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NMR is a tool of choice for the measure of diffusion coefficients of species in solution. The DOSY experiment, a 2D implementation of this measure, has proven to be particularly useful for the study of complex mixtures, molecular interactions, polymers, etc. However, DOSY data analysis requires to resort to inverse Laplace transform, in particular for polydisperse samples. This is a known difficult numerical task, for which we present here a novel approach. A new algorithm based on a splitting...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1608.07055

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4.0

Jun 30, 2018
06/18

by
Aleksei Lokhov; Fyodor Tkachov

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The method of quasi-optimal weights is applied to constructing (quasi-)optimal criteria for various anomalous contributions in experimental spectra. Anomalies in the spectra could indicate physics beyond the Standard Model (additional interactions and neutrino flavours, Lorenz violation etc.). In particular the cumulative tritium $\beta$-decay spectrum (for instance, in Troitsk-$\nu$-mass, Mainz Neutrino Mass and KATRIN experiments) is analysed using the derived special criteria. Using the...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1411.6245

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9.0

Jun 30, 2018
06/18

by
Luca M. Ghiringhelli; Jan Vybiral; Sergey V. Levchenko; Claudia Draxl; Matthias Scheffler

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Statistical learning of materials properties or functions so far starts with a largely silent, non-challenged step: the choice of the set of descriptive parameters (termed descriptor). However, when the scientific connection between the descriptor and the actuating mechanisms is unclear, causality of the learned descriptor-property relation is uncertain. Thus, trustful prediction of new promising materials, identification of anomalies, and scientific advancement are doubtful. We analyse this...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1411.7437

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6.0

Jun 26, 2018
06/18

by
Ladislav Kristoufek

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In this note, we investigate possible relationships between the bivariate Hurst exponent $H_{xy}$ and an average of the separate Hurst exponents $\frac{1}{2}(H_x+H_y)$. We show that two cases are well theoretically founded. These are the cases when $H_{xy}=\frac{1}{2}(H_x+H_y)$ and $H_{xy} \frac{1}{2}(H_x+H_y)$ is not possible regardless of stationarity issues. Further discussion of the implications is provided as well together with a note on the finite sample effect.

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1501.02947

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5.0

Jun 30, 2018
06/18

by
Ashif Sikandar Iquebal; Satish Bukkapatnam; Arun Srinivasa

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We present an approach for real-time change detection in the transient phases of complex dynamical systems based on tracking the local phase and amplitude synchronization among the components of a univariate time series signal derived via Intrinsic Time scale Decomposition (ITD)--a nonlinear, non-parametric analysis method. We investigate the properties of ITD components and show that the expected level of phase synchronization at a given change point may be enhanced by more than 4 folds when...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1701.00610

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4.0

Jun 30, 2018
06/18

by
Ardeshir Mohammad Ebtehaj; Efi Foufoula-Georgiou; Gilad Lerman; Rafael Luis Bras

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We demonstrate that the global fields of temperature, humidity and geopotential heights admit a nearly sparse representation in the wavelet domain, offering a viable path forward to explore new paradigms of sparsity-promoting data assimilation and compressive recovery of land surface-atmospheric states from space. We illustrate this idea using retrieval products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) on board the Aqua satellite. The results reveal...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1409.5068

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3.0

Jun 30, 2018
06/18

by
Jérémy Schmitt; Nelly Pustelnik; Pierre Borgnat; Patrick Flandrin; Laurent Condat

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This work proposes an extension of the 1-D Hilbert Huang transform for the analysis of images. The proposed method consists in (i) adaptively decomposing an image into oscillating parts called intrinsic mode functions (IMFs) using a mode decomposition procedure, and (ii) providing a local spectral analysis of the obtained IMFs in order to get the local amplitudes, frequencies, and orientations. For the decomposition step, we propose two robust 2-D mode decompositions based on non-smooth convex...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1404.7680

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4.0

Jun 30, 2018
06/18

by
Luca Perotti; Daniel Vrinceanu; Daniel Bessis

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We present a new method to locate the starting points in time of an arbitrary number of (damped) delayed signals. For a finite data sequence, the method permits to first locate the starting point of the component with the longest delay, and then --by iteration-- all the preceding ones. Numerical examples are given and noise sensitivity is tested for weak noise.

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1703.07001

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Jun 26, 2018
06/18

by
G. D'Amico; F. Petroni; F. Prattico

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Modeling wind speed is one of the key element when dealing with the production of energy through wind turbines. A good model can be used for forecasting, site evaluation, turbines design and many other purposes. In this work we are interested in the analysis of the future financial cash flows generated by selling the electrical energy produced. We apply an indexed semi-Markov model of wind speed that has been shown, in previous investigation, to reproduce accurately the statistical behavior of...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1502.03205

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17

Jun 26, 2018
06/18

by
Nico Reinke; André Fuchs; Wided Medjroubi; Pedro G. Lind; Matthias Wächter; Joachim Peinke

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We describe a simple stochastic method, so-called Langevin approach, which enables one to extract evolution equations of stochastic variables from a set of measurements. Our method is parameter-free and it is based on the nonlinear Langevin equation. Moreover, it can be applied not only to processes in time, but also to processes in scale, given that the data available shows ergodicity. This chapter introduces the mathematical foundations of the Langevin approach and describes how to implement...

Topics: Physics, Data Analysis, Statistics and Probability

Source: http://arxiv.org/abs/1502.05253

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4.0

Jun 29, 2018
06/18

by
Andrey Kamenshchikov

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A problem of a new physical model test given observed experimental data is a typical one for modern experiments of high energy physics (HEP). A solution of the problem may be provided with two alternative statistical formalisms, namely frequentist and Bayesian, which are widely spread in contemporary HEP searches. A characteristic experimental situation is modeled from general considerations and both the approaches are utilized in order to test a new model. The results are juxtaposed, what...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1607.04141

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8.0

Jun 29, 2018
06/18

by
Daniel Harnack; Erik Laminski; Klaus Richard Pawelzik

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Discovery of causal relations is fundamental for understanding the dynamics of complex systems. While causal interactions are well defined for acyclic systems that can be separated into causally effective subsystems, a mathematical definition of gradual causal interaction is still lacking for nonseparable dynamical systems. The solution proposed here is analytically tractable for time discrete chaotic maps and is shown to fulfill basic requirements for causality measures. It implies a method...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1605.02570

Controlling the outbreak of epidemic diseases such as influenza has always been a concern for the United States. Traditional surveillance tools such as the ILINet and Virologic provide the Centers for Disease Control and Prevention (CDC) with influenza surveillance statistics at a lag of 1 to 2 weeks. The CDC requires a tool that can forecast the level of influenza activity. The rise in the popularity of social media websites such as Flickr, Twitter and Facebook has transformed the web into an...

Topics: correlation, data analysis, Twitter, tweet, influenza

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Jun 27, 2018
06/18

by
Okpeafoh S. Agimelen; Anna Jawor-Baczynska; John McGinty; Christos Tachtatzis; Jerzy Dziewierz; Ian Haley; Jan Sefcik; Anthony J. Mulholland

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Efficient processing of particulate products across various manufacturing steps requires that particles possess desired attributes such as size and shape. Controlling the particle production process to obtain required attributes will be greatly facilitated using robust algorithms providing the size and shape information of the particles from in situ measurements. However, obtaining particle size and shape information in situ during manufacturing has been a big challenge. This is because the...

Topics: Data Analysis, Statistics and Probability, Physics

Source: http://arxiv.org/abs/1505.03320